Pandas Comprehensive Tutorial: From Zero To Hero in ONE Hour.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "200a0ef2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import polars as pl\n",
    "\n",
    "import plotly.express as px\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "\n",
    "# pandas option to print more columns\n",
    "pd.options.display.max_columns = 1000"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6e520f1",
   "metadata": {},
   "source": [
    "# Pandas: Comprehensive Tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d016fcee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://raw.githubusercontent.com/martinbel/datasets/master/'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# File Path\n",
    "base_url = \"https://raw.githubusercontent.com/martinbel/datasets/master/\"\n",
    "base_url"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2680d6b5",
   "metadata": {},
   "source": [
    "# 1. Read Data From CSV or Parquet Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "831216d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Case Number</th>\n",
       "      <th>Date</th>\n",
       "      <th>Year</th>\n",
       "      <th>Type</th>\n",
       "      <th>Country</th>\n",
       "      <th>Area</th>\n",
       "      <th>Location</th>\n",
       "      <th>Activity</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Injury</th>\n",
       "      <th>Fatal (Y/N)</th>\n",
       "      <th>Time</th>\n",
       "      <th>Species</th>\n",
       "      <th>Investigator or Source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>Case Number.1</th>\n",
       "      <th>Case Number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>Unnamed: 22</th>\n",
       "      <th>Unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>09-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Invalid</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Habush, Oahu</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>John Denges</td>\n",
       "      <td>M</td>\n",
       "      <td>48</td>\n",
       "      <td>Injury to left lower leg from surfboard skeg</td>\n",
       "      <td>N</td>\n",
       "      <td>07h45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.09-Denges.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>6301.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>08-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Arrawarra Headland</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>male</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Minor injury to lower leg</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 m shark</td>\n",
       "      <td>B. Myatt, GSAF</td>\n",
       "      <td>2018.06.08-Arrawarra.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>6300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>04-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>MEXICO</td>\n",
       "      <td>Colima</td>\n",
       "      <td>La Ticla</td>\n",
       "      <td>Free diving</td>\n",
       "      <td>Gustavo Ramos</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lacerations to leg &amp; hand shark PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tiger shark, 3m</td>\n",
       "      <td>A .Kipper</td>\n",
       "      <td>2018.06.04-Ramos.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>6299.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Case Number         Date    Year        Type    Country             Area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating        USA       California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked        USA          Georgia   \n",
       "2  2018.06.09  09-Jun-2018  2018.0     Invalid        USA           Hawaii   \n",
       "3  2018.06.08  08-Jun-2018  2018.0  Unprovoked  AUSTRALIA  New South Wales   \n",
       "4  2018.06.04  04-Jun-2018  2018.0    Provoked     MEXICO           Colima   \n",
       "\n",
       "                         Location     Activity             Name Sex   Age  \\\n",
       "0     Oceanside, San Diego County     Paddling      Julie Wolfe    F   57   \n",
       "1  St. Simon Island, Glynn County     Standing  Adyson McNeely     F   11   \n",
       "2                    Habush, Oahu      Surfing      John Denges    M   48   \n",
       "3              Arrawarra Headland      Surfing             male    M  NaN   \n",
       "4                        La Ticla  Free diving   Gustavo Ramos     M  NaN   \n",
       "\n",
       "                                              Injury Fatal (Y/N)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "2       Injury to left lower leg from surfboard skeg           N   \n",
       "3                          Minor injury to lower leg           N   \n",
       "4  Lacerations to leg & hand shark PROVOKED INCIDENT           N   \n",
       "\n",
       "            Time         Species           Investigator or Source  \\\n",
       "0          18h00      White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00              NaN  K.McMurray, TrackingSharks.com   \n",
       "2          07h45              NaN  K.McMurray, TrackingSharks.com   \n",
       "3            NaN        2 m shark                  B. Myatt, GSAF   \n",
       "4            NaN  Tiger shark, 3m                       A .Kipper   \n",
       "\n",
       "                        pdf  \\\n",
       "0      2018.06.25-Wolfe.pdf   \n",
       "1    2018.06.18-McNeely.pdf   \n",
       "2     2018.06.09-Denges.pdf   \n",
       "3  2018.06.08-Arrawarra.pdf   \n",
       "4      2018.06.04-Ramos.pdf   \n",
       "\n",
       "                                        href formula  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href Case Number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.09   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.08   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.04   \n",
       "\n",
       "  Case Number.2  original order Unnamed: 22 Unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  \n",
       "2    2018.06.09          6301.0         NaN         NaN  \n",
       "3    2018.06.08          6300.0         NaN         NaN  \n",
       "4    2018.06.04          6299.0         NaN         NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# \n",
    "df_sharks = pd.read_csv(base_url + \"attacks.csv\", encoding='cp1252')\n",
    "df_sharks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "912e384b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>AAL</th>\n",
       "      <th>AAP</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>ABBV</th>\n",
       "      <th>ABC</th>\n",
       "      <th>ABT</th>\n",
       "      <th>ACGL</th>\n",
       "      <th>ACN</th>\n",
       "      <th>ADBE</th>\n",
       "      <th>ADI</th>\n",
       "      <th>ADM</th>\n",
       "      <th>ADP</th>\n",
       "      <th>ADSK</th>\n",
       "      <th>AEE</th>\n",
       "      <th>AEP</th>\n",
       "      <th>AES</th>\n",
       "      <th>AFL</th>\n",
       "      <th>AIG</th>\n",
       "      <th>AIZ</th>\n",
       "      <th>AJG</th>\n",
       "      <th>AKAM</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALGN</th>\n",
       "      <th>ALK</th>\n",
       "      <th>ALL</th>\n",
       "      <th>ALLE</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>AMCR</th>\n",
       "      <th>AMD</th>\n",
       "      <th>AME</th>\n",
       "      <th>AMGN</th>\n",
       "      <th>AMP</th>\n",
       "      <th>AMT</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>ANET</th>\n",
       "      <th>ANSS</th>\n",
       "      <th>AON</th>\n",
       "      <th>AOS</th>\n",
       "      <th>APA</th>\n",
       "      <th>APD</th>\n",
       "      <th>APH</th>\n",
       "      <th>APTV</th>\n",
       "      <th>ARE</th>\n",
       "      <th>ATO</th>\n",
       "      <th>ATVI</th>\n",
       "      <th>AVB</th>\n",
       "      <th>AVGO</th>\n",
       "      <th>AVY</th>\n",
       "      <th>AWK</th>\n",
       "      <th>AXP</th>\n",
       "      <th>AZO</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAC</th>\n",
       "      <th>BALL</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BBWI</th>\n",
       "      <th>BBY</th>\n",
       "      <th>BDX</th>\n",
       "      <th>BEN</th>\n",
       "      <th>BFB</th>\n",
       "      <th>BG</th>\n",
       "      <th>BIIB</th>\n",
       "      <th>BIO</th>\n",
       "      <th>BK</th>\n",
       "      <th>BKNG</th>\n",
       "      <th>BKR</th>\n",
       "      <th>BLK</th>\n",
       "      <th>BMY</th>\n",
       "      <th>BR</th>\n",
       "      <th>BRKB</th>\n",
       "      <th>BRO</th>\n",
       "      <th>BSX</th>\n",
       "      <th>BWA</th>\n",
       "      <th>BXP</th>\n",
       "      <th>C</th>\n",
       "      <th>CAG</th>\n",
       "      <th>CAH</th>\n",
       "      <th>CARR</th>\n",
       "      <th>CAT</th>\n",
       "      <th>CB</th>\n",
       "      <th>CBOE</th>\n",
       "      <th>CBRE</th>\n",
       "      <th>CCI</th>\n",
       "      <th>CCL</th>\n",
       "      <th>CDAY</th>\n",
       "      <th>CDNS</th>\n",
       "      <th>CDW</th>\n",
       "      <th>CE</th>\n",
       "      <th>CEG</th>\n",
       "      <th>CF</th>\n",
       "      <th>CFG</th>\n",
       "      <th>CHD</th>\n",
       "      <th>CHRW</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>CI</th>\n",
       "      <th>CINF</th>\n",
       "      <th>CL</th>\n",
       "      <th>CLX</th>\n",
       "      <th>CMA</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CME</th>\n",
       "      <th>CMG</th>\n",
       "      <th>CMI</th>\n",
       "      <th>CMS</th>\n",
       "      <th>CNC</th>\n",
       "      <th>CNP</th>\n",
       "      <th>COF</th>\n",
       "      <th>COO</th>\n",
       "      <th>COP</th>\n",
       "      <th>COST</th>\n",
       "      <th>CPB</th>\n",
       "      <th>CPRT</th>\n",
       "      <th>CPT</th>\n",
       "      <th>CRL</th>\n",
       "      <th>CRM</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>CSGP</th>\n",
       "      <th>CSX</th>\n",
       "      <th>CTAS</th>\n",
       "      <th>CTLT</th>\n",
       "      <th>CTRA</th>\n",
       "      <th>CTSH</th>\n",
       "      <th>CTVA</th>\n",
       "      <th>CVS</th>\n",
       "      <th>CVX</th>\n",
       "      <th>CZR</th>\n",
       "      <th>D</th>\n",
       "      <th>DAL</th>\n",
       "      <th>DD</th>\n",
       "      <th>DE</th>\n",
       "      <th>DFS</th>\n",
       "      <th>DG</th>\n",
       "      <th>DGX</th>\n",
       "      <th>DHI</th>\n",
       "      <th>DHR</th>\n",
       "      <th>DIS</th>\n",
       "      <th>DISH</th>\n",
       "      <th>DLR</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>DOV</th>\n",
       "      <th>DOW</th>\n",
       "      <th>DPZ</th>\n",
       "      <th>DRI</th>\n",
       "      <th>DTE</th>\n",
       "      <th>DUK</th>\n",
       "      <th>DVA</th>\n",
       "      <th>DVN</th>\n",
       "      <th>DXC</th>\n",
       "      <th>DXCM</th>\n",
       "      <th>EA</th>\n",
       "      <th>EBAY</th>\n",
       "      <th>ECL</th>\n",
       "      <th>ED</th>\n",
       "      <th>EFX</th>\n",
       "      <th>EIX</th>\n",
       "      <th>EL</th>\n",
       "      <th>ELV</th>\n",
       "      <th>EMN</th>\n",
       "      <th>EMR</th>\n",
       "      <th>ENPH</th>\n",
       "      <th>EOG</th>\n",
       "      <th>EPAM</th>\n",
       "      <th>EQIX</th>\n",
       "      <th>EQR</th>\n",
       "      <th>EQT</th>\n",
       "      <th>ES</th>\n",
       "      <th>ESM3</th>\n",
       "      <th>ESS</th>\n",
       "      <th>ETN</th>\n",
       "      <th>ETR</th>\n",
       "      <th>ETSY</th>\n",
       "      <th>EVRG</th>\n",
       "      <th>EW</th>\n",
       "      <th>EXC</th>\n",
       "      <th>EXPD</th>\n",
       "      <th>EXPE</th>\n",
       "      <th>EXR</th>\n",
       "      <th>F</th>\n",
       "      <th>FANG</th>\n",
       "      <th>FAST</th>\n",
       "      <th>FCX</th>\n",
       "      <th>FDS</th>\n",
       "      <th>FDX</th>\n",
       "      <th>FE</th>\n",
       "      <th>FFIV</th>\n",
       "      <th>FICO</th>\n",
       "      <th>FIS</th>\n",
       "      <th>FISV</th>\n",
       "      <th>FITB</th>\n",
       "      <th>FLT</th>\n",
       "      <th>FMC</th>\n",
       "      <th>FOX</th>\n",
       "      <th>FOXA</th>\n",
       "      <th>FRC</th>\n",
       "      <th>FRT</th>\n",
       "      <th>FSLR</th>\n",
       "      <th>FTNT</th>\n",
       "      <th>FTV</th>\n",
       "      <th>GD</th>\n",
       "      <th>GE</th>\n",
       "      <th>GEHC</th>\n",
       "      <th>GEN</th>\n",
       "      <th>GILD</th>\n",
       "      <th>GIS</th>\n",
       "      <th>GL</th>\n",
       "      <th>GLW</th>\n",
       "      <th>GM</th>\n",
       "      <th>GNRC</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>GPC</th>\n",
       "      <th>GPN</th>\n",
       "      <th>GRMN</th>\n",
       "      <th>GS</th>\n",
       "      <th>GWW</th>\n",
       "      <th>HAL</th>\n",
       "      <th>HAS</th>\n",
       "      <th>HBAN</th>\n",
       "      <th>HCA</th>\n",
       "      <th>HD</th>\n",
       "      <th>HES</th>\n",
       "      <th>HIG</th>\n",
       "      <th>HII</th>\n",
       "      <th>HLT</th>\n",
       "      <th>HOLX</th>\n",
       "      <th>HON</th>\n",
       "      <th>HPE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>HRL</th>\n",
       "      <th>HSIC</th>\n",
       "      <th>HST</th>\n",
       "      <th>HSY</th>\n",
       "      <th>HUM</th>\n",
       "      <th>HWM</th>\n",
       "      <th>HYG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>ICE</th>\n",
       "      <th>IDXX</th>\n",
       "      <th>IEX</th>\n",
       "      <th>IFF</th>\n",
       "      <th>ILMN</th>\n",
       "      <th>INCY</th>\n",
       "      <th>INTC</th>\n",
       "      <th>INTU</th>\n",
       "      <th>INVH</th>\n",
       "      <th>IP</th>\n",
       "      <th>IPG</th>\n",
       "      <th>IQV</th>\n",
       "      <th>IR</th>\n",
       "      <th>IRM</th>\n",
       "      <th>ISRG</th>\n",
       "      <th>IT</th>\n",
       "      <th>ITW</th>\n",
       "      <th>IVZ</th>\n",
       "      <th>IWM</th>\n",
       "      <th>J</th>\n",
       "      <th>JBHT</th>\n",
       "      <th>JCI</th>\n",
       "      <th>JKHY</th>\n",
       "      <th>JNJ</th>\n",
       "      <th>JNPR</th>\n",
       "      <th>JPM</th>\n",
       "      <th>K</th>\n",
       "      <th>KDP</th>\n",
       "      <th>KEY</th>\n",
       "      <th>KEYS</th>\n",
       "      <th>KHC</th>\n",
       "      <th>KIM</th>\n",
       "      <th>KLAC</th>\n",
       "      <th>KMB</th>\n",
       "      <th>KMI</th>\n",
       "      <th>KMX</th>\n",
       "      <th>KO</th>\n",
       "      <th>KR</th>\n",
       "      <th>L</th>\n",
       "      <th>LDOS</th>\n",
       "      <th>LEN</th>\n",
       "      <th>LH</th>\n",
       "      <th>LHX</th>\n",
       "      <th>LIN</th>\n",
       "      <th>LKQ</th>\n",
       "      <th>LLY</th>\n",
       "      <th>LMT</th>\n",
       "      <th>LNC</th>\n",
       "      <th>LNT</th>\n",
       "      <th>LOW</th>\n",
       "      <th>LQD</th>\n",
       "      <th>LRCX</th>\n",
       "      <th>LUV</th>\n",
       "      <th>LVS</th>\n",
       "      <th>LW</th>\n",
       "      <th>LYB</th>\n",
       "      <th>LYV</th>\n",
       "      <th>MA</th>\n",
       "      <th>MAA</th>\n",
       "      <th>MAR</th>\n",
       "      <th>MAS</th>\n",
       "      <th>MCD</th>\n",
       "      <th>MCHP</th>\n",
       "      <th>MCK</th>\n",
       "      <th>MCO</th>\n",
       "      <th>MDLZ</th>\n",
       "      <th>MDT</th>\n",
       "      <th>MET</th>\n",
       "      <th>META</th>\n",
       "      <th>MGM</th>\n",
       "      <th>MHK</th>\n",
       "      <th>MKC</th>\n",
       "      <th>MKTX</th>\n",
       "      <th>MLM</th>\n",
       "      <th>MMC</th>\n",
       "      <th>MMM</th>\n",
       "      <th>MNST</th>\n",
       "      <th>MO</th>\n",
       "      <th>MOH</th>\n",
       "      <th>MOS</th>\n",
       "      <th>MPC</th>\n",
       "      <th>MPWR</th>\n",
       "      <th>MRK</th>\n",
       "      <th>MRNA</th>\n",
       "      <th>MRO</th>\n",
       "      <th>MS</th>\n",
       "      <th>MSCI</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>MSI</th>\n",
       "      <th>MTB</th>\n",
       "      <th>MTCH</th>\n",
       "      <th>MTD</th>\n",
       "      <th>MU</th>\n",
       "      <th>NCLH</th>\n",
       "      <th>NDAQ</th>\n",
       "      <th>NDSN</th>\n",
       "      <th>NEE</th>\n",
       "      <th>NEM</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>NI</th>\n",
       "      <th>NKE</th>\n",
       "      <th>NOC</th>\n",
       "      <th>NOW</th>\n",
       "      <th>NRG</th>\n",
       "      <th>NSC</th>\n",
       "      <th>NTAP</th>\n",
       "      <th>NTRS</th>\n",
       "      <th>NUE</th>\n",
       "      <th>NVDA</th>\n",
       "      <th>NVR</th>\n",
       "      <th>NWL</th>\n",
       "      <th>NWS</th>\n",
       "      <th>NWSA</th>\n",
       "      <th>NXPI</th>\n",
       "      <th>O</th>\n",
       "      <th>ODFL</th>\n",
       "      <th>OGN</th>\n",
       "      <th>OKE</th>\n",
       "      <th>OMC</th>\n",
       "      <th>ON</th>\n",
       "      <th>ORCL</th>\n",
       "      <th>ORLY</th>\n",
       "      <th>OTIS</th>\n",
       "      <th>OXY</th>\n",
       "      <th>PARA</th>\n",
       "      <th>PAYC</th>\n",
       "      <th>PAYX</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PCG</th>\n",
       "      <th>PEAK</th>\n",
       "      <th>PEG</th>\n",
       "      <th>PEP</th>\n",
       "      <th>PFE</th>\n",
       "      <th>PFG</th>\n",
       "      <th>PG</th>\n",
       "      <th>PGR</th>\n",
       "      <th>PH</th>\n",
       "      <th>PHM</th>\n",
       "      <th>PKG</th>\n",
       "      <th>PKI</th>\n",
       "      <th>PLD</th>\n",
       "      <th>PM</th>\n",
       "      <th>PNC</th>\n",
       "      <th>PNR</th>\n",
       "      <th>PNW</th>\n",
       "      <th>PODD</th>\n",
       "      <th>POOL</th>\n",
       "      <th>PPG</th>\n",
       "      <th>PPL</th>\n",
       "      <th>PRU</th>\n",
       "      <th>PSA</th>\n",
       "      <th>PSX</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PWR</th>\n",
       "      <th>PXD</th>\n",
       "      <th>PYPL</th>\n",
       "      <th>QCOM</th>\n",
       "      <th>QQQ</th>\n",
       "      <th>QRVO</th>\n",
       "      <th>RCL</th>\n",
       "      <th>RE</th>\n",
       "      <th>REG</th>\n",
       "      <th>REGN</th>\n",
       "      <th>RF</th>\n",
       "      <th>RHI</th>\n",
       "      <th>RJF</th>\n",
       "      <th>RL</th>\n",
       "      <th>RMD</th>\n",
       "      <th>ROK</th>\n",
       "      <th>ROL</th>\n",
       "      <th>ROP</th>\n",
       "      <th>ROST</th>\n",
       "      <th>RSG</th>\n",
       "      <th>RTX</th>\n",
       "      <th>SBAC</th>\n",
       "      <th>SBUX</th>\n",
       "      <th>SCHW</th>\n",
       "      <th>SEDG</th>\n",
       "      <th>SEE</th>\n",
       "      <th>SHW</th>\n",
       "      <th>SJM</th>\n",
       "      <th>SLB</th>\n",
       "      <th>SNA</th>\n",
       "      <th>SNPS</th>\n",
       "      <th>SO</th>\n",
       "      <th>SPG</th>\n",
       "      <th>SPGI</th>\n",
       "      <th>SPY</th>\n",
       "      <th>SRE</th>\n",
       "      <th>STE</th>\n",
       "      <th>STLD</th>\n",
       "      <th>STT</th>\n",
       "      <th>STX</th>\n",
       "      <th>STZ</th>\n",
       "      <th>SWK</th>\n",
       "      <th>SWKS</th>\n",
       "      <th>SYF</th>\n",
       "      <th>SYK</th>\n",
       "      <th>SYY</th>\n",
       "      <th>T</th>\n",
       "      <th>TAP</th>\n",
       "      <th>TDG</th>\n",
       "      <th>TDY</th>\n",
       "      <th>TECH</th>\n",
       "      <th>TEL</th>\n",
       "      <th>TER</th>\n",
       "      <th>TFC</th>\n",
       "      <th>TFX</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TJX</th>\n",
       "      <th>TLT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TMUS</th>\n",
       "      <th>TPR</th>\n",
       "      <th>TRGP</th>\n",
       "      <th>TRMB</th>\n",
       "      <th>TROW</th>\n",
       "      <th>TRV</th>\n",
       "      <th>TSCO</th>\n",
       "      <th>TSLA</th>\n",
       "      <th>TSN</th>\n",
       "      <th>TT</th>\n",
       "      <th>TTWO</th>\n",
       "      <th>TXN</th>\n",
       "      <th>TXT</th>\n",
       "      <th>TYL</th>\n",
       "      <th>UAL</th>\n",
       "      <th>UBFUT</th>\n",
       "      <th>UDR</th>\n",
       "      <th>UHS</th>\n",
       "      <th>ULTA</th>\n",
       "      <th>UNH</th>\n",
       "      <th>UNP</th>\n",
       "      <th>UPS</th>\n",
       "      <th>URI</th>\n",
       "      <th>USB</th>\n",
       "      <th>USD</th>\n",
       "      <th>V</th>\n",
       "      <th>VFC</th>\n",
       "      <th>VICI</th>\n",
       "      <th>VLO</th>\n",
       "      <th>VMC</th>\n",
       "      <th>VNQ</th>\n",
       "      <th>VRSK</th>\n",
       "      <th>VRSN</th>\n",
       "      <th>VRTX</th>\n",
       "      <th>VTR</th>\n",
       "      <th>VTRS</th>\n",
       "      <th>VZ</th>\n",
       "      <th>WAB</th>\n",
       "      <th>WAT</th>\n",
       "      <th>WBA</th>\n",
       "      <th>WBD</th>\n",
       "      <th>WDC</th>\n",
       "      <th>WEC</th>\n",
       "      <th>WELL</th>\n",
       "      <th>WFC</th>\n",
       "      <th>WHR</th>\n",
       "      <th>WM</th>\n",
       "      <th>WMB</th>\n",
       "      <th>WMT</th>\n",
       "      <th>WRB</th>\n",
       "      <th>WRK</th>\n",
       "      <th>WST</th>\n",
       "      <th>WTW</th>\n",
       "      <th>WY</th>\n",
       "      <th>WYNN</th>\n",
       "      <th>XEL</th>\n",
       "      <th>XOM</th>\n",
       "      <th>XRAY</th>\n",
       "      <th>XTSLA</th>\n",
       "      <th>XYL</th>\n",
       "      <th>YUM</th>\n",
       "      <th>ZBH</th>\n",
       "      <th>ZBRA</th>\n",
       "      <th>ZION</th>\n",
       "      <th>ZTS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>14.570019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.046276</td>\n",
       "      <td>0.961916</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.227891</td>\n",
       "      <td>14.587082</td>\n",
       "      <td>4.233333</td>\n",
       "      <td>19.218691</td>\n",
       "      <td>30.838949</td>\n",
       "      <td>23.532494</td>\n",
       "      <td>14.488768</td>\n",
       "      <td>22.505222</td>\n",
       "      <td>37.410706</td>\n",
       "      <td>22.796192</td>\n",
       "      <td>16.537436</td>\n",
       "      <td>9.923675</td>\n",
       "      <td>13.082962</td>\n",
       "      <td>838.538147</td>\n",
       "      <td>22.099463</td>\n",
       "      <td>17.718683</td>\n",
       "      <td>12.82</td>\n",
       "      <td>14.624438</td>\n",
       "      <td>10.56</td>\n",
       "      <td>7.373944</td>\n",
       "      <td>32.724026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.487932</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.410000</td>\n",
       "      <td>9.400531</td>\n",
       "      <td>47.763378</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.694016</td>\n",
       "      <td>2.2260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.125000</td>\n",
       "      <td>18.719162</td>\n",
       "      <td>3.631645</td>\n",
       "      <td>38.153522</td>\n",
       "      <td>34.531853</td>\n",
       "      <td>4.047470</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.998272</td>\n",
       "      <td>14.246146</td>\n",
       "      <td>4.894716</td>\n",
       "      <td>38.766911</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.199196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.012657</td>\n",
       "      <td>90.750000</td>\n",
       "      <td>35.678856</td>\n",
       "      <td>31.191706</td>\n",
       "      <td>9.214674</td>\n",
       "      <td>13.622866</td>\n",
       "      <td>7.389797</td>\n",
       "      <td>25.271982</td>\n",
       "      <td>40.557240</td>\n",
       "      <td>13.490870</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.711334</td>\n",
       "      <td>66.290001</td>\n",
       "      <td>57.169998</td>\n",
       "      <td>23.237417</td>\n",
       "      <td>23.730000</td>\n",
       "      <td>21.155216</td>\n",
       "      <td>49.527332</td>\n",
       "      <td>12.840353</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.921220</td>\n",
       "      <td>34.290001</td>\n",
       "      <td>10.991192</td>\n",
       "      <td>29.572882</td>\n",
       "      <td>330.532928</td>\n",
       "      <td>12.633684</td>\n",
       "      <td>27.238813</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.583845</td>\n",
       "      <td>28.588514</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.983333</td>\n",
       "      <td>11.828124</td>\n",
       "      <td>37.857586</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.575630</td>\n",
       "      <td>18.806643</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.347277</td>\n",
       "      <td>21.702091</td>\n",
       "      <td>16.378483</td>\n",
       "      <td>35.184326</td>\n",
       "      <td>34.957329</td>\n",
       "      <td>8.150414</td>\n",
       "      <td>24.193808</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.988682</td>\n",
       "      <td>10.39</td>\n",
       "      <td>7.1675</td>\n",
       "      <td>5.238273</td>\n",
       "      <td>64.305504</td>\n",
       "      <td>69.535233</td>\n",
       "      <td>17.544312</td>\n",
       "      <td>33.524094</td>\n",
       "      <td>17.512859</td>\n",
       "      <td>3.13250</td>\n",
       "      <td>23.353689</td>\n",
       "      <td>45.349998</td>\n",
       "      <td>4.1500</td>\n",
       "      <td>13.509480</td>\n",
       "      <td>4.621</td>\n",
       "      <td>1.616585</td>\n",
       "      <td>33.357456</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.754452</td>\n",
       "      <td>9.698395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.530188</td>\n",
       "      <td>25.738766</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.386909</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.389751</td>\n",
       "      <td>25.306190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.905075</td>\n",
       "      <td>22.944559</td>\n",
       "      <td>20.028978</td>\n",
       "      <td>22.612066</td>\n",
       "      <td>24.309177</td>\n",
       "      <td>6.486145</td>\n",
       "      <td>9.513333</td>\n",
       "      <td>19.152176</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.169011</td>\n",
       "      <td>14.680956</td>\n",
       "      <td>17.421858</td>\n",
       "      <td>18.614513</td>\n",
       "      <td>19.680000</td>\n",
       "      <td>25.388985</td>\n",
       "      <td>17.008450</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.054203</td>\n",
       "      <td>22.509624</td>\n",
       "      <td>27.973494</td>\n",
       "      <td>19.604109</td>\n",
       "      <td>23.877598</td>\n",
       "      <td>17.416594</td>\n",
       "      <td>18.468307</td>\n",
       "      <td>46.880760</td>\n",
       "      <td>16.999739</td>\n",
       "      <td>20.474434</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.686282</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.025291</td>\n",
       "      <td>15.374931</td>\n",
       "      <td>13.077070</td>\n",
       "      <td>10.208722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.883560</td>\n",
       "      <td>21.637350</td>\n",
       "      <td>32.137657</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.646234</td>\n",
       "      <td>3.395833</td>\n",
       "      <td>15.562348</td>\n",
       "      <td>22.345314</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.333207</td>\n",
       "      <td>8.404287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.057049</td>\n",
       "      <td>11.682856</td>\n",
       "      <td>31.317869</td>\n",
       "      <td>83.521484</td>\n",
       "      <td>17.720682</td>\n",
       "      <td>23.525000</td>\n",
       "      <td>34.395191</td>\n",
       "      <td>14.285803</td>\n",
       "      <td>10.0050</td>\n",
       "      <td>27.535551</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.368217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.534191</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.201683</td>\n",
       "      <td>133.725769</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.972805</td>\n",
       "      <td>6.640290</td>\n",
       "      <td>13.819250</td>\n",
       "      <td>21.209904</td>\n",
       "      <td>8.309337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.048826</td>\n",
       "      <td>5.072823</td>\n",
       "      <td>24.710352</td>\n",
       "      <td>13.833051</td>\n",
       "      <td>16.532986</td>\n",
       "      <td>81.077652</td>\n",
       "      <td>47.134235</td>\n",
       "      <td>14.686513</td>\n",
       "      <td>11.542553</td>\n",
       "      <td>13.171698</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.724991</td>\n",
       "      <td>21.140642</td>\n",
       "      <td>45.961456</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.8000</td>\n",
       "      <td>22.268833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.464890</td>\n",
       "      <td>5.405458</td>\n",
       "      <td>13.345098</td>\n",
       "      <td>9.702888</td>\n",
       "      <td>35.416748</td>\n",
       "      <td>26.390881</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.066761</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.6875</td>\n",
       "      <td>20.135777</td>\n",
       "      <td>28.223948</td>\n",
       "      <td>4.635</td>\n",
       "      <td>9.64</td>\n",
       "      <td>13.662444</td>\n",
       "      <td>19.237984</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.402803</td>\n",
       "      <td>9.216443</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.020536</td>\n",
       "      <td>4.192222</td>\n",
       "      <td>12.35</td>\n",
       "      <td>30.019175</td>\n",
       "      <td>6.922497</td>\n",
       "      <td>49.943863</td>\n",
       "      <td>21.988581</td>\n",
       "      <td>18.055584</td>\n",
       "      <td>37.924900</td>\n",
       "      <td>16.566618</td>\n",
       "      <td>37.560471</td>\n",
       "      <td>21.766951</td>\n",
       "      <td>23.722313</td>\n",
       "      <td>25.440701</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.361322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.253695</td>\n",
       "      <td>24.464628</td>\n",
       "      <td>33.118881</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.10</td>\n",
       "      <td>11.964920</td>\n",
       "      <td>6.417845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.830872</td>\n",
       "      <td>48.141151</td>\n",
       "      <td>19.909084</td>\n",
       "      <td>30.702436</td>\n",
       "      <td>2.403545</td>\n",
       "      <td>31.251883</td>\n",
       "      <td>32.287735</td>\n",
       "      <td>30.620903</td>\n",
       "      <td>7.239202</td>\n",
       "      <td>21.708817</td>\n",
       "      <td>54.420456</td>\n",
       "      <td>24.285978</td>\n",
       "      <td>14.620375</td>\n",
       "      <td>32.352276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.172163</td>\n",
       "      <td>24.408182</td>\n",
       "      <td>21.488514</td>\n",
       "      <td>19.171158</td>\n",
       "      <td>7.655173</td>\n",
       "      <td>26.903273</td>\n",
       "      <td>34.440208</td>\n",
       "      <td>14.415898</td>\n",
       "      <td>34.363136</td>\n",
       "      <td>22.418354</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.846527</td>\n",
       "      <td>89.800003</td>\n",
       "      <td>13.091311</td>\n",
       "      <td>13.918072</td>\n",
       "      <td>41.747719</td>\n",
       "      <td>21.347406</td>\n",
       "      <td>49.432259</td>\n",
       "      <td>0.382708</td>\n",
       "      <td>5.024972</td>\n",
       "      <td>31.133333</td>\n",
       "      <td>12.841348</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.753834</td>\n",
       "      <td>15.251281</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.585164</td>\n",
       "      <td>32.520618</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.813698</td>\n",
       "      <td>52.469410</td>\n",
       "      <td>63.088165</td>\n",
       "      <td>6.387365</td>\n",
       "      <td>51.070000</td>\n",
       "      <td>11.854682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.826054</td>\n",
       "      <td>15.969288</td>\n",
       "      <td>5.348523</td>\n",
       "      <td>30.733908</td>\n",
       "      <td>1.702857</td>\n",
       "      <td>4.307406</td>\n",
       "      <td>9.110441</td>\n",
       "      <td>32.551903</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.176230</td>\n",
       "      <td>23.726053</td>\n",
       "      <td>25.541609</td>\n",
       "      <td>31.584089</td>\n",
       "      <td>14.407066</td>\n",
       "      <td>1.803077</td>\n",
       "      <td>741.520020</td>\n",
       "      <td>13.405938</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.561811</td>\n",
       "      <td>6.797321</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.991725</td>\n",
       "      <td>26.706465</td>\n",
       "      <td>4.44</td>\n",
       "      <td>11.115135</td>\n",
       "      <td>22.545000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.555498</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.494865</td>\n",
       "      <td>12.818127</td>\n",
       "      <td>20.382046</td>\n",
       "      <td>9.397608</td>\n",
       "      <td>12.843070</td>\n",
       "      <td>31.470049</td>\n",
       "      <td>12.258105</td>\n",
       "      <td>24.329876</td>\n",
       "      <td>33.111019</td>\n",
       "      <td>12.431433</td>\n",
       "      <td>36.384205</td>\n",
       "      <td>26.728401</td>\n",
       "      <td>12.526014</td>\n",
       "      <td>19.087852</td>\n",
       "      <td>22.031969</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.359306</td>\n",
       "      <td>20.359480</td>\n",
       "      <td>19.710556</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.383493</td>\n",
       "      <td>22.309166</td>\n",
       "      <td>10.843645</td>\n",
       "      <td>30.904421</td>\n",
       "      <td>29.704557</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.150</td>\n",
       "      <td>7.935371</td>\n",
       "      <td>26.921709</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.240692</td>\n",
       "      <td>34.249878</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.977036</td>\n",
       "      <td>61.584785</td>\n",
       "      <td>25.942730</td>\n",
       "      <td>9.04</td>\n",
       "      <td>20.556679</td>\n",
       "      <td>20.556618</td>\n",
       "      <td>10.365809</td>\n",
       "      <td>33.201870</td>\n",
       "      <td>10.832823</td>\n",
       "      <td>33.021893</td>\n",
       "      <td>1.763708</td>\n",
       "      <td>26.942366</td>\n",
       "      <td>5.779112</td>\n",
       "      <td>14.633303</td>\n",
       "      <td>21.420725</td>\n",
       "      <td>8.915441</td>\n",
       "      <td>12.214824</td>\n",
       "      <td>8.981071</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.658882</td>\n",
       "      <td>11.346319</td>\n",
       "      <td>26.552788</td>\n",
       "      <td>22.298370</td>\n",
       "      <td>22.441540</td>\n",
       "      <td>19.41</td>\n",
       "      <td>14.352347</td>\n",
       "      <td>28.634432</td>\n",
       "      <td>31.947550</td>\n",
       "      <td>84.571556</td>\n",
       "      <td>19.954111</td>\n",
       "      <td>17.260185</td>\n",
       "      <td>6.009482</td>\n",
       "      <td>34.510967</td>\n",
       "      <td>8.886695</td>\n",
       "      <td>20.949709</td>\n",
       "      <td>31.233461</td>\n",
       "      <td>7.853062</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.510036</td>\n",
       "      <td>22.062370</td>\n",
       "      <td>5.056196</td>\n",
       "      <td>25.184740</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.82</td>\n",
       "      <td>8.117376</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.433227</td>\n",
       "      <td>21.806458</td>\n",
       "      <td>39.362537</td>\n",
       "      <td>34.827820</td>\n",
       "      <td>4.909898</td>\n",
       "      <td>50.318027</td>\n",
       "      <td>28.341032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.198719</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0825</td>\n",
       "      <td>18.821436</td>\n",
       "      <td>23.950897</td>\n",
       "      <td>7.947328</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.860072</td>\n",
       "      <td>17.890514</td>\n",
       "      <td>23.585209</td>\n",
       "      <td>16.367538</td>\n",
       "      <td>32.125858</td>\n",
       "      <td>8.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.704785</td>\n",
       "      <td>20.051275</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.431389</td>\n",
       "      <td>11.748457</td>\n",
       "      <td>50.628342</td>\n",
       "      <td>18.938057</td>\n",
       "      <td>17.829287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.837399</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.970934</td>\n",
       "      <td>41.826443</td>\n",
       "      <td>25.454876</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.648361</td>\n",
       "      <td>10.24</td>\n",
       "      <td>13.074273</td>\n",
       "      <td>15.825217</td>\n",
       "      <td>14.901470</td>\n",
       "      <td>9.799141</td>\n",
       "      <td>45.770000</td>\n",
       "      <td>26.787544</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.622047</td>\n",
       "      <td>9.738559</td>\n",
       "      <td>14.221395</td>\n",
       "      <td>18.636450</td>\n",
       "      <td>42.231106</td>\n",
       "      <td>17.647091</td>\n",
       "      <td>5.912993</td>\n",
       "      <td>36.303005</td>\n",
       "      <td>6.872738</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.520180</td>\n",
       "      <td>71.333054</td>\n",
       "      <td>13.131151</td>\n",
       "      <td>36.172791</td>\n",
       "      <td>9.113141</td>\n",
       "      <td>27.368698</td>\n",
       "      <td>24.653870</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.032602</td>\n",
       "      <td>70.087204</td>\n",
       "      <td>55.509998</td>\n",
       "      <td>50.133705</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>14.185627</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.872833</td>\n",
       "      <td>0.971795</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.139072</td>\n",
       "      <td>14.440167</td>\n",
       "      <td>4.177778</td>\n",
       "      <td>18.766836</td>\n",
       "      <td>30.024111</td>\n",
       "      <td>22.892282</td>\n",
       "      <td>14.330419</td>\n",
       "      <td>22.145958</td>\n",
       "      <td>34.981960</td>\n",
       "      <td>22.615526</td>\n",
       "      <td>16.474241</td>\n",
       "      <td>9.557489</td>\n",
       "      <td>13.069791</td>\n",
       "      <td>841.332275</td>\n",
       "      <td>21.667545</td>\n",
       "      <td>17.339153</td>\n",
       "      <td>12.20</td>\n",
       "      <td>14.028703</td>\n",
       "      <td>10.41</td>\n",
       "      <td>7.027728</td>\n",
       "      <td>32.615421</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.250350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.209999</td>\n",
       "      <td>9.157941</td>\n",
       "      <td>47.005459</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.499825</td>\n",
       "      <td>2.1070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.200001</td>\n",
       "      <td>18.544516</td>\n",
       "      <td>3.549895</td>\n",
       "      <td>37.845306</td>\n",
       "      <td>33.871559</td>\n",
       "      <td>3.920744</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.341019</td>\n",
       "      <td>14.283621</td>\n",
       "      <td>4.767549</td>\n",
       "      <td>38.334450</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.683674</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.456577</td>\n",
       "      <td>89.699997</td>\n",
       "      <td>34.985836</td>\n",
       "      <td>30.762041</td>\n",
       "      <td>9.214674</td>\n",
       "      <td>13.595317</td>\n",
       "      <td>7.327534</td>\n",
       "      <td>24.598400</td>\n",
       "      <td>40.086586</td>\n",
       "      <td>13.401621</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.561394</td>\n",
       "      <td>64.760002</td>\n",
       "      <td>57.250000</td>\n",
       "      <td>22.879486</td>\n",
       "      <td>23.879999</td>\n",
       "      <td>21.211494</td>\n",
       "      <td>49.376968</td>\n",
       "      <td>12.698978</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.933382</td>\n",
       "      <td>34.169998</td>\n",
       "      <td>10.775844</td>\n",
       "      <td>29.066462</td>\n",
       "      <td>327.725525</td>\n",
       "      <td>12.590466</td>\n",
       "      <td>26.467089</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.257095</td>\n",
       "      <td>28.514214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.920000</td>\n",
       "      <td>11.640720</td>\n",
       "      <td>37.685833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.492244</td>\n",
       "      <td>18.724434</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.163507</td>\n",
       "      <td>21.374987</td>\n",
       "      <td>16.263884</td>\n",
       "      <td>34.816578</td>\n",
       "      <td>34.725941</td>\n",
       "      <td>7.942125</td>\n",
       "      <td>23.815201</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.660637</td>\n",
       "      <td>10.25</td>\n",
       "      <td>7.0750</td>\n",
       "      <td>5.186175</td>\n",
       "      <td>63.116085</td>\n",
       "      <td>70.107460</td>\n",
       "      <td>17.429592</td>\n",
       "      <td>32.922184</td>\n",
       "      <td>17.618959</td>\n",
       "      <td>3.01750</td>\n",
       "      <td>22.865421</td>\n",
       "      <td>44.360001</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>12.978050</td>\n",
       "      <td>4.455</td>\n",
       "      <td>1.581671</td>\n",
       "      <td>32.885998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.713370</td>\n",
       "      <td>9.589423</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.342857</td>\n",
       "      <td>25.561773</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.311630</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.516006</td>\n",
       "      <td>24.702505</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.503311</td>\n",
       "      <td>21.929991</td>\n",
       "      <td>19.822390</td>\n",
       "      <td>22.368484</td>\n",
       "      <td>23.721647</td>\n",
       "      <td>6.514782</td>\n",
       "      <td>9.210000</td>\n",
       "      <td>19.063807</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.201631</td>\n",
       "      <td>14.643202</td>\n",
       "      <td>17.417782</td>\n",
       "      <td>18.428743</td>\n",
       "      <td>19.754999</td>\n",
       "      <td>25.327568</td>\n",
       "      <td>16.696306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.337811</td>\n",
       "      <td>21.957289</td>\n",
       "      <td>27.617764</td>\n",
       "      <td>19.545254</td>\n",
       "      <td>23.044474</td>\n",
       "      <td>17.372721</td>\n",
       "      <td>18.095615</td>\n",
       "      <td>46.255676</td>\n",
       "      <td>15.483706</td>\n",
       "      <td>20.236012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.486128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.371868</td>\n",
       "      <td>15.279517</td>\n",
       "      <td>12.973197</td>\n",
       "      <td>10.109393</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.934589</td>\n",
       "      <td>21.053307</td>\n",
       "      <td>31.891003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.561290</td>\n",
       "      <td>3.323333</td>\n",
       "      <td>15.457955</td>\n",
       "      <td>21.974518</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.395154</td>\n",
       "      <td>8.375719</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.915650</td>\n",
       "      <td>11.221319</td>\n",
       "      <td>30.680763</td>\n",
       "      <td>82.029404</td>\n",
       "      <td>17.662132</td>\n",
       "      <td>22.360001</td>\n",
       "      <td>32.975437</td>\n",
       "      <td>14.168241</td>\n",
       "      <td>9.8775</td>\n",
       "      <td>27.338661</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.996173</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.151833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.313274</td>\n",
       "      <td>132.117661</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.672102</td>\n",
       "      <td>6.477772</td>\n",
       "      <td>13.776856</td>\n",
       "      <td>20.996979</td>\n",
       "      <td>8.181615</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.844342</td>\n",
       "      <td>4.867367</td>\n",
       "      <td>24.483755</td>\n",
       "      <td>13.586203</td>\n",
       "      <td>15.890412</td>\n",
       "      <td>80.552307</td>\n",
       "      <td>46.337791</td>\n",
       "      <td>14.701956</td>\n",
       "      <td>11.512338</td>\n",
       "      <td>13.091542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.371185</td>\n",
       "      <td>21.180607</td>\n",
       "      <td>45.453743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.4475</td>\n",
       "      <td>21.871405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.421894</td>\n",
       "      <td>5.396626</td>\n",
       "      <td>13.392157</td>\n",
       "      <td>9.617270</td>\n",
       "      <td>35.794624</td>\n",
       "      <td>26.336590</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.475281</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.6750</td>\n",
       "      <td>19.752287</td>\n",
       "      <td>27.419472</td>\n",
       "      <td>4.490</td>\n",
       "      <td>9.27</td>\n",
       "      <td>13.390020</td>\n",
       "      <td>18.605686</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.912273</td>\n",
       "      <td>9.051983</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.791840</td>\n",
       "      <td>4.045556</td>\n",
       "      <td>12.15</td>\n",
       "      <td>29.830254</td>\n",
       "      <td>6.755689</td>\n",
       "      <td>48.873230</td>\n",
       "      <td>21.993324</td>\n",
       "      <td>17.633781</td>\n",
       "      <td>38.149635</td>\n",
       "      <td>16.011229</td>\n",
       "      <td>37.441044</td>\n",
       "      <td>20.939121</td>\n",
       "      <td>23.477819</td>\n",
       "      <td>25.348946</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.280260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.108776</td>\n",
       "      <td>23.670748</td>\n",
       "      <td>33.134277</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.99</td>\n",
       "      <td>11.797857</td>\n",
       "      <td>6.245707</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.727570</td>\n",
       "      <td>47.933559</td>\n",
       "      <td>19.028351</td>\n",
       "      <td>30.262651</td>\n",
       "      <td>2.306432</td>\n",
       "      <td>30.835188</td>\n",
       "      <td>31.739779</td>\n",
       "      <td>30.747080</td>\n",
       "      <td>7.208285</td>\n",
       "      <td>21.255625</td>\n",
       "      <td>54.115005</td>\n",
       "      <td>23.412069</td>\n",
       "      <td>14.201869</td>\n",
       "      <td>32.985851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.101778</td>\n",
       "      <td>24.033506</td>\n",
       "      <td>21.030190</td>\n",
       "      <td>19.327810</td>\n",
       "      <td>7.522676</td>\n",
       "      <td>26.556921</td>\n",
       "      <td>33.920910</td>\n",
       "      <td>14.358037</td>\n",
       "      <td>34.203232</td>\n",
       "      <td>22.278793</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.586792</td>\n",
       "      <td>88.750000</td>\n",
       "      <td>13.098211</td>\n",
       "      <td>13.577760</td>\n",
       "      <td>40.775730</td>\n",
       "      <td>21.412285</td>\n",
       "      <td>49.030331</td>\n",
       "      <td>0.366771</td>\n",
       "      <td>5.059783</td>\n",
       "      <td>32.073334</td>\n",
       "      <td>12.135864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.561518</td>\n",
       "      <td>15.187861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.500154</td>\n",
       "      <td>32.171562</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.884050</td>\n",
       "      <td>51.423702</td>\n",
       "      <td>62.814056</td>\n",
       "      <td>6.262747</td>\n",
       "      <td>50.360001</td>\n",
       "      <td>11.518800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.742525</td>\n",
       "      <td>15.638940</td>\n",
       "      <td>5.283382</td>\n",
       "      <td>30.160732</td>\n",
       "      <td>1.665714</td>\n",
       "      <td>4.240012</td>\n",
       "      <td>8.980848</td>\n",
       "      <td>31.854155</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.895983</td>\n",
       "      <td>23.532398</td>\n",
       "      <td>24.526192</td>\n",
       "      <td>31.311054</td>\n",
       "      <td>14.312835</td>\n",
       "      <td>1.718199</td>\n",
       "      <td>720.059998</td>\n",
       "      <td>13.193852</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.473913</td>\n",
       "      <td>6.749098</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.907541</td>\n",
       "      <td>26.690693</td>\n",
       "      <td>4.13</td>\n",
       "      <td>10.825035</td>\n",
       "      <td>22.469999</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.371071</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.123861</td>\n",
       "      <td>12.395357</td>\n",
       "      <td>20.227732</td>\n",
       "      <td>9.267516</td>\n",
       "      <td>12.734679</td>\n",
       "      <td>31.245876</td>\n",
       "      <td>12.258105</td>\n",
       "      <td>24.305882</td>\n",
       "      <td>32.697063</td>\n",
       "      <td>12.309317</td>\n",
       "      <td>35.619297</td>\n",
       "      <td>25.718105</td>\n",
       "      <td>12.316170</td>\n",
       "      <td>18.854544</td>\n",
       "      <td>22.021091</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.116352</td>\n",
       "      <td>19.909670</td>\n",
       "      <td>19.683758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.766096</td>\n",
       "      <td>21.804932</td>\n",
       "      <td>10.723003</td>\n",
       "      <td>30.680635</td>\n",
       "      <td>29.328547</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.675</td>\n",
       "      <td>7.580937</td>\n",
       "      <td>26.748169</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.113909</td>\n",
       "      <td>33.625580</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.548450</td>\n",
       "      <td>61.007389</td>\n",
       "      <td>25.519398</td>\n",
       "      <td>8.35</td>\n",
       "      <td>20.486700</td>\n",
       "      <td>20.650234</td>\n",
       "      <td>10.209682</td>\n",
       "      <td>32.836491</td>\n",
       "      <td>10.773129</td>\n",
       "      <td>32.513870</td>\n",
       "      <td>1.730495</td>\n",
       "      <td>26.525158</td>\n",
       "      <td>5.802044</td>\n",
       "      <td>14.584842</td>\n",
       "      <td>21.173248</td>\n",
       "      <td>8.857168</td>\n",
       "      <td>12.206831</td>\n",
       "      <td>8.773108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.014561</td>\n",
       "      <td>11.212584</td>\n",
       "      <td>26.303331</td>\n",
       "      <td>22.128309</td>\n",
       "      <td>21.976465</td>\n",
       "      <td>18.58</td>\n",
       "      <td>14.343664</td>\n",
       "      <td>28.320997</td>\n",
       "      <td>31.936888</td>\n",
       "      <td>83.538139</td>\n",
       "      <td>19.904638</td>\n",
       "      <td>16.880116</td>\n",
       "      <td>6.022762</td>\n",
       "      <td>34.369270</td>\n",
       "      <td>8.723166</td>\n",
       "      <td>20.742283</td>\n",
       "      <td>30.718668</td>\n",
       "      <td>7.695831</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.034088</td>\n",
       "      <td>21.701178</td>\n",
       "      <td>5.002849</td>\n",
       "      <td>24.676846</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.18</td>\n",
       "      <td>7.966858</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.501834</td>\n",
       "      <td>21.843039</td>\n",
       "      <td>39.044098</td>\n",
       "      <td>34.451302</td>\n",
       "      <td>4.892115</td>\n",
       "      <td>49.790707</td>\n",
       "      <td>27.987720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.763174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0300</td>\n",
       "      <td>18.296421</td>\n",
       "      <td>23.815866</td>\n",
       "      <td>7.773532</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.867762</td>\n",
       "      <td>17.532124</td>\n",
       "      <td>22.598604</td>\n",
       "      <td>15.974930</td>\n",
       "      <td>31.450640</td>\n",
       "      <td>8.02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.512852</td>\n",
       "      <td>19.923693</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.067337</td>\n",
       "      <td>11.462759</td>\n",
       "      <td>49.985039</td>\n",
       "      <td>18.539360</td>\n",
       "      <td>17.743153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.771186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.973716</td>\n",
       "      <td>41.354881</td>\n",
       "      <td>25.072300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.722784</td>\n",
       "      <td>10.09</td>\n",
       "      <td>12.915008</td>\n",
       "      <td>15.491773</td>\n",
       "      <td>14.750576</td>\n",
       "      <td>9.493651</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>26.595150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.405293</td>\n",
       "      <td>9.732780</td>\n",
       "      <td>14.141001</td>\n",
       "      <td>18.651503</td>\n",
       "      <td>41.503296</td>\n",
       "      <td>17.449883</td>\n",
       "      <td>5.863492</td>\n",
       "      <td>36.214546</td>\n",
       "      <td>6.853625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.603344</td>\n",
       "      <td>71.833092</td>\n",
       "      <td>12.929282</td>\n",
       "      <td>36.095535</td>\n",
       "      <td>8.976597</td>\n",
       "      <td>27.182922</td>\n",
       "      <td>24.454481</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.873264</td>\n",
       "      <td>70.060738</td>\n",
       "      <td>54.470001</td>\n",
       "      <td>49.449276</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>14.179530</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.920677</td>\n",
       "      <td>0.980306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.117834</td>\n",
       "      <td>14.274515</td>\n",
       "      <td>4.153333</td>\n",
       "      <td>18.693958</td>\n",
       "      <td>29.859142</td>\n",
       "      <td>22.995754</td>\n",
       "      <td>14.086306</td>\n",
       "      <td>22.053587</td>\n",
       "      <td>35.251820</td>\n",
       "      <td>22.411699</td>\n",
       "      <td>16.279799</td>\n",
       "      <td>9.535515</td>\n",
       "      <td>12.974243</td>\n",
       "      <td>855.301697</td>\n",
       "      <td>21.487579</td>\n",
       "      <td>17.246973</td>\n",
       "      <td>12.00</td>\n",
       "      <td>13.690475</td>\n",
       "      <td>10.40</td>\n",
       "      <td>6.868109</td>\n",
       "      <td>32.359879</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.042464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.750000</td>\n",
       "      <td>8.986540</td>\n",
       "      <td>46.262405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.370360</td>\n",
       "      <td>2.0885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.200001</td>\n",
       "      <td>18.044378</td>\n",
       "      <td>3.433465</td>\n",
       "      <td>37.718884</td>\n",
       "      <td>33.901283</td>\n",
       "      <td>3.829588</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.425335</td>\n",
       "      <td>14.187250</td>\n",
       "      <td>4.837366</td>\n",
       "      <td>36.484661</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.231007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.118221</td>\n",
       "      <td>90.290001</td>\n",
       "      <td>35.566833</td>\n",
       "      <td>30.406223</td>\n",
       "      <td>8.995887</td>\n",
       "      <td>13.740910</td>\n",
       "      <td>7.412738</td>\n",
       "      <td>24.747618</td>\n",
       "      <td>39.862122</td>\n",
       "      <td>13.209533</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.592648</td>\n",
       "      <td>64.839996</td>\n",
       "      <td>56.090000</td>\n",
       "      <td>22.914581</td>\n",
       "      <td>23.590000</td>\n",
       "      <td>21.139870</td>\n",
       "      <td>48.919491</td>\n",
       "      <td>12.658124</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.943520</td>\n",
       "      <td>34.700001</td>\n",
       "      <td>10.601909</td>\n",
       "      <td>27.923500</td>\n",
       "      <td>331.833954</td>\n",
       "      <td>12.465124</td>\n",
       "      <td>26.405163</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.696976</td>\n",
       "      <td>28.493952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.606667</td>\n",
       "      <td>11.929033</td>\n",
       "      <td>37.619759</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.514084</td>\n",
       "      <td>18.892260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.005085</td>\n",
       "      <td>21.775337</td>\n",
       "      <td>15.897146</td>\n",
       "      <td>34.641731</td>\n",
       "      <td>34.361496</td>\n",
       "      <td>8.016515</td>\n",
       "      <td>24.148285</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.065740</td>\n",
       "      <td>10.11</td>\n",
       "      <td>6.9600</td>\n",
       "      <td>5.091452</td>\n",
       "      <td>62.486805</td>\n",
       "      <td>71.538033</td>\n",
       "      <td>17.558920</td>\n",
       "      <td>33.048187</td>\n",
       "      <td>17.483387</td>\n",
       "      <td>2.95250</td>\n",
       "      <td>22.086973</td>\n",
       "      <td>44.060001</td>\n",
       "      <td>4.4875</td>\n",
       "      <td>12.985047</td>\n",
       "      <td>4.408</td>\n",
       "      <td>1.575582</td>\n",
       "      <td>32.800991</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.679989</td>\n",
       "      <td>9.501321</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.622034</td>\n",
       "      <td>25.728666</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.197496</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.115845</td>\n",
       "      <td>24.463116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.018166</td>\n",
       "      <td>21.457687</td>\n",
       "      <td>19.722664</td>\n",
       "      <td>22.246700</td>\n",
       "      <td>23.714304</td>\n",
       "      <td>6.300009</td>\n",
       "      <td>9.433333</td>\n",
       "      <td>18.691744</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.117752</td>\n",
       "      <td>14.222514</td>\n",
       "      <td>17.315926</td>\n",
       "      <td>18.287554</td>\n",
       "      <td>19.650000</td>\n",
       "      <td>24.979494</td>\n",
       "      <td>16.622866</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.900074</td>\n",
       "      <td>21.876413</td>\n",
       "      <td>27.350975</td>\n",
       "      <td>19.332460</td>\n",
       "      <td>23.186098</td>\n",
       "      <td>17.093054</td>\n",
       "      <td>17.751286</td>\n",
       "      <td>48.014233</td>\n",
       "      <td>15.311636</td>\n",
       "      <td>20.054216</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.381278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.679081</td>\n",
       "      <td>14.789430</td>\n",
       "      <td>12.922363</td>\n",
       "      <td>10.015586</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.345757</td>\n",
       "      <td>20.746069</td>\n",
       "      <td>31.378338</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.476348</td>\n",
       "      <td>3.289167</td>\n",
       "      <td>15.227561</td>\n",
       "      <td>22.667208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.195008</td>\n",
       "      <td>8.244312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.920641</td>\n",
       "      <td>11.092586</td>\n",
       "      <td>30.098555</td>\n",
       "      <td>81.926529</td>\n",
       "      <td>17.518028</td>\n",
       "      <td>22.240000</td>\n",
       "      <td>33.024048</td>\n",
       "      <td>14.107431</td>\n",
       "      <td>9.9275</td>\n",
       "      <td>26.898567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.828671</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.171732</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.279758</td>\n",
       "      <td>131.313644</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.531260</td>\n",
       "      <td>6.387909</td>\n",
       "      <td>14.059457</td>\n",
       "      <td>20.993256</td>\n",
       "      <td>8.089364</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.819685</td>\n",
       "      <td>4.842593</td>\n",
       "      <td>24.211830</td>\n",
       "      <td>13.437614</td>\n",
       "      <td>15.028969</td>\n",
       "      <td>80.189240</td>\n",
       "      <td>45.657215</td>\n",
       "      <td>14.516546</td>\n",
       "      <td>11.421691</td>\n",
       "      <td>13.006044</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.120317</td>\n",
       "      <td>21.047400</td>\n",
       "      <td>45.260010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.4150</td>\n",
       "      <td>21.808319</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.449535</td>\n",
       "      <td>5.345400</td>\n",
       "      <td>13.378431</td>\n",
       "      <td>9.286231</td>\n",
       "      <td>34.928101</td>\n",
       "      <td>26.879606</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.362602</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.7325</td>\n",
       "      <td>19.327890</td>\n",
       "      <td>27.385958</td>\n",
       "      <td>4.250</td>\n",
       "      <td>9.25</td>\n",
       "      <td>13.259729</td>\n",
       "      <td>18.394922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.198814</td>\n",
       "      <td>9.038277</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.888701</td>\n",
       "      <td>4.010000</td>\n",
       "      <td>12.00</td>\n",
       "      <td>30.006142</td>\n",
       "      <td>6.811288</td>\n",
       "      <td>47.896420</td>\n",
       "      <td>21.609306</td>\n",
       "      <td>17.232445</td>\n",
       "      <td>37.978432</td>\n",
       "      <td>16.098507</td>\n",
       "      <td>37.417141</td>\n",
       "      <td>20.809265</td>\n",
       "      <td>23.526722</td>\n",
       "      <td>25.503790</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.152893</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.593056</td>\n",
       "      <td>23.287289</td>\n",
       "      <td>32.564751</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.93</td>\n",
       "      <td>11.743137</td>\n",
       "      <td>6.193316</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.318367</td>\n",
       "      <td>47.330563</td>\n",
       "      <td>18.823072</td>\n",
       "      <td>29.648317</td>\n",
       "      <td>2.203249</td>\n",
       "      <td>31.157431</td>\n",
       "      <td>32.537891</td>\n",
       "      <td>30.680674</td>\n",
       "      <td>7.164487</td>\n",
       "      <td>21.075834</td>\n",
       "      <td>54.158638</td>\n",
       "      <td>22.616806</td>\n",
       "      <td>14.201869</td>\n",
       "      <td>32.579025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.393261</td>\n",
       "      <td>24.049122</td>\n",
       "      <td>20.728994</td>\n",
       "      <td>19.177185</td>\n",
       "      <td>7.293025</td>\n",
       "      <td>26.548262</td>\n",
       "      <td>33.774841</td>\n",
       "      <td>14.242314</td>\n",
       "      <td>33.949024</td>\n",
       "      <td>22.133659</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.191288</td>\n",
       "      <td>87.800003</td>\n",
       "      <td>12.932717</td>\n",
       "      <td>13.612659</td>\n",
       "      <td>40.759804</td>\n",
       "      <td>21.217636</td>\n",
       "      <td>48.430428</td>\n",
       "      <td>0.349063</td>\n",
       "      <td>5.050664</td>\n",
       "      <td>31.866667</td>\n",
       "      <td>11.850501</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.255560</td>\n",
       "      <td>15.290312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.408915</td>\n",
       "      <td>31.985392</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.841835</td>\n",
       "      <td>50.808582</td>\n",
       "      <td>62.718746</td>\n",
       "      <td>6.213876</td>\n",
       "      <td>50.369999</td>\n",
       "      <td>11.390375</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.714682</td>\n",
       "      <td>15.481833</td>\n",
       "      <td>5.215351</td>\n",
       "      <td>30.233274</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>4.214981</td>\n",
       "      <td>8.873362</td>\n",
       "      <td>32.339546</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.723836</td>\n",
       "      <td>23.966444</td>\n",
       "      <td>24.565256</td>\n",
       "      <td>31.191202</td>\n",
       "      <td>14.187177</td>\n",
       "      <td>1.734257</td>\n",
       "      <td>712.500000</td>\n",
       "      <td>12.920380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.992375</td>\n",
       "      <td>6.359468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.873512</td>\n",
       "      <td>26.564419</td>\n",
       "      <td>4.00</td>\n",
       "      <td>10.858188</td>\n",
       "      <td>22.445000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.280312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.996504</td>\n",
       "      <td>11.995350</td>\n",
       "      <td>19.980825</td>\n",
       "      <td>8.952547</td>\n",
       "      <td>12.565788</td>\n",
       "      <td>31.282230</td>\n",
       "      <td>12.174685</td>\n",
       "      <td>24.029955</td>\n",
       "      <td>33.039021</td>\n",
       "      <td>12.317836</td>\n",
       "      <td>34.985943</td>\n",
       "      <td>25.506752</td>\n",
       "      <td>12.170894</td>\n",
       "      <td>18.292896</td>\n",
       "      <td>21.118057</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.812668</td>\n",
       "      <td>19.317825</td>\n",
       "      <td>19.246048</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.851435</td>\n",
       "      <td>21.496416</td>\n",
       "      <td>10.569640</td>\n",
       "      <td>30.376537</td>\n",
       "      <td>28.281084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.375</td>\n",
       "      <td>7.679392</td>\n",
       "      <td>26.148687</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.234013</td>\n",
       "      <td>33.417480</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.945274</td>\n",
       "      <td>60.235222</td>\n",
       "      <td>24.415863</td>\n",
       "      <td>8.41</td>\n",
       "      <td>20.364241</td>\n",
       "      <td>20.225422</td>\n",
       "      <td>9.975478</td>\n",
       "      <td>32.479065</td>\n",
       "      <td>10.788052</td>\n",
       "      <td>31.829721</td>\n",
       "      <td>1.735917</td>\n",
       "      <td>26.552094</td>\n",
       "      <td>5.752009</td>\n",
       "      <td>14.474725</td>\n",
       "      <td>21.015192</td>\n",
       "      <td>8.624084</td>\n",
       "      <td>12.306726</td>\n",
       "      <td>8.719192</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.531321</td>\n",
       "      <td>11.053143</td>\n",
       "      <td>26.382719</td>\n",
       "      <td>22.197718</td>\n",
       "      <td>21.747198</td>\n",
       "      <td>18.07</td>\n",
       "      <td>14.256837</td>\n",
       "      <td>27.067263</td>\n",
       "      <td>32.000744</td>\n",
       "      <td>82.961700</td>\n",
       "      <td>19.651783</td>\n",
       "      <td>16.768324</td>\n",
       "      <td>5.972961</td>\n",
       "      <td>34.142551</td>\n",
       "      <td>8.636292</td>\n",
       "      <td>20.160595</td>\n",
       "      <td>30.627438</td>\n",
       "      <td>7.678362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.083237</td>\n",
       "      <td>21.730902</td>\n",
       "      <td>5.026556</td>\n",
       "      <td>24.062000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.40</td>\n",
       "      <td>7.956261</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.306239</td>\n",
       "      <td>21.973679</td>\n",
       "      <td>39.020802</td>\n",
       "      <td>34.478207</td>\n",
       "      <td>4.872356</td>\n",
       "      <td>50.057182</td>\n",
       "      <td>27.911337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.780600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9625</td>\n",
       "      <td>18.220104</td>\n",
       "      <td>23.777287</td>\n",
       "      <td>7.644797</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.713851</td>\n",
       "      <td>17.137417</td>\n",
       "      <td>22.398617</td>\n",
       "      <td>15.494335</td>\n",
       "      <td>31.539484</td>\n",
       "      <td>7.86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.159514</td>\n",
       "      <td>20.051275</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.190060</td>\n",
       "      <td>11.358233</td>\n",
       "      <td>49.883789</td>\n",
       "      <td>18.160599</td>\n",
       "      <td>17.835035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.666106</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.720732</td>\n",
       "      <td>41.213417</td>\n",
       "      <td>24.238836</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.017990</td>\n",
       "      <td>9.90</td>\n",
       "      <td>12.451685</td>\n",
       "      <td>15.347581</td>\n",
       "      <td>14.728499</td>\n",
       "      <td>9.277457</td>\n",
       "      <td>45.330002</td>\n",
       "      <td>27.278444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.212622</td>\n",
       "      <td>9.663447</td>\n",
       "      <td>13.524678</td>\n",
       "      <td>18.672573</td>\n",
       "      <td>41.539989</td>\n",
       "      <td>17.306461</td>\n",
       "      <td>5.821611</td>\n",
       "      <td>36.262173</td>\n",
       "      <td>6.837454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.603344</td>\n",
       "      <td>70.695076</td>\n",
       "      <td>12.984164</td>\n",
       "      <td>36.503883</td>\n",
       "      <td>8.875449</td>\n",
       "      <td>27.040861</td>\n",
       "      <td>24.166471</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.844993</td>\n",
       "      <td>69.513336</td>\n",
       "      <td>52.570000</td>\n",
       "      <td>49.270733</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>13.868362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.896755</td>\n",
       "      <td>0.981066</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.212444</td>\n",
       "      <td>14.596454</td>\n",
       "      <td>4.147778</td>\n",
       "      <td>18.526327</td>\n",
       "      <td>29.364239</td>\n",
       "      <td>22.956947</td>\n",
       "      <td>14.376613</td>\n",
       "      <td>21.904751</td>\n",
       "      <td>35.081905</td>\n",
       "      <td>22.638691</td>\n",
       "      <td>16.284664</td>\n",
       "      <td>9.542842</td>\n",
       "      <td>13.175208</td>\n",
       "      <td>856.698364</td>\n",
       "      <td>22.027481</td>\n",
       "      <td>17.317465</td>\n",
       "      <td>11.94</td>\n",
       "      <td>13.955678</td>\n",
       "      <td>10.24</td>\n",
       "      <td>6.721979</td>\n",
       "      <td>32.640987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.953376</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.719999</td>\n",
       "      <td>9.063015</td>\n",
       "      <td>46.693371</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.499825</td>\n",
       "      <td>2.0525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.720000</td>\n",
       "      <td>18.504820</td>\n",
       "      <td>3.479293</td>\n",
       "      <td>38.327381</td>\n",
       "      <td>34.109489</td>\n",
       "      <td>3.774006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.200638</td>\n",
       "      <td>14.155130</td>\n",
       "      <td>4.770042</td>\n",
       "      <td>37.073463</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.664803</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.932453</td>\n",
       "      <td>89.550003</td>\n",
       "      <td>35.335846</td>\n",
       "      <td>30.359207</td>\n",
       "      <td>9.068109</td>\n",
       "      <td>13.796006</td>\n",
       "      <td>7.314425</td>\n",
       "      <td>23.660511</td>\n",
       "      <td>39.869335</td>\n",
       "      <td>13.258038</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.669315</td>\n",
       "      <td>65.190002</td>\n",
       "      <td>56.619999</td>\n",
       "      <td>23.370768</td>\n",
       "      <td>24.180000</td>\n",
       "      <td>21.416147</td>\n",
       "      <td>52.285336</td>\n",
       "      <td>12.637704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.929327</td>\n",
       "      <td>35.189999</td>\n",
       "      <td>10.684731</td>\n",
       "      <td>28.434568</td>\n",
       "      <td>335.052429</td>\n",
       "      <td>12.560208</td>\n",
       "      <td>26.843426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.120186</td>\n",
       "      <td>28.811386</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.723333</td>\n",
       "      <td>12.001110</td>\n",
       "      <td>37.890591</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.581585</td>\n",
       "      <td>18.888836</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.017750</td>\n",
       "      <td>21.931572</td>\n",
       "      <td>16.283533</td>\n",
       "      <td>34.949203</td>\n",
       "      <td>34.407761</td>\n",
       "      <td>8.004113</td>\n",
       "      <td>24.592386</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.006247</td>\n",
       "      <td>10.10</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>5.096189</td>\n",
       "      <td>63.269512</td>\n",
       "      <td>71.380180</td>\n",
       "      <td>17.813387</td>\n",
       "      <td>33.524094</td>\n",
       "      <td>17.483387</td>\n",
       "      <td>2.94625</td>\n",
       "      <td>22.123817</td>\n",
       "      <td>44.860001</td>\n",
       "      <td>4.4300</td>\n",
       "      <td>13.180835</td>\n",
       "      <td>4.401</td>\n",
       "      <td>1.594662</td>\n",
       "      <td>33.117863</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.717862</td>\n",
       "      <td>9.387712</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.625700</td>\n",
       "      <td>26.158476</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.284916</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.564995</td>\n",
       "      <td>24.803118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.919628</td>\n",
       "      <td>21.889170</td>\n",
       "      <td>19.733343</td>\n",
       "      <td>22.279171</td>\n",
       "      <td>23.802431</td>\n",
       "      <td>6.390692</td>\n",
       "      <td>9.366667</td>\n",
       "      <td>18.515005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.038529</td>\n",
       "      <td>14.761853</td>\n",
       "      <td>17.389265</td>\n",
       "      <td>18.287554</td>\n",
       "      <td>19.629999</td>\n",
       "      <td>25.327568</td>\n",
       "      <td>16.503523</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.617714</td>\n",
       "      <td>20.945335</td>\n",
       "      <td>27.431816</td>\n",
       "      <td>19.355097</td>\n",
       "      <td>22.994476</td>\n",
       "      <td>17.098537</td>\n",
       "      <td>17.986240</td>\n",
       "      <td>48.089252</td>\n",
       "      <td>15.632049</td>\n",
       "      <td>20.185349</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.564280</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.954617</td>\n",
       "      <td>14.789430</td>\n",
       "      <td>13.147793</td>\n",
       "      <td>9.999030</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.134270</td>\n",
       "      <td>20.806906</td>\n",
       "      <td>31.407349</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.509382</td>\n",
       "      <td>3.335833</td>\n",
       "      <td>15.285158</td>\n",
       "      <td>22.781298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.409452</td>\n",
       "      <td>8.255739</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.007973</td>\n",
       "      <td>11.076889</td>\n",
       "      <td>30.213898</td>\n",
       "      <td>81.626358</td>\n",
       "      <td>17.522533</td>\n",
       "      <td>21.145000</td>\n",
       "      <td>32.849007</td>\n",
       "      <td>14.204720</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>26.788532</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.957385</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.360218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.340092</td>\n",
       "      <td>132.373520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.823269</td>\n",
       "      <td>6.428060</td>\n",
       "      <td>14.161835</td>\n",
       "      <td>21.067955</td>\n",
       "      <td>8.330626</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.696148</td>\n",
       "      <td>4.718468</td>\n",
       "      <td>24.268486</td>\n",
       "      <td>13.564634</td>\n",
       "      <td>14.967240</td>\n",
       "      <td>81.293968</td>\n",
       "      <td>45.280701</td>\n",
       "      <td>14.775355</td>\n",
       "      <td>11.433777</td>\n",
       "      <td>13.027424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.715057</td>\n",
       "      <td>21.319147</td>\n",
       "      <td>45.440350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.4025</td>\n",
       "      <td>21.663219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.437251</td>\n",
       "      <td>5.366596</td>\n",
       "      <td>13.425490</td>\n",
       "      <td>9.388970</td>\n",
       "      <td>34.862938</td>\n",
       "      <td>26.825306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.193569</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.7125</td>\n",
       "      <td>19.379032</td>\n",
       "      <td>27.540148</td>\n",
       "      <td>4.295</td>\n",
       "      <td>9.30</td>\n",
       "      <td>13.301186</td>\n",
       "      <td>18.278332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.101692</td>\n",
       "      <td>9.065690</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.910225</td>\n",
       "      <td>4.090000</td>\n",
       "      <td>12.05</td>\n",
       "      <td>29.683674</td>\n",
       "      <td>6.855774</td>\n",
       "      <td>48.150394</td>\n",
       "      <td>21.618790</td>\n",
       "      <td>17.465878</td>\n",
       "      <td>38.920128</td>\n",
       "      <td>16.693565</td>\n",
       "      <td>37.524628</td>\n",
       "      <td>20.435934</td>\n",
       "      <td>23.661194</td>\n",
       "      <td>25.538204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.979187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.808299</td>\n",
       "      <td>22.849848</td>\n",
       "      <td>33.093239</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.83</td>\n",
       "      <td>11.841063</td>\n",
       "      <td>6.144665</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.809425</td>\n",
       "      <td>47.617229</td>\n",
       "      <td>19.094572</td>\n",
       "      <td>29.941523</td>\n",
       "      <td>2.198394</td>\n",
       "      <td>31.407448</td>\n",
       "      <td>32.466412</td>\n",
       "      <td>31.273087</td>\n",
       "      <td>7.187675</td>\n",
       "      <td>21.143253</td>\n",
       "      <td>54.197422</td>\n",
       "      <td>22.450768</td>\n",
       "      <td>14.092695</td>\n",
       "      <td>32.005489</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.768637</td>\n",
       "      <td>24.275478</td>\n",
       "      <td>20.912073</td>\n",
       "      <td>19.327810</td>\n",
       "      <td>7.207638</td>\n",
       "      <td>26.989864</td>\n",
       "      <td>33.681526</td>\n",
       "      <td>14.250582</td>\n",
       "      <td>34.645447</td>\n",
       "      <td>22.390442</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.217266</td>\n",
       "      <td>88.300003</td>\n",
       "      <td>13.001667</td>\n",
       "      <td>13.333424</td>\n",
       "      <td>40.624340</td>\n",
       "      <td>20.555794</td>\n",
       "      <td>48.868351</td>\n",
       "      <td>0.360417</td>\n",
       "      <td>5.015027</td>\n",
       "      <td>31.799999</td>\n",
       "      <td>12.096231</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.203109</td>\n",
       "      <td>15.397655</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.522963</td>\n",
       "      <td>32.741684</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.820738</td>\n",
       "      <td>51.392948</td>\n",
       "      <td>62.504234</td>\n",
       "      <td>6.196771</td>\n",
       "      <td>50.200001</td>\n",
       "      <td>11.271827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.728604</td>\n",
       "      <td>15.711464</td>\n",
       "      <td>5.300031</td>\n",
       "      <td>30.182482</td>\n",
       "      <td>1.578571</td>\n",
       "      <td>4.230385</td>\n",
       "      <td>8.862306</td>\n",
       "      <td>32.254601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.859955</td>\n",
       "      <td>24.313694</td>\n",
       "      <td>24.315294</td>\n",
       "      <td>31.557461</td>\n",
       "      <td>14.050106</td>\n",
       "      <td>1.717435</td>\n",
       "      <td>715.000000</td>\n",
       "      <td>12.953861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.000022</td>\n",
       "      <td>6.390332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.880678</td>\n",
       "      <td>26.807491</td>\n",
       "      <td>3.86</td>\n",
       "      <td>10.957647</td>\n",
       "      <td>22.240000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.590631</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.841457</td>\n",
       "      <td>11.881525</td>\n",
       "      <td>19.845028</td>\n",
       "      <td>9.024444</td>\n",
       "      <td>12.590994</td>\n",
       "      <td>31.506403</td>\n",
       "      <td>12.183955</td>\n",
       "      <td>23.957970</td>\n",
       "      <td>33.201008</td>\n",
       "      <td>12.384574</td>\n",
       "      <td>35.141846</td>\n",
       "      <td>26.128141</td>\n",
       "      <td>12.047138</td>\n",
       "      <td>18.474354</td>\n",
       "      <td>21.313898</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.043465</td>\n",
       "      <td>19.388849</td>\n",
       "      <td>19.071857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.744715</td>\n",
       "      <td>21.801615</td>\n",
       "      <td>10.502164</td>\n",
       "      <td>30.594568</td>\n",
       "      <td>28.361666</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.450</td>\n",
       "      <td>7.659702</td>\n",
       "      <td>26.448427</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.694471</td>\n",
       "      <td>33.252716</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.262737</td>\n",
       "      <td>60.409122</td>\n",
       "      <td>24.606104</td>\n",
       "      <td>8.30</td>\n",
       "      <td>20.451719</td>\n",
       "      <td>20.621426</td>\n",
       "      <td>10.080704</td>\n",
       "      <td>32.590252</td>\n",
       "      <td>10.785919</td>\n",
       "      <td>31.551979</td>\n",
       "      <td>1.747439</td>\n",
       "      <td>26.655270</td>\n",
       "      <td>5.935471</td>\n",
       "      <td>14.439473</td>\n",
       "      <td>21.027672</td>\n",
       "      <td>8.701778</td>\n",
       "      <td>11.935127</td>\n",
       "      <td>8.865540</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.571596</td>\n",
       "      <td>11.060853</td>\n",
       "      <td>26.547106</td>\n",
       "      <td>22.631548</td>\n",
       "      <td>21.766855</td>\n",
       "      <td>17.90</td>\n",
       "      <td>14.165676</td>\n",
       "      <td>27.309048</td>\n",
       "      <td>32.554211</td>\n",
       "      <td>83.383499</td>\n",
       "      <td>19.827686</td>\n",
       "      <td>17.193125</td>\n",
       "      <td>5.881657</td>\n",
       "      <td>34.305496</td>\n",
       "      <td>8.590302</td>\n",
       "      <td>20.963234</td>\n",
       "      <td>30.112633</td>\n",
       "      <td>7.634683</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.837582</td>\n",
       "      <td>21.689280</td>\n",
       "      <td>5.054221</td>\n",
       "      <td>24.302599</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.42</td>\n",
       "      <td>8.043176</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.129273</td>\n",
       "      <td>21.947546</td>\n",
       "      <td>39.176132</td>\n",
       "      <td>32.609047</td>\n",
       "      <td>4.874333</td>\n",
       "      <td>50.091190</td>\n",
       "      <td>27.930428</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.167362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.8200</td>\n",
       "      <td>18.394098</td>\n",
       "      <td>23.886600</td>\n",
       "      <td>7.799276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.521454</td>\n",
       "      <td>17.160110</td>\n",
       "      <td>21.931978</td>\n",
       "      <td>15.433409</td>\n",
       "      <td>31.157452</td>\n",
       "      <td>7.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.159514</td>\n",
       "      <td>20.051275</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.967243</td>\n",
       "      <td>11.427916</td>\n",
       "      <td>49.830173</td>\n",
       "      <td>18.290176</td>\n",
       "      <td>17.794830</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.676188</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.071020</td>\n",
       "      <td>41.331306</td>\n",
       "      <td>24.425566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.967041</td>\n",
       "      <td>10.52</td>\n",
       "      <td>12.499954</td>\n",
       "      <td>15.482761</td>\n",
       "      <td>14.696908</td>\n",
       "      <td>9.338558</td>\n",
       "      <td>45.700001</td>\n",
       "      <td>27.291714</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.140371</td>\n",
       "      <td>9.721224</td>\n",
       "      <td>13.551478</td>\n",
       "      <td>18.738796</td>\n",
       "      <td>42.078197</td>\n",
       "      <td>17.216822</td>\n",
       "      <td>5.901566</td>\n",
       "      <td>36.779324</td>\n",
       "      <td>6.877146</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.590872</td>\n",
       "      <td>70.401955</td>\n",
       "      <td>13.037074</td>\n",
       "      <td>37.982800</td>\n",
       "      <td>8.860278</td>\n",
       "      <td>27.385073</td>\n",
       "      <td>24.281670</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.978628</td>\n",
       "      <td>70.316795</td>\n",
       "      <td>52.650002</td>\n",
       "      <td>49.553436</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>13.856162</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.747234</td>\n",
       "      <td>1.052499</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.179622</td>\n",
       "      <td>14.846498</td>\n",
       "      <td>4.191111</td>\n",
       "      <td>19.393608</td>\n",
       "      <td>29.384233</td>\n",
       "      <td>22.989286</td>\n",
       "      <td>14.409596</td>\n",
       "      <td>21.863682</td>\n",
       "      <td>34.282318</td>\n",
       "      <td>22.629419</td>\n",
       "      <td>16.221462</td>\n",
       "      <td>9.403691</td>\n",
       "      <td>13.076375</td>\n",
       "      <td>858.222351</td>\n",
       "      <td>21.869110</td>\n",
       "      <td>17.160233</td>\n",
       "      <td>12.15</td>\n",
       "      <td>14.005639</td>\n",
       "      <td>10.28</td>\n",
       "      <td>6.692753</td>\n",
       "      <td>32.602650</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.990495</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.920000</td>\n",
       "      <td>9.057739</td>\n",
       "      <td>46.789970</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.758745</td>\n",
       "      <td>2.1160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.865000</td>\n",
       "      <td>18.123768</td>\n",
       "      <td>3.468145</td>\n",
       "      <td>38.082397</td>\n",
       "      <td>34.293888</td>\n",
       "      <td>3.779565</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.610752</td>\n",
       "      <td>14.058766</td>\n",
       "      <td>4.610459</td>\n",
       "      <td>37.021347</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.960278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.667065</td>\n",
       "      <td>89.730003</td>\n",
       "      <td>35.216850</td>\n",
       "      <td>30.030239</td>\n",
       "      <td>8.998008</td>\n",
       "      <td>13.961273</td>\n",
       "      <td>7.370133</td>\n",
       "      <td>23.515570</td>\n",
       "      <td>39.724529</td>\n",
       "      <td>13.129980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.854099</td>\n",
       "      <td>66.089996</td>\n",
       "      <td>56.299999</td>\n",
       "      <td>23.377794</td>\n",
       "      <td>25.010000</td>\n",
       "      <td>21.155216</td>\n",
       "      <td>51.200451</td>\n",
       "      <td>12.632596</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.896881</td>\n",
       "      <td>34.740002</td>\n",
       "      <td>10.645389</td>\n",
       "      <td>28.383474</td>\n",
       "      <td>333.135010</td>\n",
       "      <td>12.499696</td>\n",
       "      <td>26.733854</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.057941</td>\n",
       "      <td>28.703325</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.733333</td>\n",
       "      <td>12.289421</td>\n",
       "      <td>37.983086</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.585557</td>\n",
       "      <td>18.635391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.973400</td>\n",
       "      <td>21.829044</td>\n",
       "      <td>16.398130</td>\n",
       "      <td>35.244614</td>\n",
       "      <td>34.280506</td>\n",
       "      <td>8.076019</td>\n",
       "      <td>24.159374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.756396</td>\n",
       "      <td>10.02</td>\n",
       "      <td>7.0775</td>\n",
       "      <td>5.067769</td>\n",
       "      <td>62.893505</td>\n",
       "      <td>70.334389</td>\n",
       "      <td>17.700754</td>\n",
       "      <td>33.237148</td>\n",
       "      <td>17.336020</td>\n",
       "      <td>2.88125</td>\n",
       "      <td>22.109997</td>\n",
       "      <td>44.400002</td>\n",
       "      <td>4.3875</td>\n",
       "      <td>13.089932</td>\n",
       "      <td>4.234</td>\n",
       "      <td>1.577206</td>\n",
       "      <td>33.828911</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.674854</td>\n",
       "      <td>9.394668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.805689</td>\n",
       "      <td>25.865191</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.248493</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.189335</td>\n",
       "      <td>24.459637</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.707020</td>\n",
       "      <td>21.842522</td>\n",
       "      <td>19.768970</td>\n",
       "      <td>22.059961</td>\n",
       "      <td>24.059477</td>\n",
       "      <td>6.328644</td>\n",
       "      <td>9.283333</td>\n",
       "      <td>18.245258</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.959308</td>\n",
       "      <td>15.301198</td>\n",
       "      <td>17.401487</td>\n",
       "      <td>18.332138</td>\n",
       "      <td>19.934999</td>\n",
       "      <td>25.259312</td>\n",
       "      <td>16.531057</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.140522</td>\n",
       "      <td>21.024242</td>\n",
       "      <td>27.270124</td>\n",
       "      <td>19.409431</td>\n",
       "      <td>22.894506</td>\n",
       "      <td>16.972401</td>\n",
       "      <td>18.144224</td>\n",
       "      <td>48.255932</td>\n",
       "      <td>15.504475</td>\n",
       "      <td>20.006531</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.482310</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.600342</td>\n",
       "      <td>14.724371</td>\n",
       "      <td>13.004135</td>\n",
       "      <td>9.987989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.857716</td>\n",
       "      <td>20.615263</td>\n",
       "      <td>31.392845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.452751</td>\n",
       "      <td>3.337500</td>\n",
       "      <td>15.130361</td>\n",
       "      <td>23.001329</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.557176</td>\n",
       "      <td>8.370002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.089487</td>\n",
       "      <td>11.183640</td>\n",
       "      <td>29.966734</td>\n",
       "      <td>81.386253</td>\n",
       "      <td>17.337893</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>32.615635</td>\n",
       "      <td>14.233100</td>\n",
       "      <td>10.0250</td>\n",
       "      <td>26.609020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.930938</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.370993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.460793</td>\n",
       "      <td>131.569427</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.055463</td>\n",
       "      <td>6.414677</td>\n",
       "      <td>14.486022</td>\n",
       "      <td>20.899851</td>\n",
       "      <td>8.429969</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.828153</td>\n",
       "      <td>4.851101</td>\n",
       "      <td>24.104210</td>\n",
       "      <td>13.770735</td>\n",
       "      <td>14.978456</td>\n",
       "      <td>80.946312</td>\n",
       "      <td>44.904217</td>\n",
       "      <td>14.671057</td>\n",
       "      <td>11.240391</td>\n",
       "      <td>12.899178</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.644291</td>\n",
       "      <td>21.313818</td>\n",
       "      <td>45.092979</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.1575</td>\n",
       "      <td>21.581217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.400397</td>\n",
       "      <td>5.373663</td>\n",
       "      <td>13.488235</td>\n",
       "      <td>9.434629</td>\n",
       "      <td>35.188709</td>\n",
       "      <td>26.626202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.956970</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.7650</td>\n",
       "      <td>19.077335</td>\n",
       "      <td>27.754667</td>\n",
       "      <td>4.255</td>\n",
       "      <td>9.11</td>\n",
       "      <td>13.502537</td>\n",
       "      <td>18.507034</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.053125</td>\n",
       "      <td>9.017720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.980177</td>\n",
       "      <td>4.133333</td>\n",
       "      <td>12.00</td>\n",
       "      <td>29.647833</td>\n",
       "      <td>7.028139</td>\n",
       "      <td>47.615101</td>\n",
       "      <td>21.519228</td>\n",
       "      <td>17.134163</td>\n",
       "      <td>38.524170</td>\n",
       "      <td>16.947470</td>\n",
       "      <td>37.387291</td>\n",
       "      <td>20.663177</td>\n",
       "      <td>23.471710</td>\n",
       "      <td>25.354681</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.788130</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.818952</td>\n",
       "      <td>23.206285</td>\n",
       "      <td>32.908524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.94</td>\n",
       "      <td>11.855464</td>\n",
       "      <td>6.223255</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.087666</td>\n",
       "      <td>47.300907</td>\n",
       "      <td>18.859495</td>\n",
       "      <td>29.934540</td>\n",
       "      <td>2.208105</td>\n",
       "      <td>31.257446</td>\n",
       "      <td>32.621292</td>\n",
       "      <td>31.011999</td>\n",
       "      <td>7.169640</td>\n",
       "      <td>21.221909</td>\n",
       "      <td>54.173191</td>\n",
       "      <td>22.520681</td>\n",
       "      <td>14.156378</td>\n",
       "      <td>30.378199</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.749868</td>\n",
       "      <td>24.240349</td>\n",
       "      <td>20.853018</td>\n",
       "      <td>19.201290</td>\n",
       "      <td>7.222359</td>\n",
       "      <td>26.738749</td>\n",
       "      <td>33.673431</td>\n",
       "      <td>14.242314</td>\n",
       "      <td>34.958828</td>\n",
       "      <td>22.167147</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.183010</td>\n",
       "      <td>87.099998</td>\n",
       "      <td>13.122347</td>\n",
       "      <td>13.525402</td>\n",
       "      <td>40.337543</td>\n",
       "      <td>20.283283</td>\n",
       "      <td>49.372272</td>\n",
       "      <td>0.352708</td>\n",
       "      <td>5.088790</td>\n",
       "      <td>31.926666</td>\n",
       "      <td>11.993182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.211852</td>\n",
       "      <td>15.187861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.632864</td>\n",
       "      <td>32.613693</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.764450</td>\n",
       "      <td>51.331444</td>\n",
       "      <td>61.664074</td>\n",
       "      <td>6.257860</td>\n",
       "      <td>50.150002</td>\n",
       "      <td>11.321221</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.539272</td>\n",
       "      <td>15.510029</td>\n",
       "      <td>5.289897</td>\n",
       "      <td>30.109932</td>\n",
       "      <td>1.588571</td>\n",
       "      <td>4.232311</td>\n",
       "      <td>8.810072</td>\n",
       "      <td>32.187870</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.831930</td>\n",
       "      <td>24.347075</td>\n",
       "      <td>23.807590</td>\n",
       "      <td>31.051367</td>\n",
       "      <td>14.087230</td>\n",
       "      <td>1.684554</td>\n",
       "      <td>709.000000</td>\n",
       "      <td>12.965023</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.942704</td>\n",
       "      <td>6.268812</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.869932</td>\n",
       "      <td>26.854836</td>\n",
       "      <td>3.61</td>\n",
       "      <td>11.048828</td>\n",
       "      <td>22.180000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.321297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.780544</td>\n",
       "      <td>11.783958</td>\n",
       "      <td>19.703064</td>\n",
       "      <td>8.962818</td>\n",
       "      <td>12.520411</td>\n",
       "      <td>31.779064</td>\n",
       "      <td>12.188591</td>\n",
       "      <td>23.879990</td>\n",
       "      <td>33.548973</td>\n",
       "      <td>12.252522</td>\n",
       "      <td>34.791054</td>\n",
       "      <td>25.954824</td>\n",
       "      <td>12.057899</td>\n",
       "      <td>18.465712</td>\n",
       "      <td>21.264925</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.836956</td>\n",
       "      <td>19.426727</td>\n",
       "      <td>19.210302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.676115</td>\n",
       "      <td>21.907766</td>\n",
       "      <td>10.457174</td>\n",
       "      <td>30.192919</td>\n",
       "      <td>28.495956</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.325</td>\n",
       "      <td>7.620319</td>\n",
       "      <td>26.274893</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.841276</td>\n",
       "      <td>33.426151</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.111938</td>\n",
       "      <td>60.311749</td>\n",
       "      <td>24.501463</td>\n",
       "      <td>8.15</td>\n",
       "      <td>20.399229</td>\n",
       "      <td>20.412624</td>\n",
       "      <td>10.009422</td>\n",
       "      <td>32.622021</td>\n",
       "      <td>10.743279</td>\n",
       "      <td>31.172670</td>\n",
       "      <td>1.721682</td>\n",
       "      <td>26.641811</td>\n",
       "      <td>5.962574</td>\n",
       "      <td>14.386626</td>\n",
       "      <td>20.800983</td>\n",
       "      <td>8.478408</td>\n",
       "      <td>11.921142</td>\n",
       "      <td>8.834728</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.666782</td>\n",
       "      <td>10.986275</td>\n",
       "      <td>26.501760</td>\n",
       "      <td>22.048487</td>\n",
       "      <td>21.819250</td>\n",
       "      <td>17.98</td>\n",
       "      <td>14.230787</td>\n",
       "      <td>27.429945</td>\n",
       "      <td>32.500996</td>\n",
       "      <td>83.263992</td>\n",
       "      <td>19.816687</td>\n",
       "      <td>17.140959</td>\n",
       "      <td>5.977942</td>\n",
       "      <td>34.411770</td>\n",
       "      <td>8.513648</td>\n",
       "      <td>22.153666</td>\n",
       "      <td>30.132185</td>\n",
       "      <td>7.556066</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.510036</td>\n",
       "      <td>21.594151</td>\n",
       "      <td>5.040154</td>\n",
       "      <td>24.122154</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.07</td>\n",
       "      <td>7.992299</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.436636</td>\n",
       "      <td>21.696711</td>\n",
       "      <td>38.943150</td>\n",
       "      <td>32.958691</td>\n",
       "      <td>4.850622</td>\n",
       "      <td>50.204620</td>\n",
       "      <td>27.519833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.285824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6600</td>\n",
       "      <td>18.256742</td>\n",
       "      <td>23.777287</td>\n",
       "      <td>7.608322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.598410</td>\n",
       "      <td>17.069378</td>\n",
       "      <td>21.498672</td>\n",
       "      <td>15.514643</td>\n",
       "      <td>31.104143</td>\n",
       "      <td>7.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.089717</td>\n",
       "      <td>20.051275</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.680901</td>\n",
       "      <td>11.288555</td>\n",
       "      <td>49.734879</td>\n",
       "      <td>17.971220</td>\n",
       "      <td>17.484766</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.684824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.032095</td>\n",
       "      <td>41.543507</td>\n",
       "      <td>24.370924</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.281227</td>\n",
       "      <td>10.49</td>\n",
       "      <td>12.461341</td>\n",
       "      <td>15.437696</td>\n",
       "      <td>14.644886</td>\n",
       "      <td>9.084764</td>\n",
       "      <td>45.669998</td>\n",
       "      <td>27.530521</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.108260</td>\n",
       "      <td>9.735669</td>\n",
       "      <td>13.570619</td>\n",
       "      <td>18.714722</td>\n",
       "      <td>41.552238</td>\n",
       "      <td>17.133162</td>\n",
       "      <td>5.836842</td>\n",
       "      <td>36.738503</td>\n",
       "      <td>6.834516</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.561764</td>\n",
       "      <td>69.505348</td>\n",
       "      <td>13.240903</td>\n",
       "      <td>36.719097</td>\n",
       "      <td>8.809707</td>\n",
       "      <td>27.204771</td>\n",
       "      <td>24.095566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.911808</td>\n",
       "      <td>70.193161</td>\n",
       "      <td>53.099998</td>\n",
       "      <td>48.348259</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    A  AAL        AAP      AAPL  ABBV        ABC        ABT  \\\n",
       "Date                                                                          \n",
       "2005-01-03  14.570019  NaN  26.046276  0.961916   NaN  11.227891  14.587082   \n",
       "2005-01-04  14.185627  NaN  25.872833  0.971795   NaN  11.139072  14.440167   \n",
       "2005-01-05  14.179530  NaN  25.920677  0.980306   NaN  11.117834  14.274515   \n",
       "2005-01-06  13.868362  NaN  25.896755  0.981066   NaN  11.212444  14.596454   \n",
       "2005-01-07  13.856162  NaN  25.747234  1.052499   NaN  11.179622  14.846498   \n",
       "\n",
       "                ACGL        ACN       ADBE        ADI        ADM        ADP  \\\n",
       "Date                                                                          \n",
       "2005-01-03  4.233333  19.218691  30.838949  23.532494  14.488768  22.505222   \n",
       "2005-01-04  4.177778  18.766836  30.024111  22.892282  14.330419  22.145958   \n",
       "2005-01-05  4.153333  18.693958  29.859142  22.995754  14.086306  22.053587   \n",
       "2005-01-06  4.147778  18.526327  29.364239  22.956947  14.376613  21.904751   \n",
       "2005-01-07  4.191111  19.393608  29.384233  22.989286  14.409596  21.863682   \n",
       "\n",
       "                 ADSK        AEE        AEP       AES        AFL         AIG  \\\n",
       "Date                                                                           \n",
       "2005-01-03  37.410706  22.796192  16.537436  9.923675  13.082962  838.538147   \n",
       "2005-01-04  34.981960  22.615526  16.474241  9.557489  13.069791  841.332275   \n",
       "2005-01-05  35.251820  22.411699  16.279799  9.535515  12.974243  855.301697   \n",
       "2005-01-06  35.081905  22.638691  16.284664  9.542842  13.175208  856.698364   \n",
       "2005-01-07  34.282318  22.629419  16.221462  9.403691  13.076375  858.222351   \n",
       "\n",
       "                  AIZ        AJG   AKAM        ALB   ALGN       ALK  \\\n",
       "Date                                                                  \n",
       "2005-01-03  22.099463  17.718683  12.82  14.624438  10.56  7.373944   \n",
       "2005-01-04  21.667545  17.339153  12.20  14.028703  10.41  7.027728   \n",
       "2005-01-05  21.487579  17.246973  12.00  13.690475  10.40  6.868109   \n",
       "2005-01-06  22.027481  17.317465  11.94  13.955678  10.24  6.721979   \n",
       "2005-01-07  21.869110  17.160233  12.15  14.005639  10.28  6.692753   \n",
       "\n",
       "                  ALL  ALLE       AMAT  AMCR        AMD       AME       AMGN  \\\n",
       "Date                                                                           \n",
       "2005-01-03  32.724026   NaN  12.487932   NaN  21.410000  9.400531  47.763378   \n",
       "2005-01-04  32.615421   NaN  12.250350   NaN  20.209999  9.157941  47.005459   \n",
       "2005-01-05  32.359879   NaN  12.042464   NaN  19.750000  8.986540  46.262405   \n",
       "2005-01-06  32.640987   NaN  11.953376   NaN  19.719999  9.063015  46.693371   \n",
       "2005-01-07  32.602650   NaN  11.990495   NaN  19.920000  9.057739  46.789970   \n",
       "\n",
       "            AMP        AMT    AMZN  ANET       ANSS        AON       AOS  \\\n",
       "Date                                                                       \n",
       "2005-01-03  NaN  14.694016  2.2260   NaN  16.125000  18.719162  3.631645   \n",
       "2005-01-04  NaN  14.499825  2.1070   NaN  16.200001  18.544516  3.549895   \n",
       "2005-01-05  NaN  14.370360  2.0885   NaN  16.200001  18.044378  3.433465   \n",
       "2005-01-06  NaN  14.499825  2.0525   NaN  15.720000  18.504820  3.479293   \n",
       "2005-01-07  NaN  14.758745  2.1160   NaN  14.865000  18.123768  3.468145   \n",
       "\n",
       "                  APA        APD       APH  APTV        ARE        ATO  \\\n",
       "Date                                                                     \n",
       "2005-01-03  38.153522  34.531853  4.047470   NaN  40.998272  14.246146   \n",
       "2005-01-04  37.845306  33.871559  3.920744   NaN  40.341019  14.283621   \n",
       "2005-01-05  37.718884  33.901283  3.829588   NaN  38.425335  14.187250   \n",
       "2005-01-06  38.327381  34.109489  3.774006   NaN  38.200638  14.155130   \n",
       "2005-01-07  38.082397  34.293888  3.779565   NaN  38.610752  14.058766   \n",
       "\n",
       "                ATVI        AVB  AVGO        AVY  AWK        AXP        AZO  \\\n",
       "Date                                                                          \n",
       "2005-01-03  4.894716  38.766911   NaN  37.199196  NaN  37.012657  90.750000   \n",
       "2005-01-04  4.767549  38.334450   NaN  36.683674  NaN  36.456577  89.699997   \n",
       "2005-01-05  4.837366  36.484661   NaN  36.231007  NaN  36.118221  90.290001   \n",
       "2005-01-06  4.770042  37.073463   NaN  36.664803  NaN  35.932453  89.550003   \n",
       "2005-01-07  4.610459  37.021347   NaN  36.960278  NaN  35.667065  89.730003   \n",
       "\n",
       "                   BA        BAC      BALL        BAX      BBWI        BBY  \\\n",
       "Date                                                                         \n",
       "2005-01-03  35.678856  31.191706  9.214674  13.622866  7.389797  25.271982   \n",
       "2005-01-04  34.985836  30.762041  9.214674  13.595317  7.327534  24.598400   \n",
       "2005-01-05  35.566833  30.406223  8.995887  13.740910  7.412738  24.747618   \n",
       "2005-01-06  35.335846  30.359207  9.068109  13.796006  7.314425  23.660511   \n",
       "2005-01-07  35.216850  30.030239  8.998008  13.961273  7.370133  23.515570   \n",
       "\n",
       "                  BDX        BEN  BFB         BG       BIIB        BIO  \\\n",
       "Date                                                                     \n",
       "2005-01-03  40.557240  13.490870  NaN  39.711334  66.290001  57.169998   \n",
       "2005-01-04  40.086586  13.401621  NaN  38.561394  64.760002  57.250000   \n",
       "2005-01-05  39.862122  13.209533  NaN  37.592648  64.839996  56.090000   \n",
       "2005-01-06  39.869335  13.258038  NaN  37.669315  65.190002  56.619999   \n",
       "2005-01-07  39.724529  13.129980  NaN  38.854099  66.089996  56.299999   \n",
       "\n",
       "                   BK       BKNG        BKR        BLK        BMY  BR  BRKB  \\\n",
       "Date                                                                          \n",
       "2005-01-03  23.237417  23.730000  21.155216  49.527332  12.840353 NaN   NaN   \n",
       "2005-01-04  22.879486  23.879999  21.211494  49.376968  12.698978 NaN   NaN   \n",
       "2005-01-05  22.914581  23.590000  21.139870  48.919491  12.658124 NaN   NaN   \n",
       "2005-01-06  23.370768  24.180000  21.416147  52.285336  12.637704 NaN   NaN   \n",
       "2005-01-07  23.377794  25.010000  21.155216  51.200451  12.632596 NaN   NaN   \n",
       "\n",
       "                 BRO        BSX        BWA        BXP           C        CAG  \\\n",
       "Date                                                                           \n",
       "2005-01-03  8.921220  34.290001  10.991192  29.572882  330.532928  12.633684   \n",
       "2005-01-04  8.933382  34.169998  10.775844  29.066462  327.725525  12.590466   \n",
       "2005-01-05  8.943520  34.700001  10.601909  27.923500  331.833954  12.465124   \n",
       "2005-01-06  8.929327  35.189999  10.684731  28.434568  335.052429  12.560208   \n",
       "2005-01-07  8.896881  34.740002  10.645389  28.383474  333.135010  12.499696   \n",
       "\n",
       "                  CAH  CARR        CAT         CB  CBOE       CBRE        CCI  \\\n",
       "Date                                                                            \n",
       "2005-01-03  27.238813   NaN  29.583845  28.588514   NaN  10.983333  11.828124   \n",
       "2005-01-04  26.467089   NaN  29.257095  28.514214   NaN  10.920000  11.640720   \n",
       "2005-01-05  26.405163   NaN  28.696976  28.493952   NaN  10.606667  11.929033   \n",
       "2005-01-06  26.843426   NaN  29.120186  28.811386   NaN  10.723333  12.001110   \n",
       "2005-01-07  26.733854   NaN  29.057941  28.703325   NaN  10.733333  12.289421   \n",
       "\n",
       "                  CCL  CDAY   CDNS  CDW  CE  CEG  CF  CFG       CHD  \\\n",
       "Date                                                                  \n",
       "2005-01-03  37.857586   NaN  13.75  NaN NaN  NaN NaN  NaN  6.575630   \n",
       "2005-01-04  37.685833   NaN  13.30  NaN NaN  NaN NaN  NaN  6.492244   \n",
       "2005-01-05  37.619759   NaN  13.31  NaN NaN  NaN NaN  NaN  6.514084   \n",
       "2005-01-06  37.890591   NaN  13.34  NaN NaN  NaN NaN  NaN  6.581585   \n",
       "2005-01-07  37.983086   NaN  13.28  NaN NaN  NaN NaN  NaN  6.585557   \n",
       "\n",
       "                 CHRW  CHTR         CI       CINF         CL        CLX  \\\n",
       "Date                                                                      \n",
       "2005-01-03  18.806643   NaN  25.347277  21.702091  16.378483  35.184326   \n",
       "2005-01-04  18.724434   NaN  25.163507  21.374987  16.263884  34.816578   \n",
       "2005-01-05  18.892260   NaN  25.005085  21.775337  15.897146  34.641731   \n",
       "2005-01-06  18.888836   NaN  25.017750  21.931572  16.283533  34.949203   \n",
       "2005-01-07  18.635391   NaN  24.973400  21.829044  16.398130  35.244614   \n",
       "\n",
       "                  CMA     CMCSA        CME  CMG        CMI    CMS     CNC  \\\n",
       "Date                                                                        \n",
       "2005-01-03  34.957329  8.150414  24.193808  NaN  13.988682  10.39  7.1675   \n",
       "2005-01-04  34.725941  7.942125  23.815201  NaN  13.660637  10.25  7.0750   \n",
       "2005-01-05  34.361496  8.016515  24.148285  NaN  13.065740  10.11  6.9600   \n",
       "2005-01-06  34.407761  8.004113  24.592386  NaN  13.006247  10.10  7.0000   \n",
       "2005-01-07  34.280506  8.076019  24.159374  NaN  12.756396  10.02  7.0775   \n",
       "\n",
       "                 CNP        COF        COO        COP       COST        CPB  \\\n",
       "Date                                                                          \n",
       "2005-01-03  5.238273  64.305504  69.535233  17.544312  33.524094  17.512859   \n",
       "2005-01-04  5.186175  63.116085  70.107460  17.429592  32.922184  17.618959   \n",
       "2005-01-05  5.091452  62.486805  71.538033  17.558920  33.048187  17.483387   \n",
       "2005-01-06  5.096189  63.269512  71.380180  17.813387  33.524094  17.483387   \n",
       "2005-01-07  5.067769  62.893505  70.334389  17.700754  33.237148  17.336020   \n",
       "\n",
       "               CPRT        CPT        CRL     CRM       CSCO   CSGP       CSX  \\\n",
       "Date                                                                            \n",
       "2005-01-03  3.13250  23.353689  45.349998  4.1500  13.509480  4.621  1.616585   \n",
       "2005-01-04  3.01750  22.865421  44.360001  4.0900  12.978050  4.455  1.581671   \n",
       "2005-01-05  2.95250  22.086973  44.060001  4.4875  12.985047  4.408  1.575582   \n",
       "2005-01-06  2.94625  22.123817  44.860001  4.4300  13.180835  4.401  1.594662   \n",
       "2005-01-07  2.88125  22.109997  44.400002  4.3875  13.089932  4.234  1.577206   \n",
       "\n",
       "                 CTAS  CTLT      CTRA      CTSH  CTVA        CVS        CVX  \\\n",
       "Date                                                                          \n",
       "2005-01-03  33.357456   NaN  2.754452  9.698395   NaN  16.530188  25.738766   \n",
       "2005-01-04  32.885998   NaN  2.713370  9.589423   NaN  16.342857  25.561773   \n",
       "2005-01-05  32.800991   NaN  2.679989  9.501321   NaN  16.622034  25.728666   \n",
       "2005-01-06  33.117863   NaN  2.717862  9.387712   NaN  16.625700  26.158476   \n",
       "2005-01-07  33.828911   NaN  2.674854  9.394668   NaN  16.805689  25.865191   \n",
       "\n",
       "            CZR          D  DAL         DD         DE  DFS  DG        DGX  \\\n",
       "Date                                                                        \n",
       "2005-01-03  NaN  16.386909  NaN  40.389751  25.306190  NaN NaN  35.905075   \n",
       "2005-01-04  NaN  16.311630  NaN  39.516006  24.702505  NaN NaN  35.503311   \n",
       "2005-01-05  NaN  16.197496  NaN  39.115845  24.463116  NaN NaN  35.018166   \n",
       "2005-01-06  NaN  16.284916  NaN  39.564995  24.803118  NaN NaN  34.919628   \n",
       "2005-01-07  NaN  16.248493  NaN  39.189335  24.459637  NaN NaN  34.707020   \n",
       "\n",
       "                  DHI        DHR        DIS       DISH       DLR      DLTR  \\\n",
       "Date                                                                         \n",
       "2005-01-03  22.944559  20.028978  22.612066  24.309177  6.486145  9.513333   \n",
       "2005-01-04  21.929991  19.822390  22.368484  23.721647  6.514782  9.210000   \n",
       "2005-01-05  21.457687  19.722664  22.246700  23.714304  6.300009  9.433333   \n",
       "2005-01-06  21.889170  19.733343  22.279171  23.802431  6.390692  9.366667   \n",
       "2005-01-07  21.842522  19.768970  22.059961  24.059477  6.328644  9.283333   \n",
       "\n",
       "                  DOV  DOW       DPZ        DRI        DTE        DUK  \\\n",
       "Date                                                                    \n",
       "2005-01-03  19.152176  NaN  8.169011  14.680956  17.421858  18.614513   \n",
       "2005-01-04  19.063807  NaN  8.201631  14.643202  17.417782  18.428743   \n",
       "2005-01-05  18.691744  NaN  8.117752  14.222514  17.315926  18.287554   \n",
       "2005-01-06  18.515005  NaN  8.038529  14.761853  17.389265  18.287554   \n",
       "2005-01-07  18.245258  NaN  7.959308  15.301198  17.401487  18.332138   \n",
       "\n",
       "                  DVA        DVN        DXC  DXCM         EA       EBAY  \\\n",
       "Date                                                                      \n",
       "2005-01-03  19.680000  25.388985  17.008450   NaN  60.054203  22.509624   \n",
       "2005-01-04  19.754999  25.327568  16.696306   NaN  58.337811  21.957289   \n",
       "2005-01-05  19.650000  24.979494  16.622866   NaN  58.900074  21.876413   \n",
       "2005-01-06  19.629999  25.327568  16.503523   NaN  57.617714  20.945335   \n",
       "2005-01-07  19.934999  25.259312  16.531057   NaN  58.140522  21.024242   \n",
       "\n",
       "                  ECL         ED        EFX        EIX         EL        ELV  \\\n",
       "Date                                                                           \n",
       "2005-01-03  27.973494  19.604109  23.877598  17.416594  18.468307  46.880760   \n",
       "2005-01-04  27.617764  19.545254  23.044474  17.372721  18.095615  46.255676   \n",
       "2005-01-05  27.350975  19.332460  23.186098  17.093054  17.751286  48.014233   \n",
       "2005-01-06  27.431816  19.355097  22.994476  17.098537  17.986240  48.089252   \n",
       "2005-01-07  27.270124  19.409431  22.894506  16.972401  18.144224  48.255932   \n",
       "\n",
       "                  EMN        EMR  ENPH        EOG  EPAM       EQIX        EQR  \\\n",
       "Date                                                                            \n",
       "2005-01-03  16.999739  20.474434   NaN  12.686282   NaN  34.025291  15.374931   \n",
       "2005-01-04  15.483706  20.236012   NaN  12.486128   NaN  33.371868  15.279517   \n",
       "2005-01-05  15.311636  20.054216   NaN  12.381278   NaN  32.679081  14.789430   \n",
       "2005-01-06  15.632049  20.185349   NaN  12.564280   NaN  32.954617  14.789430   \n",
       "2005-01-07  15.504475  20.006531   NaN  12.482310   NaN  32.600342  14.724371   \n",
       "\n",
       "                  EQT         ES  ESM3        ESS        ETN        ETR  ETSY  \\\n",
       "Date                                                                            \n",
       "2005-01-03  13.077070  10.208722   NaN  44.883560  21.637350  32.137657   NaN   \n",
       "2005-01-04  12.973197  10.109393   NaN  43.934589  21.053307  31.891003   NaN   \n",
       "2005-01-05  12.922363  10.015586   NaN  42.345757  20.746069  31.378338   NaN   \n",
       "2005-01-06  13.147793   9.999030   NaN  42.134270  20.806906  31.407349   NaN   \n",
       "2005-01-07  13.004135   9.987989   NaN  41.857716  20.615263  31.392845   NaN   \n",
       "\n",
       "                 EVRG        EW        EXC       EXPD  EXPE       EXR  \\\n",
       "Date                                                                    \n",
       "2005-01-03  10.646234  3.395833  15.562348  22.345314   NaN  6.333207   \n",
       "2005-01-04  10.561290  3.323333  15.457955  21.974518   NaN  6.395154   \n",
       "2005-01-05  10.476348  3.289167  15.227561  22.667208   NaN  6.195008   \n",
       "2005-01-06  10.509382  3.335833  15.285158  22.781298   NaN  6.409452   \n",
       "2005-01-07  10.452751  3.337500  15.130361  23.001329   NaN  6.557176   \n",
       "\n",
       "                   F  FANG      FAST        FCX        FDS        FDX  \\\n",
       "Date                                                                    \n",
       "2005-01-03  8.404287   NaN  5.057049  11.682856  31.317869  83.521484   \n",
       "2005-01-04  8.375719   NaN  4.915650  11.221319  30.680763  82.029404   \n",
       "2005-01-05  8.244312   NaN  4.920641  11.092586  30.098555  81.926529   \n",
       "2005-01-06  8.255739   NaN  5.007973  11.076889  30.213898  81.626358   \n",
       "2005-01-07  8.370002   NaN  5.089487  11.183640  29.966734  81.386253   \n",
       "\n",
       "                   FE       FFIV       FICO        FIS     FISV       FITB  \\\n",
       "Date                                                                         \n",
       "2005-01-03  17.720682  23.525000  34.395191  14.285803  10.0050  27.535551   \n",
       "2005-01-04  17.662132  22.360001  32.975437  14.168241   9.8775  27.338661   \n",
       "2005-01-05  17.518028  22.240000  33.024048  14.107431   9.9275  26.898567   \n",
       "2005-01-06  17.522533  21.145000  32.849007  14.204720  10.0000  26.788532   \n",
       "2005-01-07  17.337893  21.100000  32.615635  14.233100  10.0250  26.609020   \n",
       "\n",
       "            FLT       FMC  FOX  FOXA  FRC        FRT  FSLR  FTNT  FTV  \\\n",
       "Date                                                                    \n",
       "2005-01-03  NaN  8.368217  NaN   NaN  NaN  27.534191   NaN   NaN  NaN   \n",
       "2005-01-04  NaN  7.996173  NaN   NaN  NaN  27.151833   NaN   NaN  NaN   \n",
       "2005-01-05  NaN  7.828671  NaN   NaN  NaN  26.171732   NaN   NaN  NaN   \n",
       "2005-01-06  NaN  7.957385  NaN   NaN  NaN  26.360218   NaN   NaN  NaN   \n",
       "2005-01-07  NaN  7.930938  NaN   NaN  NaN  26.370993   NaN   NaN  NaN   \n",
       "\n",
       "                   GD          GE  GEHC       GEN      GILD        GIS  \\\n",
       "Date                                                                     \n",
       "2005-01-03  34.201683  133.725769   NaN  9.972805  6.640290  13.819250   \n",
       "2005-01-04  33.313274  132.117661   NaN  9.672102  6.477772  13.776856   \n",
       "2005-01-05  33.279758  131.313644   NaN  9.531260  6.387909  14.059457   \n",
       "2005-01-06  33.340092  132.373520   NaN  8.823269  6.428060  14.161835   \n",
       "2005-01-07  33.460793  131.569427   NaN  9.055463  6.414677  14.486022   \n",
       "\n",
       "                   GL       GLW  GM  GNRC      GOOG     GOOGL        GPC  \\\n",
       "Date                                                                       \n",
       "2005-01-03  21.209904  8.309337 NaN   NaN  5.048826  5.072823  24.710352   \n",
       "2005-01-04  20.996979  8.181615 NaN   NaN  4.844342  4.867367  24.483755   \n",
       "2005-01-05  20.993256  8.089364 NaN   NaN  4.819685  4.842593  24.211830   \n",
       "2005-01-06  21.067955  8.330626 NaN   NaN  4.696148  4.718468  24.268486   \n",
       "2005-01-07  20.899851  8.429969 NaN   NaN  4.828153  4.851101  24.104210   \n",
       "\n",
       "                  GPN       GRMN         GS        GWW        HAL        HAS  \\\n",
       "Date                                                                           \n",
       "2005-01-03  13.833051  16.532986  81.077652  47.134235  14.686513  11.542553   \n",
       "2005-01-04  13.586203  15.890412  80.552307  46.337791  14.701956  11.512338   \n",
       "2005-01-05  13.437614  15.028969  80.189240  45.657215  14.516546  11.421691   \n",
       "2005-01-06  13.564634  14.967240  81.293968  45.280701  14.775355  11.433777   \n",
       "2005-01-07  13.770735  14.978456  80.946312  44.904217  14.671057  11.240391   \n",
       "\n",
       "                 HBAN  HCA         HD        HES        HIG  HII  HLT    HOLX  \\\n",
       "Date                                                                            \n",
       "2005-01-03  13.171698  NaN  27.724991  21.140642  45.961456  NaN  NaN  6.8000   \n",
       "2005-01-04  13.091542  NaN  27.371185  21.180607  45.453743  NaN  NaN  6.4475   \n",
       "2005-01-05  13.006044  NaN  27.120317  21.047400  45.260010  NaN  NaN  6.4150   \n",
       "2005-01-06  13.027424  NaN  26.715057  21.319147  45.440350  NaN  NaN  6.4025   \n",
       "2005-01-07  12.899178  NaN  26.644291  21.313818  45.092979  NaN  NaN  6.1575   \n",
       "\n",
       "                  HON  HPE       HPQ       HRL       HSIC       HST  \\\n",
       "Date                                                                  \n",
       "2005-01-03  22.268833  NaN  6.464890  5.405458  13.345098  9.702888   \n",
       "2005-01-04  21.871405  NaN  6.421894  5.396626  13.392157  9.617270   \n",
       "2005-01-05  21.808319  NaN  6.449535  5.345400  13.378431  9.286231   \n",
       "2005-01-06  21.663219  NaN  6.437251  5.366596  13.425490  9.388970   \n",
       "2005-01-07  21.581217  NaN  6.400397  5.373663  13.488235  9.434629   \n",
       "\n",
       "                  HSY        HUM  HWM  HYG        IBM  ICE     IDXX  \\\n",
       "Date                                                                  \n",
       "2005-01-03  35.416748  26.390881  NaN  NaN  55.066761  NaN  13.6875   \n",
       "2005-01-04  35.794624  26.336590  NaN  NaN  54.475281  NaN  13.6750   \n",
       "2005-01-05  34.928101  26.879606  NaN  NaN  54.362602  NaN  13.7325   \n",
       "2005-01-06  34.862938  26.825306  NaN  NaN  54.193569  NaN  13.7125   \n",
       "2005-01-07  35.188709  26.626202  NaN  NaN  53.956970  NaN  13.7650   \n",
       "\n",
       "                  IEX        IFF   ILMN  INCY       INTC       INTU  INVH  \\\n",
       "Date                                                                        \n",
       "2005-01-03  20.135777  28.223948  4.635  9.64  13.662444  19.237984   NaN   \n",
       "2005-01-04  19.752287  27.419472  4.490  9.27  13.390020  18.605686   NaN   \n",
       "2005-01-05  19.327890  27.385958  4.250  9.25  13.259729  18.394922   NaN   \n",
       "2005-01-06  19.379032  27.540148  4.295  9.30  13.301186  18.278332   NaN   \n",
       "2005-01-07  19.077335  27.754667  4.255  9.11  13.502537  18.507034   NaN   \n",
       "\n",
       "                   IP       IPG  IQV  IR       IRM      ISRG     IT  \\\n",
       "Date                                                                  \n",
       "2005-01-03  20.402803  9.216443  NaN NaN  8.020536  4.192222  12.35   \n",
       "2005-01-04  19.912273  9.051983  NaN NaN  7.791840  4.045556  12.15   \n",
       "2005-01-05  20.198814  9.038277  NaN NaN  7.888701  4.010000  12.00   \n",
       "2005-01-06  20.101692  9.065690  NaN NaN  7.910225  4.090000  12.05   \n",
       "2005-01-07  20.053125  9.017720  NaN NaN  7.980177  4.133333  12.00   \n",
       "\n",
       "                  ITW       IVZ        IWM          J       JBHT        JCI  \\\n",
       "Date                                                                          \n",
       "2005-01-03  30.019175  6.922497  49.943863  21.988581  18.055584  37.924900   \n",
       "2005-01-04  29.830254  6.755689  48.873230  21.993324  17.633781  38.149635   \n",
       "2005-01-05  30.006142  6.811288  47.896420  21.609306  17.232445  37.978432   \n",
       "2005-01-06  29.683674  6.855774  48.150394  21.618790  17.465878  38.920128   \n",
       "2005-01-07  29.647833  7.028139  47.615101  21.519228  17.134163  38.524170   \n",
       "\n",
       "                 JKHY        JNJ       JNPR        JPM          K  KDP  \\\n",
       "Date                                                                     \n",
       "2005-01-03  16.566618  37.560471  21.766951  23.722313  25.440701  NaN   \n",
       "2005-01-04  16.011229  37.441044  20.939121  23.477819  25.348946  NaN   \n",
       "2005-01-05  16.098507  37.417141  20.809265  23.526722  25.503790  NaN   \n",
       "2005-01-06  16.693565  37.524628  20.435934  23.661194  25.538204  NaN   \n",
       "2005-01-07  16.947470  37.387291  20.663177  23.471710  25.354681  NaN   \n",
       "\n",
       "                  KEY  KEYS  KHC        KIM       KLAC        KMB  KMI    KMX  \\\n",
       "Date                                                                            \n",
       "2005-01-03  19.361322   NaN  NaN  12.253695  24.464628  33.118881  NaN  15.10   \n",
       "2005-01-04  19.280260   NaN  NaN  12.108776  23.670748  33.134277  NaN  14.99   \n",
       "2005-01-05  19.152893   NaN  NaN  11.593056  23.287289  32.564751  NaN  14.93   \n",
       "2005-01-06  18.979187   NaN  NaN  11.808299  22.849848  33.093239  NaN  14.83   \n",
       "2005-01-07  18.788130   NaN  NaN  11.818952  23.206285  32.908524  NaN  14.94   \n",
       "\n",
       "                   KO        KR   L  LDOS        LEN         LH        LHX  \\\n",
       "Date                                                                         \n",
       "2005-01-03  11.964920  6.417845 NaN   NaN  45.830872  48.141151  19.909084   \n",
       "2005-01-04  11.797857  6.245707 NaN   NaN  43.727570  47.933559  19.028351   \n",
       "2005-01-05  11.743137  6.193316 NaN   NaN  43.318367  47.330563  18.823072   \n",
       "2005-01-06  11.841063  6.144665 NaN   NaN  43.809425  47.617229  19.094572   \n",
       "2005-01-07  11.855464  6.223255 NaN   NaN  44.087666  47.300907  18.859495   \n",
       "\n",
       "                  LIN       LKQ        LLY        LMT        LNC       LNT  \\\n",
       "Date                                                                         \n",
       "2005-01-03  30.702436  2.403545  31.251883  32.287735  30.620903  7.239202   \n",
       "2005-01-04  30.262651  2.306432  30.835188  31.739779  30.747080  7.208285   \n",
       "2005-01-05  29.648317  2.203249  31.157431  32.537891  30.680674  7.164487   \n",
       "2005-01-06  29.941523  2.198394  31.407448  32.466412  31.273087  7.187675   \n",
       "2005-01-07  29.934540  2.208105  31.257446  32.621292  31.011999  7.169640   \n",
       "\n",
       "                  LOW        LQD       LRCX        LUV        LVS  LW  LYB  \\\n",
       "Date                                                                         \n",
       "2005-01-03  21.708817  54.420456  24.285978  14.620375  32.352276 NaN  NaN   \n",
       "2005-01-04  21.255625  54.115005  23.412069  14.201869  32.985851 NaN  NaN   \n",
       "2005-01-05  21.075834  54.158638  22.616806  14.201869  32.579025 NaN  NaN   \n",
       "2005-01-06  21.143253  54.197422  22.450768  14.092695  32.005489 NaN  NaN   \n",
       "2005-01-07  21.221909  54.173191  22.520681  14.156378  30.378199 NaN  NaN   \n",
       "\n",
       "            LYV  MA        MAA        MAR        MAS        MCD      MCHP  \\\n",
       "Date                                                                        \n",
       "2005-01-03  NaN NaN  19.172163  24.408182  21.488514  19.171158  7.655173   \n",
       "2005-01-04  NaN NaN  19.101778  24.033506  21.030190  19.327810  7.522676   \n",
       "2005-01-05  NaN NaN  18.393261  24.049122  20.728994  19.177185  7.293025   \n",
       "2005-01-06  NaN NaN  18.768637  24.275478  20.912073  19.327810  7.207638   \n",
       "2005-01-07  NaN NaN  18.749868  24.240349  20.853018  19.201290  7.222359   \n",
       "\n",
       "                  MCK        MCO       MDLZ        MDT        MET  META  \\\n",
       "Date                                                                      \n",
       "2005-01-03  26.903273  34.440208  14.415898  34.363136  22.418354   NaN   \n",
       "2005-01-04  26.556921  33.920910  14.358037  34.203232  22.278793   NaN   \n",
       "2005-01-05  26.548262  33.774841  14.242314  33.949024  22.133659   NaN   \n",
       "2005-01-06  26.989864  33.681526  14.250582  34.645447  22.390442   NaN   \n",
       "2005-01-07  26.738749  33.673431  14.242314  34.958828  22.167147   NaN   \n",
       "\n",
       "                  MGM        MHK        MKC       MKTX        MLM        MMC  \\\n",
       "Date                                                                           \n",
       "2005-01-03  33.846527  89.800003  13.091311  13.918072  41.747719  21.347406   \n",
       "2005-01-04  33.586792  88.750000  13.098211  13.577760  40.775730  21.412285   \n",
       "2005-01-05  34.191288  87.800003  12.932717  13.612659  40.759804  21.217636   \n",
       "2005-01-06  36.217266  88.300003  13.001667  13.333424  40.624340  20.555794   \n",
       "2005-01-07  35.183010  87.099998  13.122347  13.525402  40.337543  20.283283   \n",
       "\n",
       "                  MMM      MNST        MO        MOH        MOS  MPC  \\\n",
       "Date                                                                   \n",
       "2005-01-03  49.432259  0.382708  5.024972  31.133333  12.841348  NaN   \n",
       "2005-01-04  49.030331  0.366771  5.059783  32.073334  12.135864  NaN   \n",
       "2005-01-05  48.430428  0.349063  5.050664  31.866667  11.850501  NaN   \n",
       "2005-01-06  48.868351  0.360417  5.015027  31.799999  12.096231  NaN   \n",
       "2005-01-07  49.372272  0.352708  5.088790  31.926666  11.993182  NaN   \n",
       "\n",
       "                MPWR        MRK  MRNA       MRO         MS  MSCI       MSFT  \\\n",
       "Date                                                                          \n",
       "2005-01-03  7.753834  15.251281   NaN  7.585164  32.520618   NaN  18.813698   \n",
       "2005-01-04  7.561518  15.187861   NaN  7.500154  32.171562   NaN  18.884050   \n",
       "2005-01-05  7.255560  15.290312   NaN  7.408915  31.985392   NaN  18.841835   \n",
       "2005-01-06  7.203109  15.397655   NaN  7.522963  32.741684   NaN  18.820738   \n",
       "2005-01-07  7.211852  15.187861   NaN  7.632864  32.613693   NaN  18.764450   \n",
       "\n",
       "                  MSI        MTB      MTCH        MTD         MU  NCLH  \\\n",
       "Date                                                                     \n",
       "2005-01-03  52.469410  63.088165  6.387365  51.070000  11.854682   NaN   \n",
       "2005-01-04  51.423702  62.814056  6.262747  50.360001  11.518800   NaN   \n",
       "2005-01-05  50.808582  62.718746  6.213876  50.369999  11.390375   NaN   \n",
       "2005-01-06  51.392948  62.504234  6.196771  50.200001  11.271827   NaN   \n",
       "2005-01-07  51.331444  61.664074  6.257860  50.150002  11.321221   NaN   \n",
       "\n",
       "                NDAQ       NDSN       NEE        NEM      NFLX        NI  \\\n",
       "Date                                                                       \n",
       "2005-01-03  2.826054  15.969288  5.348523  30.733908  1.702857  4.307406   \n",
       "2005-01-04  2.742525  15.638940  5.283382  30.160732  1.665714  4.240012   \n",
       "2005-01-05  2.714682  15.481833  5.215351  30.233274  1.600000  4.214981   \n",
       "2005-01-06  2.728604  15.711464  5.300031  30.182482  1.578571  4.230385   \n",
       "2005-01-07  2.539272  15.510029  5.289897  30.109932  1.588571  4.232311   \n",
       "\n",
       "                 NKE        NOC  NOW        NRG        NSC       NTAP  \\\n",
       "Date                                                                    \n",
       "2005-01-03  9.110441  32.551903  NaN  14.176230  23.726053  25.541609   \n",
       "2005-01-04  8.980848  31.854155  NaN  13.895983  23.532398  24.526192   \n",
       "2005-01-05  8.873362  32.339546  NaN  13.723836  23.966444  24.565256   \n",
       "2005-01-06  8.862306  32.254601  NaN  13.859955  24.313694  24.315294   \n",
       "2005-01-07  8.810072  32.187870  NaN  13.831930  24.347075  23.807590   \n",
       "\n",
       "                 NTRS        NUE      NVDA         NVR        NWL  NWS  NWSA  \\\n",
       "Date                                                                           \n",
       "2005-01-03  31.584089  14.407066  1.803077  741.520020  13.405938  NaN   NaN   \n",
       "2005-01-04  31.311054  14.312835  1.718199  720.059998  13.193852  NaN   NaN   \n",
       "2005-01-05  31.191202  14.187177  1.734257  712.500000  12.920380  NaN   NaN   \n",
       "2005-01-06  31.557461  14.050106  1.717435  715.000000  12.953861  NaN   NaN   \n",
       "2005-01-07  31.051367  14.087230  1.684554  709.000000  12.965023  NaN   NaN   \n",
       "\n",
       "            NXPI         O      ODFL  OGN       OKE        OMC    ON  \\\n",
       "Date                                                                   \n",
       "2005-01-03   NaN  9.561811  6.797321  NaN  4.991725  26.706465  4.44   \n",
       "2005-01-04   NaN  9.473913  6.749098  NaN  4.907541  26.690693  4.13   \n",
       "2005-01-05   NaN  8.992375  6.359468  NaN  4.873512  26.564419  4.00   \n",
       "2005-01-06   NaN  9.000022  6.390332  NaN  4.880678  26.807491  3.86   \n",
       "2005-01-07   NaN  8.942704  6.268812  NaN  4.869932  26.854836  3.61   \n",
       "\n",
       "                 ORCL       ORLY  OTIS        OXY  PARA  PAYC       PAYX  \\\n",
       "Date                                                                       \n",
       "2005-01-03  11.115135  22.545000   NaN  16.555498   NaN   NaN  18.494865   \n",
       "2005-01-04  10.825035  22.469999   NaN  16.371071   NaN   NaN  18.123861   \n",
       "2005-01-05  10.858188  22.445000   NaN  16.280312   NaN   NaN  17.996504   \n",
       "2005-01-06  10.957647  22.240000   NaN  16.590631   NaN   NaN  17.841457   \n",
       "2005-01-07  11.048828  22.180000   NaN  16.321297   NaN   NaN  17.780544   \n",
       "\n",
       "                 PCAR        PCG      PEAK        PEG        PEP        PFE  \\\n",
       "Date                                                                          \n",
       "2005-01-03  12.818127  20.382046  9.397608  12.843070  31.470049  12.258105   \n",
       "2005-01-04  12.395357  20.227732  9.267516  12.734679  31.245876  12.258105   \n",
       "2005-01-05  11.995350  19.980825  8.952547  12.565788  31.282230  12.174685   \n",
       "2005-01-06  11.881525  19.845028  9.024444  12.590994  31.506403  12.183955   \n",
       "2005-01-07  11.783958  19.703064  8.962818  12.520411  31.779064  12.188591   \n",
       "\n",
       "                  PFG         PG        PGR         PH        PHM        PKG  \\\n",
       "Date                                                                           \n",
       "2005-01-03  24.329876  33.111019  12.431433  36.384205  26.728401  12.526014   \n",
       "2005-01-04  24.305882  32.697063  12.309317  35.619297  25.718105  12.316170   \n",
       "2005-01-05  24.029955  33.039021  12.317836  34.985943  25.506752  12.170894   \n",
       "2005-01-06  23.957970  33.201008  12.384574  35.141846  26.128141  12.047138   \n",
       "2005-01-07  23.879990  33.548973  12.252522  34.791054  25.954824  12.057899   \n",
       "\n",
       "                  PKI        PLD  PM        PNC        PNR        PNW  PODD  \\\n",
       "Date                                                                          \n",
       "2005-01-03  19.087852  22.031969 NaN  34.359306  20.359480  19.710556   NaN   \n",
       "2005-01-04  18.854544  22.021091 NaN  34.116352  19.909670  19.683758   NaN   \n",
       "2005-01-05  18.292896  21.118057 NaN  33.812668  19.317825  19.246048   NaN   \n",
       "2005-01-06  18.474354  21.313898 NaN  34.043465  19.388849  19.071857   NaN   \n",
       "2005-01-07  18.465712  21.264925 NaN  33.836956  19.426727  19.210302   NaN   \n",
       "\n",
       "                 POOL        PPG        PPL        PRU        PSA  PSX  \\\n",
       "Date                                                                     \n",
       "2005-01-03  24.383493  22.309166  10.843645  30.904421  29.704557  NaN   \n",
       "2005-01-04  23.766096  21.804932  10.723003  30.680635  29.328547  NaN   \n",
       "2005-01-05  22.851435  21.496416  10.569640  30.376537  28.281084  NaN   \n",
       "2005-01-06  22.744715  21.801615  10.502164  30.594568  28.361666  NaN   \n",
       "2005-01-07  22.676115  21.907766  10.457174  30.192919  28.495956  NaN   \n",
       "\n",
       "               PTC       PWR        PXD  PYPL       QCOM        QQQ  QRVO  \\\n",
       "Date                                                                        \n",
       "2005-01-03  14.150  7.935371  26.921709   NaN  28.240692  34.249878   NaN   \n",
       "2005-01-04  13.675  7.580937  26.748169   NaN  28.113909  33.625580   NaN   \n",
       "2005-01-05  13.375  7.679392  26.148687   NaN  28.234013  33.417480   NaN   \n",
       "2005-01-06  13.450  7.659702  26.448427   NaN  28.694471  33.252716   NaN   \n",
       "2005-01-07  13.325  7.620319  26.274893   NaN  28.841276  33.426151   NaN   \n",
       "\n",
       "                  RCL         RE        REG  REGN         RF        RHI  \\\n",
       "Date                                                                      \n",
       "2005-01-03  42.977036  61.584785  25.942730  9.04  20.556679  20.556618   \n",
       "2005-01-04  42.548450  61.007389  25.519398  8.35  20.486700  20.650234   \n",
       "2005-01-05  41.945274  60.235222  24.415863  8.41  20.364241  20.225422   \n",
       "2005-01-06  42.262737  60.409122  24.606104  8.30  20.451719  20.621426   \n",
       "2005-01-07  42.111938  60.311749  24.501463  8.15  20.399229  20.412624   \n",
       "\n",
       "                  RJF         RL        RMD        ROK       ROL        ROP  \\\n",
       "Date                                                                          \n",
       "2005-01-03  10.365809  33.201870  10.832823  33.021893  1.763708  26.942366   \n",
       "2005-01-04  10.209682  32.836491  10.773129  32.513870  1.730495  26.525158   \n",
       "2005-01-05   9.975478  32.479065  10.788052  31.829721  1.735917  26.552094   \n",
       "2005-01-06  10.080704  32.590252  10.785919  31.551979  1.747439  26.655270   \n",
       "2005-01-07  10.009422  32.622021  10.743279  31.172670  1.721682  26.641811   \n",
       "\n",
       "                ROST        RSG        RTX      SBAC       SBUX      SCHW  \\\n",
       "Date                                                                        \n",
       "2005-01-03  5.779112  14.633303  21.420725  8.915441  12.214824  8.981071   \n",
       "2005-01-04  5.802044  14.584842  21.173248  8.857168  12.206831  8.773108   \n",
       "2005-01-05  5.752009  14.474725  21.015192  8.624084  12.306726  8.719192   \n",
       "2005-01-06  5.935471  14.439473  21.027672  8.701778  11.935127  8.865540   \n",
       "2005-01-07  5.962574  14.386626  20.800983  8.478408  11.921142  8.834728   \n",
       "\n",
       "            SEDG        SEE        SHW        SJM        SLB        SNA  \\\n",
       "Date                                                                      \n",
       "2005-01-03   NaN  19.658882  11.346319  26.552788  22.298370  22.441540   \n",
       "2005-01-04   NaN  19.014561  11.212584  26.303331  22.128309  21.976465   \n",
       "2005-01-05   NaN  18.531321  11.053143  26.382719  22.197718  21.747198   \n",
       "2005-01-06   NaN  18.571596  11.060853  26.547106  22.631548  21.766855   \n",
       "2005-01-07   NaN  18.666782  10.986275  26.501760  22.048487  21.819250   \n",
       "\n",
       "             SNPS         SO        SPG       SPGI        SPY        SRE  \\\n",
       "Date                                                                       \n",
       "2005-01-03  19.41  14.352347  28.634432  31.947550  84.571556  19.954111   \n",
       "2005-01-04  18.58  14.343664  28.320997  31.936888  83.538139  19.904638   \n",
       "2005-01-05  18.07  14.256837  27.067263  32.000744  82.961700  19.651783   \n",
       "2005-01-06  17.90  14.165676  27.309048  32.554211  83.383499  19.827686   \n",
       "2005-01-07  17.98  14.230787  27.429945  32.500996  83.263992  19.816687   \n",
       "\n",
       "                  STE      STLD        STT       STX        STZ        SWK  \\\n",
       "Date                                                                         \n",
       "2005-01-03  17.260185  6.009482  34.510967  8.886695  20.949709  31.233461   \n",
       "2005-01-04  16.880116  6.022762  34.369270  8.723166  20.742283  30.718668   \n",
       "2005-01-05  16.768324  5.972961  34.142551  8.636292  20.160595  30.627438   \n",
       "2005-01-06  17.193125  5.881657  34.305496  8.590302  20.963234  30.112633   \n",
       "2005-01-07  17.140959  5.977942  34.411770  8.513648  22.153666  30.132185   \n",
       "\n",
       "                SWKS  SYF        SYK        SYY         T        TAP  TDG  \\\n",
       "Date                                                                        \n",
       "2005-01-03  7.853062  NaN  39.510036  22.062370  5.056196  25.184740  NaN   \n",
       "2005-01-04  7.695831  NaN  40.034088  21.701178  5.002849  24.676846  NaN   \n",
       "2005-01-05  7.678362  NaN  40.083237  21.730902  5.026556  24.062000  NaN   \n",
       "2005-01-06  7.634683  NaN  39.837582  21.689280  5.054221  24.302599  NaN   \n",
       "2005-01-07  7.556066  NaN  39.510036  21.594151  5.040154  24.122154  NaN   \n",
       "\n",
       "              TDY      TECH  TEL        TER        TFC        TFX        TGT  \\\n",
       "Date                                                                           \n",
       "2005-01-03  29.82  8.117376  NaN  15.433227  21.806458  39.362537  34.827820   \n",
       "2005-01-04  29.18  7.966858  NaN  14.501834  21.843039  39.044098  34.451302   \n",
       "2005-01-05  28.40  7.956261  NaN  14.306239  21.973679  39.020802  34.478207   \n",
       "2005-01-06  28.42  8.043176  NaN  14.129273  21.947546  39.176132  32.609047   \n",
       "2005-01-07  28.07  7.992299  NaN  14.436636  21.696711  38.943150  32.958691   \n",
       "\n",
       "                 TJX        TLT        TMO  TMUS        TPR  TRGP    TRMB  \\\n",
       "Date                                                                        \n",
       "2005-01-03  4.909898  50.318027  28.341032   NaN  19.198719   NaN  8.0825   \n",
       "2005-01-04  4.892115  49.790707  27.987720   NaN  18.763174   NaN  8.0300   \n",
       "2005-01-05  4.872356  50.057182  27.911337   NaN  18.780600   NaN  7.9625   \n",
       "2005-01-06  4.874333  50.091190  27.930428   NaN  19.167362   NaN  7.8200   \n",
       "2005-01-07  4.850622  50.204620  27.519833   NaN  19.285824   NaN  7.6600   \n",
       "\n",
       "                 TROW        TRV      TSCO  TSLA        TSN         TT  \\\n",
       "Date                                                                     \n",
       "2005-01-03  18.821436  23.950897  7.947328   NaN  13.860072  17.890514   \n",
       "2005-01-04  18.296421  23.815866  7.773532   NaN  13.867762  17.532124   \n",
       "2005-01-05  18.220104  23.777287  7.644797   NaN  13.713851  17.137417   \n",
       "2005-01-06  18.394098  23.886600  7.799276   NaN  13.521454  17.160110   \n",
       "2005-01-07  18.256742  23.777287  7.608322   NaN  13.598410  17.069378   \n",
       "\n",
       "                 TTWO        TXN        TXT   TYL  UAL  UBFUT        UDR  \\\n",
       "Date                                                                       \n",
       "2005-01-03  23.585209  16.367538  32.125858  8.19  NaN    NaN  10.704785   \n",
       "2005-01-04  22.598604  15.974930  31.450640  8.02  NaN    NaN  10.512852   \n",
       "2005-01-05  22.398617  15.494335  31.539484  7.86  NaN    NaN  10.159514   \n",
       "2005-01-06  21.931978  15.433409  31.157452  7.83  NaN    NaN  10.159514   \n",
       "2005-01-07  21.498672  15.514643  31.104143  7.77  NaN    NaN  10.089717   \n",
       "\n",
       "                  UHS  ULTA        UNH        UNP        UPS        URI  \\\n",
       "Date                                                                      \n",
       "2005-01-03  20.051275   NaN  35.431389  11.748457  50.628342  18.938057   \n",
       "2005-01-04  19.923693   NaN  35.067337  11.462759  49.985039  18.539360   \n",
       "2005-01-05  20.051275   NaN  35.190060  11.358233  49.883789  18.160599   \n",
       "2005-01-06  20.051275   NaN  35.967243  11.427916  49.830173  18.290176   \n",
       "2005-01-07  20.051275   NaN  35.680901  11.288555  49.734879  17.971220   \n",
       "\n",
       "                  USB  USD   V       VFC  VICI        VLO        VMC  \\\n",
       "Date                                                                   \n",
       "2005-01-03  17.829287  NaN NaN  7.837399   NaN  11.970934  41.826443   \n",
       "2005-01-04  17.743153  NaN NaN  7.771186   NaN  11.973716  41.354881   \n",
       "2005-01-05  17.835035  NaN NaN  7.666106   NaN  11.720732  41.213417   \n",
       "2005-01-06  17.794830  NaN NaN  7.676188   NaN  12.071020  41.331306   \n",
       "2005-01-07  17.484766  NaN NaN  7.684824   NaN  12.032095  41.543507   \n",
       "\n",
       "                  VNQ  VRSK       VRSN   VRTX        VTR       VTRS  \\\n",
       "Date                                                                  \n",
       "2005-01-03  25.454876   NaN  27.648361  10.24  13.074273  15.825217   \n",
       "2005-01-04  25.072300   NaN  26.722784  10.09  12.915008  15.491773   \n",
       "2005-01-05  24.238836   NaN  26.017990   9.90  12.451685  15.347581   \n",
       "2005-01-06  24.425566   NaN  25.967041  10.52  12.499954  15.482761   \n",
       "2005-01-07  24.370924   NaN  26.281227  10.49  12.461341  15.437696   \n",
       "\n",
       "                   VZ       WAB        WAT        WBA  WBD       WDC  \\\n",
       "Date                                                                   \n",
       "2005-01-03  14.901470  9.799141  45.770000  26.787544  NaN  8.622047   \n",
       "2005-01-04  14.750576  9.493651  45.000000  26.595150  NaN  8.405293   \n",
       "2005-01-05  14.728499  9.277457  45.330002  27.278444  NaN  8.212622   \n",
       "2005-01-06  14.696908  9.338558  45.700001  27.291714  NaN  8.140371   \n",
       "2005-01-07  14.644886  9.084764  45.669998  27.530521  NaN  8.108260   \n",
       "\n",
       "                 WEC       WELL        WFC        WHR         WM       WMB  \\\n",
       "Date                                                                         \n",
       "2005-01-03  9.738559  14.221395  18.636450  42.231106  17.647091  5.912993   \n",
       "2005-01-04  9.732780  14.141001  18.651503  41.503296  17.449883  5.863492   \n",
       "2005-01-05  9.663447  13.524678  18.672573  41.539989  17.306461  5.821611   \n",
       "2005-01-06  9.721224  13.551478  18.738796  42.078197  17.216822  5.901566   \n",
       "2005-01-07  9.735669  13.570619  18.714722  41.552238  17.133162  5.836842   \n",
       "\n",
       "                  WMT       WRB  WRK        WST        WTW         WY  \\\n",
       "Date                                                                    \n",
       "2005-01-03  36.303005  6.872738  NaN  10.520180  71.333054  13.131151   \n",
       "2005-01-04  36.214546  6.853625  NaN  10.603344  71.833092  12.929282   \n",
       "2005-01-05  36.262173  6.837454  NaN  10.603344  70.695076  12.984164   \n",
       "2005-01-06  36.779324  6.877146  NaN  10.590872  70.401955  13.037074   \n",
       "2005-01-07  36.738503  6.834516  NaN  10.561764  69.505348  13.240903   \n",
       "\n",
       "                 WYNN       XEL        XOM       XRAY  XTSLA  XYL        YUM  \\\n",
       "Date                                                                           \n",
       "2005-01-03  36.172791  9.113141  27.368698  24.653870    NaN  NaN  12.032602   \n",
       "2005-01-04  36.095535  8.976597  27.182922  24.454481    NaN  NaN  11.873264   \n",
       "2005-01-05  36.503883  8.875449  27.040861  24.166471    NaN  NaN  11.844993   \n",
       "2005-01-06  37.982800  8.860278  27.385073  24.281670    NaN  NaN  11.978628   \n",
       "2005-01-07  36.719097  8.809707  27.204771  24.095566    NaN  NaN  11.911808   \n",
       "\n",
       "                  ZBH       ZBRA       ZION  ZTS  \n",
       "Date                                              \n",
       "2005-01-03  70.087204  55.509998  50.133705  NaN  \n",
       "2005-01-04  70.060738  54.470001  49.449276  NaN  \n",
       "2005-01-05  69.513336  52.570000  49.270733  NaN  \n",
       "2005-01-06  70.316795  52.650002  49.553436  NaN  \n",
       "2005-01-07  70.193161  53.099998  48.348259  NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# \n",
    "stocks = pd.read_parquet(base_url + \"spy_close_adjusted.parquet\")\n",
    "stocks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a13a3a32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 4597 entries, 2005-01-03 to 2023-04-06\n",
      "Columns: 514 entries, A to ZTS\n",
      "dtypes: float64(514)\n",
      "memory usage: 18.1 MB\n"
     ]
    }
   ],
   "source": [
    "stocks.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "006edbea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FEC_EVENT</th>\n",
       "      <th>PAGE</th>\n",
       "      <th>CONTENT_CATEGORY</th>\n",
       "      <th>CONTENT_CATEGORY_TOP</th>\n",
       "      <th>CONTENT_CATEGORY_BOTTOM</th>\n",
       "      <th>SITE_ID</th>\n",
       "      <th>ON_SITE_SEARCH_TERM</th>\n",
       "      <th>USER_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18350981</th>\n",
       "      <td>2018-09-12 09:11:48</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7974880</th>\n",
       "      <td>2018-06-21 17:26:35</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12678188</th>\n",
       "      <td>2018-12-18 08:06:09</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5143671</th>\n",
       "      <td>2018-04-18 06:49:01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9400713</th>\n",
       "      <td>2018-04-07 14:44:46</td>\n",
       "      <td>60</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   FEC_EVENT  PAGE  CONTENT_CATEGORY  CONTENT_CATEGORY_TOP  \\\n",
       "18350981 2018-09-12 09:11:48    40                 1                     1   \n",
       "7974880  2018-06-21 17:26:35     2                 2                     2   \n",
       "12678188 2018-12-18 08:06:09    27                 2                     2   \n",
       "5143671  2018-04-18 06:49:01     2                 2                     2   \n",
       "9400713  2018-04-07 14:44:46    60                 2                     2   \n",
       "\n",
       "          CONTENT_CATEGORY_BOTTOM  SITE_ID  ON_SITE_SEARCH_TERM  USER_ID  \n",
       "18350981                        1        1                    1     5215  \n",
       "7974880                         2        2                    1     6323  \n",
       "12678188                        2        3                    1     6117  \n",
       "5143671                         2        2                    1      441  \n",
       "9400713                         2        3                    1     8844  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# \n",
    "pageviews = pd.read_parquet(base_url +  \"all_pageviews.parquet\")\n",
    "pageviews.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e9e13eb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5717588, 8)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pageviews.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "85583a1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pd.read_csv\n",
    "# pd.read_parquet\n",
    "# df.info\n",
    "# df.dtypes\n",
    "# df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e00217a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 25723 entries, 0 to 25722\n",
      "Data columns (total 24 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   Case Number             8702 non-null   object \n",
      " 1   Date                    6302 non-null   object \n",
      " 2   Year                    6300 non-null   float64\n",
      " 3   Type                    6298 non-null   object \n",
      " 4   Country                 6252 non-null   object \n",
      " 5   Area                    5847 non-null   object \n",
      " 6   Location                5762 non-null   object \n",
      " 7   Activity                5758 non-null   object \n",
      " 8   Name                    6092 non-null   object \n",
      " 9   Sex                     5737 non-null   object \n",
      " 10  Age                     3471 non-null   object \n",
      " 11  Injury                  6274 non-null   object \n",
      " 12  Fatal (Y/N)             5763 non-null   object \n",
      " 13  Time                    2948 non-null   object \n",
      " 14  Species                 3464 non-null   object \n",
      " 15  Investigator or Source  6285 non-null   object \n",
      " 16  pdf                     6302 non-null   object \n",
      " 17  href formula            6301 non-null   object \n",
      " 18  href                    6302 non-null   object \n",
      " 19  Case Number.1           6302 non-null   object \n",
      " 20  Case Number.2           6302 non-null   object \n",
      " 21  original order          6309 non-null   float64\n",
      " 22  Unnamed: 22             1 non-null      object \n",
      " 23  Unnamed: 23             2 non-null      object \n",
      "dtypes: float64(2), object(22)\n",
      "memory usage: 4.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df_sharks.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cb64f367",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Case Number                object\n",
       "Date                       object\n",
       "Year                      float64\n",
       "Type                       object\n",
       "Country                    object\n",
       "Area                       object\n",
       "Location                   object\n",
       "Activity                   object\n",
       "Name                       object\n",
       "Sex                        object\n",
       "Age                        object\n",
       "Injury                     object\n",
       "Fatal (Y/N)                object\n",
       "Time                       object\n",
       "Species                    object\n",
       "Investigator or Source     object\n",
       "pdf                        object\n",
       "href formula               object\n",
       "href                       object\n",
       "Case Number.1              object\n",
       "Case Number.2              object\n",
       "original order            float64\n",
       "Unnamed: 22                object\n",
       "Unnamed: 23                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "956e8a3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>original order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6299.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25718</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25719</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25720</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25721</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25722</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25723 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Year  original order\n",
       "0      2018.0          6303.0\n",
       "1      2018.0          6302.0\n",
       "2      2018.0          6301.0\n",
       "3      2018.0          6300.0\n",
       "4      2018.0          6299.0\n",
       "...       ...             ...\n",
       "25718     NaN             NaN\n",
       "25719     NaN             NaN\n",
       "25720     NaN             NaN\n",
       "25721     NaN             NaN\n",
       "25722     NaN             NaN\n",
       "\n",
       "[25723 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.select_dtypes(\"float64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba449937",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3c7b5584",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading File: /mnt/yt_videos/polars/airlines-full/2007.csv\n",
      "Reading File: /mnt/yt_videos/polars/airlines-full/2008.csv\n"
     ]
    }
   ],
   "source": [
    "# Read Multiple Files and concatenate results\n",
    "# https://pandas.pydata.org/docs/reference/api/pandas.concat.html\n",
    "files = [\"/mnt/yt_videos/polars/airlines-full/2007.csv\", \n",
    "         \"/mnt/yt_videos/polars/airlines-full/2008.csv\"]\n",
    "\n",
    "data = []\n",
    "for file in files:\n",
    "    print(f\"Reading File: {file}\")\n",
    "    df = pd.read_csv(file, engine='pyarrow')\n",
    "    data.append(df)\n",
    "    del df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1158215c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_airlines = pd.concat(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e8dcf3ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9842432, 29)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "934eeacf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1232.0</td>\n",
       "      <td>1225</td>\n",
       "      <td>1341.0</td>\n",
       "      <td>1340</td>\n",
       "      <td>WN</td>\n",
       "      <td>2891</td>\n",
       "      <td>N351</td>\n",
       "      <td>69.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>ONT</td>\n",
       "      <td>389</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>1905</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>2035</td>\n",
       "      <td>WN</td>\n",
       "      <td>462</td>\n",
       "      <td>N370</td>\n",
       "      <td>85.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2206.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>2300</td>\n",
       "      <td>WN</td>\n",
       "      <td>1229</td>\n",
       "      <td>N685</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>1200</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>1330</td>\n",
       "      <td>WN</td>\n",
       "      <td>1355</td>\n",
       "      <td>N364</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>831.0</td>\n",
       "      <td>830</td>\n",
       "      <td>957.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>2278</td>\n",
       "      <td>N480</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "0  2007      1           1          1   1232.0        1225   1341.0   \n",
       "1  2007      1           1          1   1918.0        1905   2043.0   \n",
       "2  2007      1           1          1   2206.0        2130   2334.0   \n",
       "3  2007      1           1          1   1230.0        1200   1356.0   \n",
       "4  2007      1           1          1    831.0         830    957.0   \n",
       "\n",
       "   CRSArrTime UniqueCarrier  FlightNum TailNum  ActualElapsedTime  \\\n",
       "0        1340            WN       2891    N351               69.0   \n",
       "1        2035            WN        462    N370               85.0   \n",
       "2        2300            WN       1229    N685               88.0   \n",
       "3        1330            WN       1355    N364               86.0   \n",
       "4        1000            WN       2278    N480               86.0   \n",
       "\n",
       "   CRSElapsedTime  AirTime  ArrDelay  DepDelay Origin Dest  Distance  TaxiIn  \\\n",
       "0            75.0     54.0       1.0       7.0    SMF  ONT       389     4.0   \n",
       "1            90.0     74.0       8.0      13.0    SMF  PDX       479     5.0   \n",
       "2            90.0     73.0      34.0      36.0    SMF  PDX       479     6.0   \n",
       "3            90.0     75.0      26.0      30.0    SMF  PDX       479     3.0   \n",
       "4            90.0     74.0      -3.0       1.0    SMF  PDX       479     3.0   \n",
       "\n",
       "   TaxiOut  Cancelled CancellationCode  Diverted  CarrierDelay  WeatherDelay  \\\n",
       "0     11.0          0                          0           0.0           0.0   \n",
       "1      6.0          0                          0           0.0           0.0   \n",
       "2      9.0          0                          0           3.0           0.0   \n",
       "3      8.0          0                          0          23.0           0.0   \n",
       "4      9.0          0                          0           0.0           0.0   \n",
       "\n",
       "   NASDelay  SecurityDelay  LateAircraftDelay  \n",
       "0       0.0            0.0                0.0  \n",
       "1       0.0            0.0                0.0  \n",
       "2       0.0            0.0               31.0  \n",
       "3       0.0            0.0                3.0  \n",
       "4       0.0            0.0                0.0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c14252a",
   "metadata": {},
   "source": [
    "# 2. Select Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d32a22b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389212</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389213</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389214</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389215</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389216</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9842432 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Year  Month  DayofMonth\n",
       "0        2007      1           1\n",
       "1        2007      1           1\n",
       "2        2007      1           1\n",
       "3        2007      1           1\n",
       "4        2007      1           1\n",
       "...       ...    ...         ...\n",
       "2389212  2008      4          17\n",
       "2389213  2008      4          17\n",
       "2389214  2008      4          17\n",
       "2389215  2008      4          17\n",
       "2389216  2008      4          17\n",
       "\n",
       "[9842432 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pass a list\n",
    "keep_cols = ['Year', \"Month\", \"DayofMonth\"]\n",
    "\n",
    "df_airlines[keep_cols]\n",
    "#df_airlines[['Year', \"Month\", \"DayofMonth\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7ac7de8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1232.0</td>\n",
       "      <td>1225</td>\n",
       "      <td>1341.0</td>\n",
       "      <td>1340</td>\n",
       "      <td>WN</td>\n",
       "      <td>2891</td>\n",
       "      <td>N351</td>\n",
       "      <td>69.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>ONT</td>\n",
       "      <td>389</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>1905</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>2035</td>\n",
       "      <td>WN</td>\n",
       "      <td>462</td>\n",
       "      <td>N370</td>\n",
       "      <td>85.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2206.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>2300</td>\n",
       "      <td>WN</td>\n",
       "      <td>1229</td>\n",
       "      <td>N685</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>1200</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>1330</td>\n",
       "      <td>WN</td>\n",
       "      <td>1355</td>\n",
       "      <td>N364</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>831.0</td>\n",
       "      <td>830</td>\n",
       "      <td>957.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>2278</td>\n",
       "      <td>N480</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "0  2007      1           1          1   1232.0        1225   1341.0   \n",
       "1  2007      1           1          1   1918.0        1905   2043.0   \n",
       "2  2007      1           1          1   2206.0        2130   2334.0   \n",
       "3  2007      1           1          1   1230.0        1200   1356.0   \n",
       "4  2007      1           1          1    831.0         830    957.0   \n",
       "\n",
       "   CRSArrTime UniqueCarrier  FlightNum TailNum  ActualElapsedTime  \\\n",
       "0        1340            WN       2891    N351               69.0   \n",
       "1        2035            WN        462    N370               85.0   \n",
       "2        2300            WN       1229    N685               88.0   \n",
       "3        1330            WN       1355    N364               86.0   \n",
       "4        1000            WN       2278    N480               86.0   \n",
       "\n",
       "   CRSElapsedTime  AirTime  ArrDelay  DepDelay Origin Dest  Distance  TaxiIn  \\\n",
       "0            75.0     54.0       1.0       7.0    SMF  ONT       389     4.0   \n",
       "1            90.0     74.0       8.0      13.0    SMF  PDX       479     5.0   \n",
       "2            90.0     73.0      34.0      36.0    SMF  PDX       479     6.0   \n",
       "3            90.0     75.0      26.0      30.0    SMF  PDX       479     3.0   \n",
       "4            90.0     74.0      -3.0       1.0    SMF  PDX       479     3.0   \n",
       "\n",
       "   TaxiOut  Cancelled CancellationCode  Diverted  CarrierDelay  WeatherDelay  \\\n",
       "0     11.0          0                          0           0.0           0.0   \n",
       "1      6.0          0                          0           0.0           0.0   \n",
       "2      9.0          0                          0           3.0           0.0   \n",
       "3      8.0          0                          0          23.0           0.0   \n",
       "4      9.0          0                          0           0.0           0.0   \n",
       "\n",
       "   NASDelay  SecurityDelay  LateAircraftDelay  \n",
       "0       0.0            0.0                0.0  \n",
       "1       0.0            0.0                0.0  \n",
       "2       0.0            0.0               31.0  \n",
       "3       0.0            0.0                3.0  \n",
       "4       0.0            0.0                0.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5aa8ece3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  DayofMonth\n",
       "0  2007      1           1\n",
       "1  2007      1           1\n",
       "2  2007      1           1\n",
       "3  2007      1           1\n",
       "4  2007      1           1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.loc[df_airlines.Year == 2007, keep_cols].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d8ee89ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7453210</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7453211</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7453212</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7453213</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7453214</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7453215 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Year  Month  DayofMonth\n",
       "0        2007      1           1\n",
       "1        2007      1           1\n",
       "2        2007      1           1\n",
       "3        2007      1           1\n",
       "4        2007      1           1\n",
       "...       ...    ...         ...\n",
       "7453210  2007     12          15\n",
       "7453211  2007     12          15\n",
       "7453212  2007     12          15\n",
       "7453213  2007     12          15\n",
       "7453214  2007     12          15\n",
       "\n",
       "[7453215 rows x 3 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_airlines\n",
    " [keep_cols]\n",
    " .loc[df_airlines.Year == 2007, :] \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5b836e4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2a69fb3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd4f38a8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b62bbc75",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed29dff8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d164871",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7fd584d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d113a3e7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a476d388",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e797ff2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9947eeac",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02f37697",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3473b16e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ce5756d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9625e9d4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56128f9c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cacbcd59",
   "metadata": {},
   "source": [
    "# 3. Filter Rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3fa18f22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Case Number                object\n",
       "Date                       object\n",
       "Year                      float64\n",
       "Type                       object\n",
       "Country                    object\n",
       "Area                       object\n",
       "Location                   object\n",
       "Activity                   object\n",
       "Name                       object\n",
       "Sex                        object\n",
       "Age                        object\n",
       "Injury                     object\n",
       "Fatal (Y/N)                object\n",
       "Time                       object\n",
       "Species                    object\n",
       "Investigator or Source     object\n",
       "pdf                        object\n",
       "href formula               object\n",
       "href                       object\n",
       "Case Number.1              object\n",
       "Case Number.2              object\n",
       "original order            float64\n",
       "Unnamed: 22                object\n",
       "Unnamed: 23                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8c18f719",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sharks.columns = df_sharks.columns.str.strip().str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "73f63aad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>09-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Invalid</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Habush, Oahu</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>John Denges</td>\n",
       "      <td>M</td>\n",
       "      <td>48</td>\n",
       "      <td>Injury to left lower leg from surfboard skeg</td>\n",
       "      <td>N</td>\n",
       "      <td>07h45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.09-Denges.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>6301.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>08-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Arrawarra Headland</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>male</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Minor injury to lower leg</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 m shark</td>\n",
       "      <td>B. Myatt, GSAF</td>\n",
       "      <td>2018.06.08-Arrawarra.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>6300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>04-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>MEXICO</td>\n",
       "      <td>Colima</td>\n",
       "      <td>La Ticla</td>\n",
       "      <td>Free diving</td>\n",
       "      <td>Gustavo Ramos</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lacerations to leg &amp; hand shark PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tiger shark, 3m</td>\n",
       "      <td>A .Kipper</td>\n",
       "      <td>2018.06.04-Ramos.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>6299.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type    country             area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating        USA       California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked        USA          Georgia   \n",
       "2  2018.06.09  09-Jun-2018  2018.0     Invalid        USA           Hawaii   \n",
       "3  2018.06.08  08-Jun-2018  2018.0  Unprovoked  AUSTRALIA  New South Wales   \n",
       "4  2018.06.04  04-Jun-2018  2018.0    Provoked     MEXICO           Colima   \n",
       "\n",
       "                         location     activity             name sex  age  \\\n",
       "0     Oceanside, San Diego County     Paddling      Julie Wolfe   F   57   \n",
       "1  St. Simon Island, Glynn County     Standing  Adyson McNeely    F   11   \n",
       "2                    Habush, Oahu      Surfing      John Denges   M   48   \n",
       "3              Arrawarra Headland      Surfing             male   M  NaN   \n",
       "4                        La Ticla  Free diving   Gustavo Ramos    M  NaN   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "2       Injury to left lower leg from surfboard skeg           N   \n",
       "3                          Minor injury to lower leg           N   \n",
       "4  Lacerations to leg & hand shark PROVOKED INCIDENT           N   \n",
       "\n",
       "            time          species          investigator or source  \\\n",
       "0          18h00      White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00              NaN  K.McMurray, TrackingSharks.com   \n",
       "2          07h45              NaN  K.McMurray, TrackingSharks.com   \n",
       "3            NaN        2 m shark                  B. Myatt, GSAF   \n",
       "4            NaN  Tiger shark, 3m                       A .Kipper   \n",
       "\n",
       "                        pdf  \\\n",
       "0      2018.06.25-Wolfe.pdf   \n",
       "1    2018.06.18-McNeely.pdf   \n",
       "2     2018.06.09-Denges.pdf   \n",
       "3  2018.06.08-Arrawarra.pdf   \n",
       "4      2018.06.04-Ramos.pdf   \n",
       "\n",
       "                                        href formula  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.09   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.08   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.04   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  \n",
       "2    2018.06.09          6301.0         NaN         NaN  \n",
       "3    2018.06.08          6300.0         NaN         NaN  \n",
       "4    2018.06.04          6299.0         NaN         NaN  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fa02dec3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type country        area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating     USA  California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked     USA     Georgia   \n",
       "\n",
       "                         location  activity             name sex age  \\\n",
       "0     Oceanside, San Diego County  Paddling      Julie Wolfe   F  57   \n",
       "1  St. Simon Island, Glynn County  Standing  Adyson McNeely    F  11   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "\n",
       "            time      species          investigator or source  \\\n",
       "0          18h00  White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00          NaN  K.McMurray, TrackingSharks.com   \n",
       "\n",
       "                      pdf                                       href formula  \\\n",
       "0    2018.06.25-Wolfe.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  2018.06.18-McNeely.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Boolean Indexing\n",
    "df_sharks[df_sharks.sex == 'F'].head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "52a3b176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2017.12.31</td>\n",
       "      <td>31-Dec-2017</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Hultin's Beach, Oahu</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>Marjorie Mariano</td>\n",
       "      <td>F</td>\n",
       "      <td>54</td>\n",
       "      <td>Severe lacerations to left thigh &amp; knee</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>Tiger shark</td>\n",
       "      <td>J. Howard, Surfling Now, 1/2/2018</td>\n",
       "      <td>2017.12.31-Mariano.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2017.12.31</td>\n",
       "      <td>2017.12.31</td>\n",
       "      <td>6250.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2017.12.30</td>\n",
       "      <td>30-Dec-2017</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Drakes Estero, Point Reyes, Marin County</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>Natalie Jones</td>\n",
       "      <td>F</td>\n",
       "      <td>35</td>\n",
       "      <td>Foot bitten</td>\n",
       "      <td>N</td>\n",
       "      <td>12h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R. Collier</td>\n",
       "      <td>2017.12.30.Jones.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2017.12.30</td>\n",
       "      <td>2017.12.30</td>\n",
       "      <td>6249.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2017.11.18</td>\n",
       "      <td>18-Nov-2017</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Floridana Beach, Brevard County</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>Kaia Anderson</td>\n",
       "      <td>F</td>\n",
       "      <td>14</td>\n",
       "      <td>Heel bitten</td>\n",
       "      <td>N</td>\n",
       "      <td>Late afternoon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Florida Today, 11/21/2017</td>\n",
       "      <td>2017.11.18-Anderson.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2017.11.18</td>\n",
       "      <td>2017.11.18</td>\n",
       "      <td>6242.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5973</th>\n",
       "      <td>1862.00.00.b</td>\n",
       "      <td>Circa 1862</td>\n",
       "      <td>1862.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Puna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A chiefess</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ankle bitten</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Captain W. Young</td>\n",
       "      <td>1862.00.00.b-Hawaii.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>1862.00.00.b</td>\n",
       "      <td>1862.00.00.b</td>\n",
       "      <td>330.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6034</th>\n",
       "      <td>1849.06.08.a</td>\n",
       "      <td>08-Jun-1849</td>\n",
       "      <td>1849.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Pensacola, Escambia County</td>\n",
       "      <td>Bathing</td>\n",
       "      <td>Mrs. Cracton</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FATAL</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Adams Sentinel, 8/6/1849</td>\n",
       "      <td>1849.06.08.a-Cracton.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>1849.06.08.a</td>\n",
       "      <td>1849.06.08.a</td>\n",
       "      <td>269.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6200</th>\n",
       "      <td>ND-0123</td>\n",
       "      <td>Before 2009</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Florida</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shark tagging</td>\n",
       "      <td>Danniell Washington</td>\n",
       "      <td>F</td>\n",
       "      <td>21</td>\n",
       "      <td>Severe abrasion to forearm from captive shark ...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>Blacktip shark, 5'</td>\n",
       "      <td>Daniell Washington</td>\n",
       "      <td>ND-0123-Daniell-Washington.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND-0123</td>\n",
       "      <td>ND-0123</td>\n",
       "      <td>103.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6245</th>\n",
       "      <td>ND.0060</td>\n",
       "      <td>Before  19-Jun-1959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Capistrano, Orange County</td>\n",
       "      <td>NaN</td>\n",
       "      <td>girl</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Leg injured</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>White shark, 1,900-lb</td>\n",
       "      <td>B. Walton, Sun (San Bernardino), 6/19/1959</td>\n",
       "      <td>ND-0060-Capistrano.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND.0060</td>\n",
       "      <td>ND.0060</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6292</th>\n",
       "      <td>ND.0010</td>\n",
       "      <td>Circa 1862</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Puna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A \"chiefess\"</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ankle bitten</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Captain W. Young</td>\n",
       "      <td>ND-0010-Puna Hawaii.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND.0010</td>\n",
       "      <td>ND.0010</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>337 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       case number                 date    year        type country  \\\n",
       "0       2018.06.25          25-Jun-2018  2018.0     Boating     USA   \n",
       "1       2018.06.18          18-Jun-2018  2018.0  Unprovoked     USA   \n",
       "53      2017.12.31          31-Dec-2017  2017.0  Unprovoked     USA   \n",
       "54      2017.12.30          30-Dec-2017  2017.0  Unprovoked     USA   \n",
       "61      2017.11.18          18-Nov-2017  2017.0  Unprovoked     USA   \n",
       "...            ...                  ...     ...         ...     ...   \n",
       "5973  1862.00.00.b           Circa 1862  1862.0  Unprovoked     USA   \n",
       "6034  1849.06.08.a          08-Jun-1849  1849.0  Unprovoked     USA   \n",
       "6200       ND-0123          Before 2009     0.0  Unprovoked     USA   \n",
       "6245       ND.0060  Before  19-Jun-1959     0.0  Unprovoked     USA   \n",
       "6292       ND.0010           Circa 1862     0.0  Unprovoked     USA   \n",
       "\n",
       "            area                                  location       activity  \\\n",
       "0     California               Oceanside, San Diego County       Paddling   \n",
       "1        Georgia            St. Simon Island, Glynn County       Standing   \n",
       "53        Hawaii                      Hultin's Beach, Oahu        Surfing   \n",
       "54    California  Drakes Estero, Point Reyes, Marin County        Surfing   \n",
       "61       Florida           Floridana Beach, Brevard County        Surfing   \n",
       "...          ...                                       ...            ...   \n",
       "5973      Hawaii                                      Puna            NaN   \n",
       "6034     Florida                Pensacola, Escambia County        Bathing   \n",
       "6200     Florida                                       NaN  Shark tagging   \n",
       "6245  California                 Capistrano, Orange County            NaN   \n",
       "6292      Hawaii                                      Puna            NaN   \n",
       "\n",
       "                     name sex  age  \\\n",
       "0             Julie Wolfe   F   57   \n",
       "1         Adyson McNeely    F   11   \n",
       "53       Marjorie Mariano   F   54   \n",
       "54          Natalie Jones   F   35   \n",
       "61          Kaia Anderson   F   14   \n",
       "...                   ...  ..  ...   \n",
       "5973           A chiefess   F  NaN   \n",
       "6034         Mrs. Cracton   F  NaN   \n",
       "6200  Danniell Washington   F   21   \n",
       "6245                 girl   F  NaN   \n",
       "6292         A \"chiefess\"   F  NaN   \n",
       "\n",
       "                                                 injury fatal (y/n)  \\\n",
       "0     No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                            Minor injury to left thigh           N   \n",
       "53              Severe lacerations to left thigh & knee           N   \n",
       "54                                          Foot bitten           N   \n",
       "61                                          Heel bitten           N   \n",
       "...                                                 ...         ...   \n",
       "5973                                       Ankle bitten           N   \n",
       "6034                                              FATAL           Y   \n",
       "6200  Severe abrasion to forearm from captive shark ...           N   \n",
       "6245                                        Leg injured           N   \n",
       "6292                                       Ankle bitten           N   \n",
       "\n",
       "                time                 species  \\\n",
       "0              18h00             White shark   \n",
       "1      14h00  -15h00                     NaN   \n",
       "53             18h00             Tiger shark   \n",
       "54             12h00                     NaN   \n",
       "61    Late afternoon                     NaN   \n",
       "...              ...                     ...   \n",
       "5973             NaN                     NaN   \n",
       "6034             NaN                     NaN   \n",
       "6200           18h00      Blacktip shark, 5'   \n",
       "6245             NaN  White shark, 1,900-lb    \n",
       "6292             NaN                     NaN   \n",
       "\n",
       "                           investigator or source  \\\n",
       "0                                R. Collier, GSAF   \n",
       "1                  K.McMurray, TrackingSharks.com   \n",
       "53              J. Howard, Surfling Now, 1/2/2018   \n",
       "54                                     R. Collier   \n",
       "61                      Florida Today, 11/21/2017   \n",
       "...                                           ...   \n",
       "5973                             Captain W. Young   \n",
       "6034                     Adams Sentinel, 8/6/1849   \n",
       "6200                           Daniell Washington   \n",
       "6245  B. Walton, Sun (San Bernardino), 6/19/1959    \n",
       "6292                             Captain W. Young   \n",
       "\n",
       "                                 pdf  \\\n",
       "0               2018.06.25-Wolfe.pdf   \n",
       "1             2018.06.18-McNeely.pdf   \n",
       "53            2017.12.31-Mariano.pdf   \n",
       "54              2017.12.30.Jones.pdf   \n",
       "61           2017.11.18-Anderson.pdf   \n",
       "...                              ...   \n",
       "5973         1862.00.00.b-Hawaii.pdf   \n",
       "6034        1849.06.08.a-Cracton.pdf   \n",
       "6200  ND-0123-Daniell-Washington.pdf   \n",
       "6245          ND-0060-Capistrano.pdf   \n",
       "6292         ND-0010-Puna Hawaii.pdf   \n",
       "\n",
       "                                           href formula  \\\n",
       "0     http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1     http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "53    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "54    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "61    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "...                                                 ...   \n",
       "5973  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6034  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6200  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6245  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6292  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                   href case number.1  \\\n",
       "0     http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1     http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "53    http://sharkattackfile.net/spreadsheets/pdf_di...    2017.12.31   \n",
       "54    http://sharkattackfile.net/spreadsheets/pdf_di...    2017.12.30   \n",
       "61    http://sharkattackfile.net/spreadsheets/pdf_di...    2017.11.18   \n",
       "...                                                 ...           ...   \n",
       "5973  http://sharkattackfile.net/spreadsheets/pdf_di...  1862.00.00.b   \n",
       "6034  http://sharkattackfile.net/spreadsheets/pdf_di...  1849.06.08.a   \n",
       "6200  http://sharkattackfile.net/spreadsheets/pdf_di...       ND-0123   \n",
       "6245  http://sharkattackfile.net/spreadsheets/pdf_di...       ND.0060   \n",
       "6292  http://sharkattackfile.net/spreadsheets/pdf_di...       ND.0010   \n",
       "\n",
       "     case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0       2018.06.25          6303.0         NaN         NaN  \n",
       "1       2018.06.18          6302.0         NaN         NaN  \n",
       "53      2017.12.31          6250.0         NaN         NaN  \n",
       "54      2017.12.30          6249.0         NaN         NaN  \n",
       "61      2017.11.18          6242.0         NaN         NaN  \n",
       "...            ...             ...         ...         ...  \n",
       "5973  1862.00.00.b           330.0         NaN         NaN  \n",
       "6034  1849.06.08.a           269.0         NaN         NaN  \n",
       "6200       ND-0123           103.0         NaN         NaN  \n",
       "6245       ND.0060            58.0         NaN         NaN  \n",
       "6292       ND.0010            11.0         NaN         NaN  \n",
       "\n",
       "[337 rows x 24 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks[(df_sharks.sex == 'F') & (df_sharks.country == 'USA')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cc47f34a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_sharks.country.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c91ebfee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018.05.00</td>\n",
       "      <td>May 2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>Westerm Australia</td>\n",
       "      <td>Dugong Bay</td>\n",
       "      <td>Feeding sharks</td>\n",
       "      <td>Melisa Brunning</td>\n",
       "      <td>F</td>\n",
       "      <td>34</td>\n",
       "      <td>Shallow lacerations to finger PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tawny nurse shark, 2m</td>\n",
       "      <td>Perth Now, 6/30/2018</td>\n",
       "      <td>2018.05.00-Brunning.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.05.00</td>\n",
       "      <td>2018.05.00</td>\n",
       "      <td>6289.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2018.02.23</td>\n",
       "      <td>23-Feb-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Little Congwong Beach, La Perouse</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>Anna Shurapey</td>\n",
       "      <td>F</td>\n",
       "      <td>55</td>\n",
       "      <td>Laceratons to right leg &amp; foot</td>\n",
       "      <td>N</td>\n",
       "      <td>19h00, Dusk</td>\n",
       "      <td>Juvenile white shark,  2.7 to 3.2 m</td>\n",
       "      <td>B. Myatt, GSAF</td>\n",
       "      <td>2018.02.23-Shurapey.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.02.23</td>\n",
       "      <td>2018.02.23</td>\n",
       "      <td>6263.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2018.02.14</td>\n",
       "      <td>14-Feb-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Invalid</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>Queensland</td>\n",
       "      <td>Mooloolaba Beach</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>Sharna Babd</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Collision / No injury, no attack</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>Possibly a wobbegong</td>\n",
       "      <td>Sunshine Coast Daily, 2/15/2018</td>\n",
       "      <td>2018.02.14-Babd.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.02.14</td>\n",
       "      <td>2018.02.14</td>\n",
       "      <td>6260.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6135</th>\n",
       "      <td>1791.00.00</td>\n",
       "      <td>1791</td>\n",
       "      <td>1791.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Port Jackson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female, an Australian aboriginal</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FATAL, \"bitten in two\"</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>G.P. Whitley;  D. Baldridge, p.162</td>\n",
       "      <td>1791.00.00-aboriginal woman.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>1791.00.00</td>\n",
       "      <td>1791.00.00</td>\n",
       "      <td>168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6189</th>\n",
       "      <td>ND-0139</td>\n",
       "      <td>1880-1899</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>Queensland</td>\n",
       "      <td>Boonooroo</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lassie</td>\n",
       "      <td>F</td>\n",
       "      <td>15</td>\n",
       "      <td>Foot severed</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Courier Mail, 6/30/1951</td>\n",
       "      <td>ND-0139-Lassie.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND-0139</td>\n",
       "      <td>ND-0139</td>\n",
       "      <td>114.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6200</th>\n",
       "      <td>ND-0123</td>\n",
       "      <td>Before 2009</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Florida</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shark tagging</td>\n",
       "      <td>Danniell Washington</td>\n",
       "      <td>F</td>\n",
       "      <td>21</td>\n",
       "      <td>Severe abrasion to forearm from captive shark ...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>Blacktip shark, 5'</td>\n",
       "      <td>Daniell Washington</td>\n",
       "      <td>ND-0123-Daniell-Washington.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND-0123</td>\n",
       "      <td>ND-0123</td>\n",
       "      <td>103.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6245</th>\n",
       "      <td>ND.0060</td>\n",
       "      <td>Before  19-Jun-1959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Capistrano, Orange County</td>\n",
       "      <td>NaN</td>\n",
       "      <td>girl</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Leg injured</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>White shark, 1,900-lb</td>\n",
       "      <td>B. Walton, Sun (San Bernardino), 6/19/1959</td>\n",
       "      <td>ND-0060-Capistrano.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND.0060</td>\n",
       "      <td>ND.0060</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6292</th>\n",
       "      <td>ND.0010</td>\n",
       "      <td>Circa 1862</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Puna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A \"chiefess\"</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ankle bitten</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Captain W. Young</td>\n",
       "      <td>ND-0010-Puna Hawaii.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>ND.0010</td>\n",
       "      <td>ND.0010</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>425 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     case number                 date    year        type    country  \\\n",
       "0     2018.06.25          25-Jun-2018  2018.0     Boating        USA   \n",
       "1     2018.06.18          18-Jun-2018  2018.0  Unprovoked        USA   \n",
       "14    2018.05.00             May 2018  2018.0    Provoked  AUSTRALIA   \n",
       "40    2018.02.23          23-Feb-2018  2018.0  Unprovoked  AUSTRALIA   \n",
       "43    2018.02.14          14-Feb-2018  2018.0     Invalid  AUSTRALIA   \n",
       "...          ...                  ...     ...         ...        ...   \n",
       "6135  1791.00.00                 1791  1791.0  Unprovoked  AUSTRALIA   \n",
       "6189     ND-0139            1880-1899     0.0  Unprovoked  AUSTRALIA   \n",
       "6200     ND-0123          Before 2009     0.0  Unprovoked        USA   \n",
       "6245     ND.0060  Before  19-Jun-1959     0.0  Unprovoked        USA   \n",
       "6292     ND.0010           Circa 1862     0.0  Unprovoked        USA   \n",
       "\n",
       "                   area                            location        activity  \\\n",
       "0            California         Oceanside, San Diego County        Paddling   \n",
       "1               Georgia      St. Simon Island, Glynn County        Standing   \n",
       "14    Westerm Australia                          Dugong Bay  Feeding sharks   \n",
       "40      New South Wales  Little Congwong Beach, La Perouse         Swimming   \n",
       "43           Queensland                    Mooloolaba Beach        Swimming   \n",
       "...                 ...                                 ...             ...   \n",
       "6135    New South Wales                        Port Jackson             NaN   \n",
       "6189         Queensland                           Boonooroo             NaN   \n",
       "6200            Florida                                 NaN   Shark tagging   \n",
       "6245         California           Capistrano, Orange County             NaN   \n",
       "6292             Hawaii                                Puna             NaN   \n",
       "\n",
       "                                  name sex  age  \\\n",
       "0                          Julie Wolfe   F   57   \n",
       "1                      Adyson McNeely    F   11   \n",
       "14                     Melisa Brunning   F   34   \n",
       "40                      Anna Shurapey    F   55   \n",
       "43                         Sharna Babd   F  NaN   \n",
       "...                                ...  ..  ...   \n",
       "6135  female, an Australian aboriginal   F  NaN   \n",
       "6189                            Lassie   F   15   \n",
       "6200               Danniell Washington   F   21   \n",
       "6245                              girl   F  NaN   \n",
       "6292                      A \"chiefess\"   F  NaN   \n",
       "\n",
       "                                                 injury fatal (y/n)  \\\n",
       "0     No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                            Minor injury to left thigh           N   \n",
       "14      Shallow lacerations to finger PROVOKED INCIDENT           N   \n",
       "40                       Laceratons to right leg & foot           N   \n",
       "43                     Collision / No injury, no attack           N   \n",
       "...                                                 ...         ...   \n",
       "6135                             FATAL, \"bitten in two\"           Y   \n",
       "6189                                       Foot severed           N   \n",
       "6200  Severe abrasion to forearm from captive shark ...           N   \n",
       "6245                                        Leg injured           N   \n",
       "6292                                       Ankle bitten           N   \n",
       "\n",
       "               time                              species  \\\n",
       "0             18h00                          White shark   \n",
       "1     14h00  -15h00                                  NaN   \n",
       "14              NaN                Tawny nurse shark, 2m   \n",
       "40      19h00, Dusk  Juvenile white shark,  2.7 to 3.2 m   \n",
       "43            18h00                 Possibly a wobbegong   \n",
       "...             ...                                  ...   \n",
       "6135            NaN                                  NaN   \n",
       "6189            NaN                                  NaN   \n",
       "6200          18h00                   Blacktip shark, 5'   \n",
       "6245            NaN               White shark, 1,900-lb    \n",
       "6292            NaN                                  NaN   \n",
       "\n",
       "                           investigator or source  \\\n",
       "0                                R. Collier, GSAF   \n",
       "1                  K.McMurray, TrackingSharks.com   \n",
       "14                           Perth Now, 6/30/2018   \n",
       "40                                 B. Myatt, GSAF   \n",
       "43                Sunshine Coast Daily, 2/15/2018   \n",
       "...                                           ...   \n",
       "6135           G.P. Whitley;  D. Baldridge, p.162   \n",
       "6189                      Courier Mail, 6/30/1951   \n",
       "6200                           Daniell Washington   \n",
       "6245  B. Walton, Sun (San Bernardino), 6/19/1959    \n",
       "6292                             Captain W. Young   \n",
       "\n",
       "                                  pdf  \\\n",
       "0                2018.06.25-Wolfe.pdf   \n",
       "1              2018.06.18-McNeely.pdf   \n",
       "14            2018.05.00-Brunning.pdf   \n",
       "40            2018.02.23-Shurapey.pdf   \n",
       "43                2018.02.14-Babd.pdf   \n",
       "...                               ...   \n",
       "6135  1791.00.00-aboriginal woman.pdf   \n",
       "6189               ND-0139-Lassie.pdf   \n",
       "6200   ND-0123-Daniell-Washington.pdf   \n",
       "6245           ND-0060-Capistrano.pdf   \n",
       "6292          ND-0010-Puna Hawaii.pdf   \n",
       "\n",
       "                                           href formula  \\\n",
       "0     http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1     http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "14    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "40    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "43    http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "...                                                 ...   \n",
       "6135  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6189  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6200  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6245  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "6292  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                   href case number.1  \\\n",
       "0     http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1     http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "14    http://sharkattackfile.net/spreadsheets/pdf_di...    2018.05.00   \n",
       "40    http://sharkattackfile.net/spreadsheets/pdf_di...    2018.02.23   \n",
       "43    http://sharkattackfile.net/spreadsheets/pdf_di...    2018.02.14   \n",
       "...                                                 ...           ...   \n",
       "6135  http://sharkattackfile.net/spreadsheets/pdf_di...    1791.00.00   \n",
       "6189  http://sharkattackfile.net/spreadsheets/pdf_di...       ND-0139   \n",
       "6200  http://sharkattackfile.net/spreadsheets/pdf_di...       ND-0123   \n",
       "6245  http://sharkattackfile.net/spreadsheets/pdf_di...       ND.0060   \n",
       "6292  http://sharkattackfile.net/spreadsheets/pdf_di...       ND.0010   \n",
       "\n",
       "     case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0       2018.06.25          6303.0         NaN         NaN  \n",
       "1       2018.06.18          6302.0         NaN         NaN  \n",
       "14      2018.05.00          6289.0         NaN         NaN  \n",
       "40      2018.02.23          6263.0         NaN         NaN  \n",
       "43      2018.02.14          6260.0         NaN         NaN  \n",
       "...            ...             ...         ...         ...  \n",
       "6135    1791.00.00           168.0         NaN         NaN  \n",
       "6189       ND-0139           114.0         NaN         NaN  \n",
       "6200       ND-0123           103.0         NaN         NaN  \n",
       "6245       ND.0060            58.0         NaN         NaN  \n",
       "6292       ND.0010            11.0         NaN         NaN  \n",
       "\n",
       "[425 rows x 24 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Boolean Indexing with df.query\n",
    "keep_countries = ['USA', 'AUSTRALIA']\n",
    "\n",
    "(df_sharks\n",
    " .query(\"sex == 'F' & country == @keep_countries\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "026c54a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>09-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Invalid</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Habush, Oahu</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>John Denges</td>\n",
       "      <td>M</td>\n",
       "      <td>48</td>\n",
       "      <td>Injury to left lower leg from surfboard skeg</td>\n",
       "      <td>N</td>\n",
       "      <td>07h45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.09-Denges.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>6301.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>08-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Arrawarra Headland</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>male</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Minor injury to lower leg</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 m shark</td>\n",
       "      <td>B. Myatt, GSAF</td>\n",
       "      <td>2018.06.08-Arrawarra.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>2018.06.08</td>\n",
       "      <td>6300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>04-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>MEXICO</td>\n",
       "      <td>Colima</td>\n",
       "      <td>La Ticla</td>\n",
       "      <td>Free diving</td>\n",
       "      <td>Gustavo Ramos</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lacerations to leg &amp; hand shark PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tiger shark, 3m</td>\n",
       "      <td>A .Kipper</td>\n",
       "      <td>2018.06.04-Ramos.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>2018.06.04</td>\n",
       "      <td>6299.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type    country             area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating        USA       California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked        USA          Georgia   \n",
       "2  2018.06.09  09-Jun-2018  2018.0     Invalid        USA           Hawaii   \n",
       "3  2018.06.08  08-Jun-2018  2018.0  Unprovoked  AUSTRALIA  New South Wales   \n",
       "4  2018.06.04  04-Jun-2018  2018.0    Provoked     MEXICO           Colima   \n",
       "\n",
       "                         location     activity             name sex  age  \\\n",
       "0     Oceanside, San Diego County     Paddling      Julie Wolfe   F   57   \n",
       "1  St. Simon Island, Glynn County     Standing  Adyson McNeely    F   11   \n",
       "2                    Habush, Oahu      Surfing      John Denges   M   48   \n",
       "3              Arrawarra Headland      Surfing             male   M  NaN   \n",
       "4                        La Ticla  Free diving   Gustavo Ramos    M  NaN   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "2       Injury to left lower leg from surfboard skeg           N   \n",
       "3                          Minor injury to lower leg           N   \n",
       "4  Lacerations to leg & hand shark PROVOKED INCIDENT           N   \n",
       "\n",
       "            time          species          investigator or source  \\\n",
       "0          18h00      White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00              NaN  K.McMurray, TrackingSharks.com   \n",
       "2          07h45              NaN  K.McMurray, TrackingSharks.com   \n",
       "3            NaN        2 m shark                  B. Myatt, GSAF   \n",
       "4            NaN  Tiger shark, 3m                       A .Kipper   \n",
       "\n",
       "                        pdf  \\\n",
       "0      2018.06.25-Wolfe.pdf   \n",
       "1    2018.06.18-McNeely.pdf   \n",
       "2     2018.06.09-Denges.pdf   \n",
       "3  2018.06.08-Arrawarra.pdf   \n",
       "4      2018.06.04-Ramos.pdf   \n",
       "\n",
       "                                        href formula  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.09   \n",
       "3  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.08   \n",
       "4  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.04   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  \n",
       "2    2018.06.09          6301.0         NaN         NaN  \n",
       "3    2018.06.08          6300.0         NaN         NaN  \n",
       "4    2018.06.04          6299.0         NaN         NaN  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1f65dc9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1673</th>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>18-May-2004</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>BAHAMAS</td>\n",
       "      <td>Abaco Islands</td>\n",
       "      <td>Green Turtle Cay</td>\n",
       "      <td>Free diving &amp; spearfishing</td>\n",
       "      <td>Wolfgang Leander</td>\n",
       "      <td>M</td>\n",
       "      <td>63</td>\n",
       "      <td>Left forearm bitten PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>15h00</td>\n",
       "      <td>1,5 m [5'] Caribbean reef shark (Carcharhinus ...</td>\n",
       "      <td>W. Leander, M. Levine, GSAF</td>\n",
       "      <td>2004.05.18-Leander.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>4630.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4288</th>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>Aug-1955</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>NORTH ATLANTIC OCEAN</td>\n",
       "      <td>Open sea</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treading water</td>\n",
       "      <td>Wolfgang Emrich</td>\n",
       "      <td>M</td>\n",
       "      <td>15</td>\n",
       "      <td>No injury</td>\n",
       "      <td>N</td>\n",
       "      <td>Early afternoon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H.D.Baldridge (1994), SAF Case #1489</td>\n",
       "      <td>1955.08.00.c-NV-Emrich.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       case number         date    year        type                country  \\\n",
       "1673    2004.05.18  18-May-2004  2004.0    Provoked                BAHAMAS   \n",
       "4288  1955.08.00.c     Aug-1955  1955.0  Unprovoked  NORTH ATLANTIC OCEAN    \n",
       "\n",
       "               area          location                    activity  \\\n",
       "1673  Abaco Islands  Green Turtle Cay  Free diving & spearfishing   \n",
       "4288       Open sea               NaN              Treading water   \n",
       "\n",
       "                  name sex age                                 injury  \\\n",
       "1673  Wolfgang Leander   M  63  Left forearm bitten PROVOKED INCIDENT   \n",
       "4288   Wolfgang Emrich   M  15                              No injury   \n",
       "\n",
       "     fatal (y/n)             time  \\\n",
       "1673           N            15h00   \n",
       "4288           N  Early afternoon   \n",
       "\n",
       "                                                species  \\\n",
       "1673  1,5 m [5'] Caribbean reef shark (Carcharhinus ...   \n",
       "4288                                                NaN   \n",
       "\n",
       "                    investigator or source                         pdf  \\\n",
       "1673           W. Leander, M. Levine, GSAF      2004.05.18-Leander.pdf   \n",
       "4288  H.D.Baldridge (1994), SAF Case #1489  1955.08.00.c-NV-Emrich.pdf   \n",
       "\n",
       "                                           href formula  \\\n",
       "1673  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "4288  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                   href case number.1  \\\n",
       "1673  http://sharkattackfile.net/spreadsheets/pdf_di...    2004.05.18   \n",
       "4288  http://sharkattackfile.net/spreadsheets/pdf_di...  1955.08.00.c   \n",
       "\n",
       "     case number.2  original order unnamed: 22 unnamed: 23  \n",
       "1673    2004.05.18          4630.0         NaN         NaN  \n",
       "4288  1955.08.00.c          2015.0         NaN         NaN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# str.contains\n",
    "# https://pandas.pydata.org/docs/reference/api/pandas.Series.str.contains.html\n",
    "\n",
    "df_sharks[df_sharks.name.str.contains(\"^wolf\", na=False, regex=True, case=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "529c152f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eac8f467",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9ed1066",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "418839c8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c003478",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15fd022f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97a42fa4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b70a128",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4bfa159c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae61fa28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cccbcd9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0f77d54",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1eafac08",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d7a9627",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "61a06031",
   "metadata": {},
   "source": [
    "# 4. Sort DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5dbc712a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# sort_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "936b8cc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1232.0</td>\n",
       "      <td>1225</td>\n",
       "      <td>1341.0</td>\n",
       "      <td>1340</td>\n",
       "      <td>WN</td>\n",
       "      <td>2891</td>\n",
       "      <td>N351</td>\n",
       "      <td>69.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>ONT</td>\n",
       "      <td>389</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>1905</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>2035</td>\n",
       "      <td>WN</td>\n",
       "      <td>462</td>\n",
       "      <td>N370</td>\n",
       "      <td>85.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2206.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>2300</td>\n",
       "      <td>WN</td>\n",
       "      <td>1229</td>\n",
       "      <td>N685</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>1200</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>1330</td>\n",
       "      <td>WN</td>\n",
       "      <td>1355</td>\n",
       "      <td>N364</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>831.0</td>\n",
       "      <td>830</td>\n",
       "      <td>957.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>2278</td>\n",
       "      <td>N480</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>SMF</td>\n",
       "      <td>PDX</td>\n",
       "      <td>479</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "0  2007      1           1          1   1232.0        1225   1341.0   \n",
       "1  2007      1           1          1   1918.0        1905   2043.0   \n",
       "2  2007      1           1          1   2206.0        2130   2334.0   \n",
       "3  2007      1           1          1   1230.0        1200   1356.0   \n",
       "4  2007      1           1          1    831.0         830    957.0   \n",
       "\n",
       "   CRSArrTime UniqueCarrier  FlightNum TailNum  ActualElapsedTime  \\\n",
       "0        1340            WN       2891    N351               69.0   \n",
       "1        2035            WN        462    N370               85.0   \n",
       "2        2300            WN       1229    N685               88.0   \n",
       "3        1330            WN       1355    N364               86.0   \n",
       "4        1000            WN       2278    N480               86.0   \n",
       "\n",
       "   CRSElapsedTime  AirTime  ArrDelay  DepDelay Origin Dest  Distance  TaxiIn  \\\n",
       "0            75.0     54.0       1.0       7.0    SMF  ONT       389     4.0   \n",
       "1            90.0     74.0       8.0      13.0    SMF  PDX       479     5.0   \n",
       "2            90.0     73.0      34.0      36.0    SMF  PDX       479     6.0   \n",
       "3            90.0     75.0      26.0      30.0    SMF  PDX       479     3.0   \n",
       "4            90.0     74.0      -3.0       1.0    SMF  PDX       479     3.0   \n",
       "\n",
       "   TaxiOut  Cancelled CancellationCode  Diverted  CarrierDelay  WeatherDelay  \\\n",
       "0     11.0          0                          0           0.0           0.0   \n",
       "1      6.0          0                          0           0.0           0.0   \n",
       "2      9.0          0                          0           3.0           0.0   \n",
       "3      8.0          0                          0          23.0           0.0   \n",
       "4      9.0          0                          0           0.0           0.0   \n",
       "\n",
       "   NASDelay  SecurityDelay  LateAircraftDelay  \n",
       "0       0.0            0.0                0.0  \n",
       "1       0.0            0.0                0.0  \n",
       "2       0.0            0.0               31.0  \n",
       "3       0.0            0.0                3.0  \n",
       "4       0.0            0.0                0.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a98f9f9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6061662</th>\n",
       "      <td>2007</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>820.0</td>\n",
       "      <td>1259</td>\n",
       "      <td>1109.0</td>\n",
       "      <td>1551</td>\n",
       "      <td>NW</td>\n",
       "      <td>891</td>\n",
       "      <td>N329NW</td>\n",
       "      <td>169.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>2598.0</td>\n",
       "      <td>2601.0</td>\n",
       "      <td>PBI</td>\n",
       "      <td>DTW</td>\n",
       "      <td>1087</td>\n",
       "      <td>3.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>2580.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018504</th>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1820</td>\n",
       "      <td>2256.0</td>\n",
       "      <td>555</td>\n",
       "      <td>NW</td>\n",
       "      <td>808</td>\n",
       "      <td>N817NW</td>\n",
       "      <td>459.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>437.0</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>2457.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>MSP</td>\n",
       "      <td>3972</td>\n",
       "      <td>6.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1455.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1002.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2235384</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>724.0</td>\n",
       "      <td>1417</td>\n",
       "      <td>858.0</td>\n",
       "      <td>1605</td>\n",
       "      <td>NW</td>\n",
       "      <td>1699</td>\n",
       "      <td>N3324L</td>\n",
       "      <td>154.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>2453.0</td>\n",
       "      <td>2467.0</td>\n",
       "      <td>CLT</td>\n",
       "      <td>MSP</td>\n",
       "      <td>930</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>2436.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7299451</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1536.0</td>\n",
       "      <td>700</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>805</td>\n",
       "      <td>9E</td>\n",
       "      <td>4714</td>\n",
       "      <td>87189E</td>\n",
       "      <td>51.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1942.0</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>ALO</td>\n",
       "      <td>MSP</td>\n",
       "      <td>166</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1942.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6060526</th>\n",
       "      <td>2007</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2351.0</td>\n",
       "      <td>1720</td>\n",
       "      <td>1244.0</td>\n",
       "      <td>556</td>\n",
       "      <td>NW</td>\n",
       "      <td>808</td>\n",
       "      <td>N816NW</td>\n",
       "      <td>473.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>431.0</td>\n",
       "      <td>1848.0</td>\n",
       "      <td>1831.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>MSP</td>\n",
       "      <td>3972</td>\n",
       "      <td>16.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1831.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6082457</th>\n",
       "      <td>2007</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>1256.0</td>\n",
       "      <td>800</td>\n",
       "      <td>1340.0</td>\n",
       "      <td>905</td>\n",
       "      <td>9E</td>\n",
       "      <td>3743</td>\n",
       "      <td>88009E</td>\n",
       "      <td>44.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1715.0</td>\n",
       "      <td>1736.0</td>\n",
       "      <td>FWA</td>\n",
       "      <td>DTW</td>\n",
       "      <td>128</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1715.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5439037</th>\n",
       "      <td>2007</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1309.0</td>\n",
       "      <td>900</td>\n",
       "      <td>2110.0</td>\n",
       "      <td>1725</td>\n",
       "      <td>NW</td>\n",
       "      <td>862</td>\n",
       "      <td>N528US</td>\n",
       "      <td>301.0</td>\n",
       "      <td>325.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>1665.0</td>\n",
       "      <td>1689.0</td>\n",
       "      <td>FAI</td>\n",
       "      <td>MSP</td>\n",
       "      <td>2466</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1665.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5440692</th>\n",
       "      <td>2007</td>\n",
       "      <td>9</td>\n",
       "      <td>28</td>\n",
       "      <td>5</td>\n",
       "      <td>1035.0</td>\n",
       "      <td>638</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>749</td>\n",
       "      <td>NW</td>\n",
       "      <td>966</td>\n",
       "      <td>N922RW</td>\n",
       "      <td>49.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1655.0</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>PIT</td>\n",
       "      <td>DTW</td>\n",
       "      <td>201</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1655.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7272228</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>1027.0</td>\n",
       "      <td>650</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>758</td>\n",
       "      <td>NW</td>\n",
       "      <td>189</td>\n",
       "      <td>N324US</td>\n",
       "      <td>63.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1652.0</td>\n",
       "      <td>1657.0</td>\n",
       "      <td>MSN</td>\n",
       "      <td>MSP</td>\n",
       "      <td>228</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1652.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1643023</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>5</td>\n",
       "      <td>1311.0</td>\n",
       "      <td>1124</td>\n",
       "      <td>1539.0</td>\n",
       "      <td>1335</td>\n",
       "      <td>NW</td>\n",
       "      <td>549</td>\n",
       "      <td>N364NW</td>\n",
       "      <td>208.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>1564.0</td>\n",
       "      <td>1547.0</td>\n",
       "      <td>JFK</td>\n",
       "      <td>MSP</td>\n",
       "      <td>1028</td>\n",
       "      <td>6.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>1324.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "6061662  2007     10           3          3    820.0        1259   1109.0   \n",
       "1018504  2008      2           3          7   1117.0        1820   2256.0   \n",
       "2235384  2008      4          10          4    724.0        1417    858.0   \n",
       "7299451  2007     12           1          6   1536.0         700   1627.0   \n",
       "6060526  2007     10           2          2   2351.0        1720   1244.0   \n",
       "6082457  2007     10          28          7   1256.0         800   1340.0   \n",
       "5439037  2007      9           1          6   1309.0         900   2110.0   \n",
       "5440692  2007      9          28          5   1035.0         638   1124.0   \n",
       "7272228  2007     12          23          7   1027.0         650   1130.0   \n",
       "1643023  2007      3          16          5   1311.0        1124   1539.0   \n",
       "\n",
       "         CRSArrTime UniqueCarrier  FlightNum TailNum  ActualElapsedTime  \\\n",
       "6061662        1551            NW        891  N329NW              169.0   \n",
       "1018504         555            NW        808  N817NW              459.0   \n",
       "2235384        1605            NW       1699  N3324L              154.0   \n",
       "7299451         805            9E       4714  87189E               51.0   \n",
       "6060526         556            NW        808  N816NW              473.0   \n",
       "6082457         905            9E       3743  88009E               44.0   \n",
       "5439037        1725            NW        862  N528US              301.0   \n",
       "5440692         749            NW        966  N922RW               49.0   \n",
       "7272228         758            NW        189  N324US               63.0   \n",
       "1643023        1335            NW        549  N364NW              208.0   \n",
       "\n",
       "         CRSElapsedTime  AirTime  ArrDelay  DepDelay Origin Dest  Distance  \\\n",
       "6061662           172.0    145.0    2598.0    2601.0    PBI  DTW      1087   \n",
       "1018504           455.0    437.0    2461.0    2457.0    HNL  MSP      3972   \n",
       "2235384           168.0    132.0    2453.0    2467.0    CLT  MSP       930   \n",
       "7299451            65.0     34.0    1942.0    1956.0    ALO  MSP       166   \n",
       "6060526           456.0    431.0    1848.0    1831.0    HNL  MSP      3972   \n",
       "6082457            65.0     27.0    1715.0    1736.0    FWA  DTW       128   \n",
       "5439037           325.0    281.0    1665.0    1689.0    FAI  MSP      2466   \n",
       "5440692            71.0     37.0    1655.0    1677.0    PIT  DTW       201   \n",
       "7272228            68.0     40.0    1652.0    1657.0    MSN  MSP       228   \n",
       "1643023           191.0    144.0    1564.0    1547.0    JFK  MSP      1028   \n",
       "\n",
       "         TaxiIn  TaxiOut  Cancelled CancellationCode  Diverted  CarrierDelay  \\\n",
       "6061662     3.0     21.0          0                          0        2580.0   \n",
       "1018504     6.0     16.0          0                          0        1455.0   \n",
       "2235384     8.0     14.0          0                          0        2436.0   \n",
       "7299451     5.0     12.0          0                          0        1942.0   \n",
       "6060526    16.0     26.0          0                          0        1831.0   \n",
       "6082457     7.0     10.0          0                          0        1715.0   \n",
       "5439037     6.0     14.0          0                          0        1665.0   \n",
       "5440692     4.0      8.0          0                          0        1655.0   \n",
       "7272228     9.0     14.0          0                          0        1652.0   \n",
       "1643023     6.0     58.0          0                          0           0.0   \n",
       "\n",
       "         WeatherDelay  NASDelay  SecurityDelay  LateAircraftDelay  \n",
       "6061662           0.0       0.0            0.0               18.0  \n",
       "1018504           0.0       4.0            0.0             1002.0  \n",
       "2235384           0.0       0.0            0.0               17.0  \n",
       "7299451           0.0       0.0            0.0                0.0  \n",
       "6060526           0.0      17.0            0.0                0.0  \n",
       "6082457           0.0       0.0            0.0                0.0  \n",
       "5439037           0.0       0.0            0.0                0.0  \n",
       "5440692           0.0       0.0            0.0                0.0  \n",
       "7272228           0.0       0.0            0.0                0.0  \n",
       "1643023         240.0    1324.0            0.0                0.0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.sort_values(\"ArrDelay\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "981bb8fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>ArrDelay</th>\n",
       "      <th>DepDelay</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6801165</th>\n",
       "      <td>2007</td>\n",
       "      <td>11</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>2236.0</td>\n",
       "      <td>2245</td>\n",
       "      <td>1304.0</td>\n",
       "      <td>1310</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N67052</td>\n",
       "      <td>568.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>533.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>13.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1166010</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>2233.0</td>\n",
       "      <td>2245</td>\n",
       "      <td>1327.0</td>\n",
       "      <td>1310</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N78060</td>\n",
       "      <td>594.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>564.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>13.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7423336</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "      <td>5</td>\n",
       "      <td>2234.0</td>\n",
       "      <td>2245</td>\n",
       "      <td>1259.0</td>\n",
       "      <td>1310</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N76055</td>\n",
       "      <td>565.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>-11.0</td>\n",
       "      <td>-11.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>6.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4325325</th>\n",
       "      <td>2007</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1425.0</td>\n",
       "      <td>1330</td>\n",
       "      <td>1840.0</td>\n",
       "      <td>1805</td>\n",
       "      <td>CO</td>\n",
       "      <td>15</td>\n",
       "      <td>N76054</td>\n",
       "      <td>615.0</td>\n",
       "      <td>635.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>HNL</td>\n",
       "      <td>4962</td>\n",
       "      <td>7.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7412671</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>1317.0</td>\n",
       "      <td>1320</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>1920</td>\n",
       "      <td>CO</td>\n",
       "      <td>15</td>\n",
       "      <td>N76064</td>\n",
       "      <td>670.0</td>\n",
       "      <td>660.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>HNL</td>\n",
       "      <td>4962</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1799647</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>6</td>\n",
       "      <td>1358.0</td>\n",
       "      <td>1320</td>\n",
       "      <td>1832.0</td>\n",
       "      <td>1820</td>\n",
       "      <td>CO</td>\n",
       "      <td>15</td>\n",
       "      <td>N67058</td>\n",
       "      <td>634.0</td>\n",
       "      <td>660.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>HNL</td>\n",
       "      <td>4962</td>\n",
       "      <td>4.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5577867</th>\n",
       "      <td>2007</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1327.0</td>\n",
       "      <td>1330</td>\n",
       "      <td>1751.0</td>\n",
       "      <td>1805</td>\n",
       "      <td>CO</td>\n",
       "      <td>15</td>\n",
       "      <td>N76055</td>\n",
       "      <td>624.0</td>\n",
       "      <td>635.0</td>\n",
       "      <td>589.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>EWR</td>\n",
       "      <td>HNL</td>\n",
       "      <td>4962</td>\n",
       "      <td>6.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1145252</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2240.0</td>\n",
       "      <td>2245</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>1310</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N59053</td>\n",
       "      <td>565.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4301281</th>\n",
       "      <td>2007</td>\n",
       "      <td>7</td>\n",
       "      <td>27</td>\n",
       "      <td>5</td>\n",
       "      <td>2112.0</td>\n",
       "      <td>2120</td>\n",
       "      <td>1249.0</td>\n",
       "      <td>1255</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N76055</td>\n",
       "      <td>577.0</td>\n",
       "      <td>575.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>9.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1799514</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>2241.0</td>\n",
       "      <td>2245</td>\n",
       "      <td>1309.0</td>\n",
       "      <td>1310</td>\n",
       "      <td>CO</td>\n",
       "      <td>14</td>\n",
       "      <td>N66051</td>\n",
       "      <td>568.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>538.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>HNL</td>\n",
       "      <td>EWR</td>\n",
       "      <td>4962</td>\n",
       "      <td>9.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "6801165  2007     11          26          1   2236.0        2245   1304.0   \n",
       "1166010  2007      2          13          2   2233.0        2245   1327.0   \n",
       "7423336  2007     12          28          5   2234.0        2245   1259.0   \n",
       "4325325  2007      7           6          5   1425.0        1330   1840.0   \n",
       "7412671  2007     12          31          1   1317.0        1320   1927.0   \n",
       "1799647  2007      3          17          6   1358.0        1320   1832.0   \n",
       "5577867  2007      9           2          7   1327.0        1330   1751.0   \n",
       "1145252  2007      2           3          6   2240.0        2245   1305.0   \n",
       "4301281  2007      7          27          5   2112.0        2120   1249.0   \n",
       "1799514  2007      3           8          4   2241.0        2245   1309.0   \n",
       "\n",
       "         CRSArrTime UniqueCarrier  FlightNum TailNum  ActualElapsedTime  \\\n",
       "6801165        1310            CO         14  N67052              568.0   \n",
       "1166010        1310            CO         14  N78060              594.0   \n",
       "7423336        1310            CO         14  N76055              565.0   \n",
       "4325325        1805            CO         15  N76054              615.0   \n",
       "7412671        1920            CO         15  N76064              670.0   \n",
       "1799647        1820            CO         15  N67058              634.0   \n",
       "5577867        1805            CO         15  N76055              624.0   \n",
       "1145252        1310            CO         14  N59053              565.0   \n",
       "4301281        1255            CO         14  N76055              577.0   \n",
       "1799514        1310            CO         14  N66051              568.0   \n",
       "\n",
       "         CRSElapsedTime  AirTime  ArrDelay  DepDelay Origin Dest  Distance  \\\n",
       "6801165           565.0    533.0      -6.0      -9.0    HNL  EWR      4962   \n",
       "1166010           565.0    564.0      17.0     -12.0    HNL  EWR      4962   \n",
       "7423336           565.0    536.0     -11.0     -11.0    HNL  EWR      4962   \n",
       "4325325           635.0    576.0      35.0      55.0    EWR  HNL      4962   \n",
       "7412671           660.0    643.0       7.0      -3.0    EWR  HNL      4962   \n",
       "1799647           660.0    592.0      12.0      38.0    EWR  HNL      4962   \n",
       "5577867           635.0    589.0     -14.0      -3.0    EWR  HNL      4962   \n",
       "1145252           565.0    539.0      -5.0      -5.0    HNL  EWR      4962   \n",
       "4301281           575.0    547.0      -6.0      -8.0    HNL  EWR      4962   \n",
       "1799514           565.0    538.0      -1.0      -4.0    HNL  EWR      4962   \n",
       "\n",
       "         TaxiIn  TaxiOut  Cancelled CancellationCode  Diverted  CarrierDelay  \\\n",
       "6801165    13.0     22.0          0                          0           0.0   \n",
       "1166010    13.0     17.0          0                          0           0.0   \n",
       "7423336     6.0     23.0          0                          0           0.0   \n",
       "4325325     7.0     32.0          0                          0          11.0   \n",
       "7412671     7.0     20.0          0                          0           0.0   \n",
       "1799647     4.0     38.0          0                          0           0.0   \n",
       "5577867     6.0     29.0          0                          0           0.0   \n",
       "1145252     8.0     18.0          0                          0           0.0   \n",
       "4301281     9.0     21.0          0                          0           0.0   \n",
       "1799514     9.0     21.0          0                          0           0.0   \n",
       "\n",
       "         WeatherDelay  NASDelay  SecurityDelay  LateAircraftDelay  \n",
       "6801165           0.0       0.0            0.0                0.0  \n",
       "1166010           0.0      17.0            0.0                0.0  \n",
       "7423336           0.0       0.0            0.0                0.0  \n",
       "4325325           0.0       0.0            0.0               24.0  \n",
       "7412671           0.0       0.0            0.0                0.0  \n",
       "1799647           0.0       0.0            0.0                0.0  \n",
       "5577867           0.0       0.0            0.0                0.0  \n",
       "1145252           0.0       0.0            0.0                0.0  \n",
       "4301281           0.0       0.0            0.0                0.0  \n",
       "1799514           0.0       0.0            0.0                0.0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_airlines.sort_values(\"Distance\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12bfc315",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14a0751e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf9ab912",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "557f8386",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a35e7063",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0361c8e4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5912581c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "072f45e6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a777af3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9421ee5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5db245e3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a564cf7d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45fbc100",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "febbed7a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1a9b3d1c",
   "metadata": {},
   "source": [
    "# 5. Update a column based on a condition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ae784616",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>Julie Wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>Adyson McNeely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>09-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Invalid</td>\n",
       "      <td>USA</td>\n",
       "      <td>Hawaii</td>\n",
       "      <td>Habush, Oahu</td>\n",
       "      <td>Surfing</td>\n",
       "      <td>John Denges</td>\n",
       "      <td>M</td>\n",
       "      <td>48</td>\n",
       "      <td>Injury to left lower leg from surfboard skeg</td>\n",
       "      <td>N</td>\n",
       "      <td>07h45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.09-Denges.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>2018.06.09</td>\n",
       "      <td>6301.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type country        area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating     USA  California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked     USA     Georgia   \n",
       "2  2018.06.09  09-Jun-2018  2018.0     Invalid     USA      Hawaii   \n",
       "\n",
       "                         location  activity             name sex age  \\\n",
       "0     Oceanside, San Diego County  Paddling      Julie Wolfe   F  57   \n",
       "1  St. Simon Island, Glynn County  Standing  Adyson McNeely    F  11   \n",
       "2                    Habush, Oahu   Surfing      John Denges   M  48   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "2       Injury to left lower leg from surfboard skeg           N   \n",
       "\n",
       "            time      species          investigator or source  \\\n",
       "0          18h00  White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00          NaN  K.McMurray, TrackingSharks.com   \n",
       "2          07h45          NaN  K.McMurray, TrackingSharks.com   \n",
       "\n",
       "                      pdf                                       href formula  \\\n",
       "0    2018.06.25-Wolfe.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  2018.06.18-McNeely.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "2   2018.06.09-Denges.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "2  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.09   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  \n",
       "2    2018.06.09          6301.0         NaN         NaN  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add a column\n",
    "df_sharks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "41953411",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sharks['name'] = df_sharks.name.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ce9f057e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>julie wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>adyson mcneely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type country        area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating     USA  California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked     USA     Georgia   \n",
       "\n",
       "                         location  activity             name sex age  \\\n",
       "0     Oceanside, San Diego County  Paddling      julie wolfe   F  57   \n",
       "1  St. Simon Island, Glynn County  Standing  adyson mcneely    F  11   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "\n",
       "            time      species          investigator or source  \\\n",
       "0          18h00  White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00          NaN  K.McMurray, TrackingSharks.com   \n",
       "\n",
       "                      pdf                                       href formula  \\\n",
       "0    2018.06.25-Wolfe.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  2018.06.18-McNeely.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "798e8010",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sharks['dummy'] = 123"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "77222374",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "      <th>unnamed: 22</th>\n",
       "      <th>unnamed: 23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>julie wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>adyson mcneely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type country        area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating     USA  California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked     USA     Georgia   \n",
       "\n",
       "                         location  activity             name sex age  \\\n",
       "0     Oceanside, San Diego County  Paddling      julie wolfe   F  57   \n",
       "1  St. Simon Island, Glynn County  Standing  adyson mcneely    F  11   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "\n",
       "            time      species          investigator or source  \\\n",
       "0          18h00  White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00          NaN  K.McMurray, TrackingSharks.com   \n",
       "\n",
       "                      pdf                                       href formula  \\\n",
       "0    2018.06.25-Wolfe.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  2018.06.18-McNeely.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "\n",
       "  case number.2  original order unnamed: 22 unnamed: 23  \n",
       "0    2018.06.25          6303.0         NaN         NaN  \n",
       "1    2018.06.18          6302.0         NaN         NaN  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# delete a column\n",
    "# del df_sharks['dummy']\n",
    "df_sharks = df_sharks.drop(columns=\"dummy\")\n",
    "df_sharks.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "aab01aac",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sharks = df_sharks.drop(columns=['unnamed: 22','unnamed: 23'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0824808b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "43714037",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Update columns using df.assign: You can create multiple columns in one call of assign\n",
    "\n",
    "# https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.assign.html\n",
    "# df.assign(temp_f=lambda x: x['temp_c'] * 9 / 5 + 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "04f61b0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.assign(\n",
    "#    temp_f=lambda x: x['temp_c'] * 9 / 5 + 32,\n",
    "#    temp_k=lambda x: (x['temp_f'] + 459.67) * 5 / 9\n",
    "#)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "06387e0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AMZN</th>\n",
       "      <th>amzn_returns</th>\n",
       "      <th>amzn_cumulative_returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>2.1070</td>\n",
       "      <td>-0.053459</td>\n",
       "      <td>0.946541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>2.0885</td>\n",
       "      <td>-0.008780</td>\n",
       "      <td>0.938230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>2.0525</td>\n",
       "      <td>-0.017237</td>\n",
       "      <td>0.922057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>2.1160</td>\n",
       "      <td>0.030938</td>\n",
       "      <td>0.950584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>2.0920</td>\n",
       "      <td>-0.011342</td>\n",
       "      <td>0.939802</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              AMZN  amzn_returns  amzn_cumulative_returns\n",
       "Date                                                     \n",
       "2005-01-04  2.1070     -0.053459                 0.946541\n",
       "2005-01-05  2.0885     -0.008780                 0.938230\n",
       "2005-01-06  2.0525     -0.017237                 0.922057\n",
       "2005-01-07  2.1160      0.030938                 0.950584\n",
       "2005-01-10  2.0920     -0.011342                 0.939802"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn = stocks['AMZN'].to_frame()\n",
    "\n",
    "amzn_returns = (amzn\n",
    " .assign(\n",
    "     amzn_returns=lambda x: x.AMZN.pct_change(),\n",
    "     amzn_cumulative_returns=lambda x: (1 + x.amzn_returns).cumprod()\n",
    " )\n",
    " .dropna()\n",
    ")\n",
    "amzn_returns.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "aa7df6e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.05345911949685522"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2.1070 / 2.2260 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b509098a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.00878025628856216"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2.0885 / 2.1070 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3c5e03e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97db922d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f6599b0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "030c339f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "50651c0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Update a column using a regex\n",
    "# https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.replace.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4bb6ed65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>25-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Boating</td>\n",
       "      <td>USA</td>\n",
       "      <td>California</td>\n",
       "      <td>Oceanside, San Diego County</td>\n",
       "      <td>Paddling</td>\n",
       "      <td>julie wolfe</td>\n",
       "      <td>F</td>\n",
       "      <td>57</td>\n",
       "      <td>No injury to occupant, outrigger canoe and pad...</td>\n",
       "      <td>N</td>\n",
       "      <td>18h00</td>\n",
       "      <td>White shark</td>\n",
       "      <td>R. Collier, GSAF</td>\n",
       "      <td>2018.06.25-Wolfe.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>2018.06.25</td>\n",
       "      <td>6303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>18-Jun-2018</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>USA</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>St. Simon Island, Glynn County</td>\n",
       "      <td>Standing</td>\n",
       "      <td>adyson mcneely</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>Minor injury to left thigh</td>\n",
       "      <td>N</td>\n",
       "      <td>14h00  -15h00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K.McMurray, TrackingSharks.com</td>\n",
       "      <td>2018.06.18-McNeely.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>2018.06.18</td>\n",
       "      <td>6302.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  case number         date    year        type country        area  \\\n",
       "0  2018.06.25  25-Jun-2018  2018.0     Boating     USA  California   \n",
       "1  2018.06.18  18-Jun-2018  2018.0  Unprovoked     USA     Georgia   \n",
       "\n",
       "                         location  activity             name sex age  \\\n",
       "0     Oceanside, San Diego County  Paddling      julie wolfe   F  57   \n",
       "1  St. Simon Island, Glynn County  Standing  adyson mcneely    F  11   \n",
       "\n",
       "                                              injury fatal (y/n)  \\\n",
       "0  No injury to occupant, outrigger canoe and pad...           N   \n",
       "1                         Minor injury to left thigh           N   \n",
       "\n",
       "            time      species          investigator or source  \\\n",
       "0          18h00  White shark                R. Collier, GSAF   \n",
       "1  14h00  -15h00          NaN  K.McMurray, TrackingSharks.com   \n",
       "\n",
       "                      pdf                                       href formula  \\\n",
       "0    2018.06.25-Wolfe.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "1  2018.06.18-McNeely.pdf  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                href case number.1  \\\n",
       "0  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.25   \n",
       "1  http://sharkattackfile.net/spreadsheets/pdf_di...    2018.06.18   \n",
       "\n",
       "  case number.2  original order  \n",
       "0    2018.06.25          6303.0  \n",
       "1    2018.06.18          6302.0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e6894433",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case number</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>type</th>\n",
       "      <th>country</th>\n",
       "      <th>area</th>\n",
       "      <th>location</th>\n",
       "      <th>activity</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>injury</th>\n",
       "      <th>fatal (y/n)</th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "      <th>investigator or source</th>\n",
       "      <th>pdf</th>\n",
       "      <th>href formula</th>\n",
       "      <th>href</th>\n",
       "      <th>case number.1</th>\n",
       "      <th>case number.2</th>\n",
       "      <th>original order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1673</th>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>18-May-2004</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Provoked</td>\n",
       "      <td>BAHAMAS</td>\n",
       "      <td>Abaco Islands</td>\n",
       "      <td>Green Turtle Cay</td>\n",
       "      <td>Free diving &amp; spearfishing</td>\n",
       "      <td>wolfgang leander</td>\n",
       "      <td>M</td>\n",
       "      <td>63</td>\n",
       "      <td>Left forearm bitten PROVOKED INCIDENT</td>\n",
       "      <td>N</td>\n",
       "      <td>15h00</td>\n",
       "      <td>1,5 m [5'] Caribbean reef shark (Carcharhinus ...</td>\n",
       "      <td>W. Leander, M. Levine, GSAF</td>\n",
       "      <td>2004.05.18-Leander.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>2004.05.18</td>\n",
       "      <td>4630.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4288</th>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>Aug-1955</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>Unprovoked</td>\n",
       "      <td>NORTH ATLANTIC OCEAN</td>\n",
       "      <td>Open sea</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treading water</td>\n",
       "      <td>wolfgang emrich</td>\n",
       "      <td>M</td>\n",
       "      <td>15</td>\n",
       "      <td>No injury</td>\n",
       "      <td>N</td>\n",
       "      <td>Early afternoon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H.D.Baldridge (1994), SAF Case #1489</td>\n",
       "      <td>1955.08.00.c-NV-Emrich.pdf</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>http://sharkattackfile.net/spreadsheets/pdf_di...</td>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>1955.08.00.c</td>\n",
       "      <td>2015.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       case number         date    year        type                country  \\\n",
       "1673    2004.05.18  18-May-2004  2004.0    Provoked                BAHAMAS   \n",
       "4288  1955.08.00.c     Aug-1955  1955.0  Unprovoked  NORTH ATLANTIC OCEAN    \n",
       "\n",
       "               area          location                    activity  \\\n",
       "1673  Abaco Islands  Green Turtle Cay  Free diving & spearfishing   \n",
       "4288       Open sea               NaN              Treading water   \n",
       "\n",
       "                  name sex age                                 injury  \\\n",
       "1673  wolfgang leander   M  63  Left forearm bitten PROVOKED INCIDENT   \n",
       "4288   wolfgang emrich   M  15                              No injury   \n",
       "\n",
       "     fatal (y/n)             time  \\\n",
       "1673           N            15h00   \n",
       "4288           N  Early afternoon   \n",
       "\n",
       "                                                species  \\\n",
       "1673  1,5 m [5'] Caribbean reef shark (Carcharhinus ...   \n",
       "4288                                                NaN   \n",
       "\n",
       "                    investigator or source                         pdf  \\\n",
       "1673           W. Leander, M. Levine, GSAF      2004.05.18-Leander.pdf   \n",
       "4288  H.D.Baldridge (1994), SAF Case #1489  1955.08.00.c-NV-Emrich.pdf   \n",
       "\n",
       "                                           href formula  \\\n",
       "1673  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "4288  http://sharkattackfile.net/spreadsheets/pdf_di...   \n",
       "\n",
       "                                                   href case number.1  \\\n",
       "1673  http://sharkattackfile.net/spreadsheets/pdf_di...    2004.05.18   \n",
       "4288  http://sharkattackfile.net/spreadsheets/pdf_di...  1955.08.00.c   \n",
       "\n",
       "     case number.2  original order  \n",
       "1673    2004.05.18          4630.0  \n",
       "4288  1955.08.00.c          2015.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sharks[df_sharks.name.str.contains('^wolf', na=False, regex=True)].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a40e7b4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.replace(to_replace=r'^ba.$', value='new', regex=True)\n",
    "df_sharks['name'] = (df_sharks\n",
    " .name\n",
    " .replace(to_replace='^wolf', value='', regex=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "6190ec1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_sharks[df_sharks.name.str.contains('^gang', na=False, regex=True)].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8477cf0c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4bf6b63",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "808886b9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d93dc76",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b661dd9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9fe1d1d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d2aeb19",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc280bf2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8238f83",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "210827e4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9614a496",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3860ba79",
   "metadata": {},
   "source": [
    "# 6. Value Counts & Groupby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d3ddfa09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2     944282\n",
       "3     914525\n",
       "21    236554\n",
       "27    215122\n",
       "5     210817\n",
       "40    192292\n",
       "4     174884\n",
       "20    168124\n",
       "26    144635\n",
       "23    131908\n",
       "Name: PAGE, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.value_counts\n",
    "pageviews.PAGE.value_counts().nlargest(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "cff91022",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FEC_EVENT</th>\n",
       "      <th>PAGE</th>\n",
       "      <th>CONTENT_CATEGORY</th>\n",
       "      <th>CONTENT_CATEGORY_TOP</th>\n",
       "      <th>CONTENT_CATEGORY_BOTTOM</th>\n",
       "      <th>SITE_ID</th>\n",
       "      <th>ON_SITE_SEARCH_TERM</th>\n",
       "      <th>USER_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18350981</th>\n",
       "      <td>2018-09-12 09:11:48</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7974880</th>\n",
       "      <td>2018-06-21 17:26:35</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12678188</th>\n",
       "      <td>2018-12-18 08:06:09</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5143671</th>\n",
       "      <td>2018-04-18 06:49:01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9400713</th>\n",
       "      <td>2018-04-07 14:44:46</td>\n",
       "      <td>60</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   FEC_EVENT  PAGE  CONTENT_CATEGORY  CONTENT_CATEGORY_TOP  \\\n",
       "18350981 2018-09-12 09:11:48    40                 1                     1   \n",
       "7974880  2018-06-21 17:26:35     2                 2                     2   \n",
       "12678188 2018-12-18 08:06:09    27                 2                     2   \n",
       "5143671  2018-04-18 06:49:01     2                 2                     2   \n",
       "9400713  2018-04-07 14:44:46    60                 2                     2   \n",
       "\n",
       "          CONTENT_CATEGORY_BOTTOM  SITE_ID  ON_SITE_SEARCH_TERM  USER_ID  \n",
       "18350981                        1        1                    1     5215  \n",
       "7974880                         2        2                    1     6323  \n",
       "12678188                        2        3                    1     6117  \n",
       "5143671                         2        2                    1      441  \n",
       "9400713                         2        3                    1     8844  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pageviews.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "174a5913",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PAGE</th>\n",
       "      <th>CONTENT_CATEGORY</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>944282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>914525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>236554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>215122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>210817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1670</th>\n",
       "      <td>1067</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1671</th>\n",
       "      <td>1067</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1672</th>\n",
       "      <td>1065</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1673</th>\n",
       "      <td>1053</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1674</th>\n",
       "      <td>1831</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1675 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PAGE  CONTENT_CATEGORY       0\n",
       "0        2                 2  944282\n",
       "1        3                 2  914525\n",
       "2       21                 2  236554\n",
       "3       27                 2  215122\n",
       "4        5                 2  210817\n",
       "...    ...               ...     ...\n",
       "1670  1067                39       1\n",
       "1671  1067                11       1\n",
       "1672  1065                 2       1\n",
       "1673  1053                 4       1\n",
       "1674  1831                 2       1\n",
       "\n",
       "[1675 rows x 3 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.value_counts - 2 variables\n",
    "pageviews.value_counts(['PAGE','CONTENT_CATEGORY']).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3cfe6c61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PAGE</th>\n",
       "      <th>CONTENT_CATEGORY</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>89239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>944282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>914525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>174884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>210817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1670</th>\n",
       "      <td>1823</td>\n",
       "      <td>22</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1671</th>\n",
       "      <td>1826</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1672</th>\n",
       "      <td>1827</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1673</th>\n",
       "      <td>1830</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1674</th>\n",
       "      <td>1831</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1675 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PAGE  CONTENT_CATEGORY       0\n",
       "0        1                 1   89239\n",
       "1        2                 2  944282\n",
       "2        3                 2  914525\n",
       "3        4                 2  174884\n",
       "4        5                 2  210817\n",
       "...    ...               ...     ...\n",
       "1670  1823                22       6\n",
       "1671  1826                11       1\n",
       "1672  1827                 2       2\n",
       "1673  1830                 2       1\n",
       "1674  1831                 2       1\n",
       "\n",
       "[1675 rows x 3 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.size\n",
    "pageviews.groupby(['PAGE','CONTENT_CATEGORY']).size().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "1055b501",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat      cut color clarity  depth  table  price     x     y     z\n",
       "0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43\n",
       "1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31\n",
       "2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31\n",
       "3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63\n",
       "4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# groupby examples\n",
    "diamonds = pd.read_csv(base_url + \"diamonds.csv\")\n",
    "diamonds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "4f36c53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>avg_price</th>\n",
       "      <th>avg_carat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fair</td>\n",
       "      <td>D</td>\n",
       "      <td>4291.061350</td>\n",
       "      <td>0.920123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Fair</td>\n",
       "      <td>E</td>\n",
       "      <td>3682.312500</td>\n",
       "      <td>0.856607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fair</td>\n",
       "      <td>F</td>\n",
       "      <td>3827.003205</td>\n",
       "      <td>0.904712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fair</td>\n",
       "      <td>G</td>\n",
       "      <td>4239.254777</td>\n",
       "      <td>1.023822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fair</td>\n",
       "      <td>H</td>\n",
       "      <td>5135.683168</td>\n",
       "      <td>1.219175</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cut color    avg_price  avg_carat\n",
       "0  Fair     D  4291.061350   0.920123\n",
       "1  Fair     E  3682.312500   0.856607\n",
       "2  Fair     F  3827.003205   0.904712\n",
       "3  Fair     G  4239.254777   1.023822\n",
       "4  Fair     H  5135.683168   1.219175"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(diamonds\n",
    " .groupby([\"cut\", \"color\"], as_index=False)\n",
    " .agg(\n",
    "     avg_price = (\"price\", \"mean\"),\n",
    "     avg_carat = (\"carat\", \"mean\")\n",
    " )\n",
    ").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a31d82ab",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "24ddeea9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clarity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>I1</th>\n",
       "      <td>3924.168691</td>\n",
       "      <td>2806.778270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IF</th>\n",
       "      <td>2864.839106</td>\n",
       "      <td>3920.248499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SI1</th>\n",
       "      <td>3996.001148</td>\n",
       "      <td>3799.483853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SI2</th>\n",
       "      <td>5063.028606</td>\n",
       "      <td>4260.458578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VS1</th>\n",
       "      <td>3839.455391</td>\n",
       "      <td>4011.747958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VS2</th>\n",
       "      <td>3924.989395</td>\n",
       "      <td>4042.302816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VVS1</th>\n",
       "      <td>2523.114637</td>\n",
       "      <td>3334.838888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VVS2</th>\n",
       "      <td>3283.737071</td>\n",
       "      <td>3821.647537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mean          std\n",
       "clarity                          \n",
       "I1       3924.168691  2806.778270\n",
       "IF       2864.839106  3920.248499\n",
       "SI1      3996.001148  3799.483853\n",
       "SI2      5063.028606  4260.458578\n",
       "VS1      3839.455391  4011.747958\n",
       "VS2      3924.989395  4042.302816\n",
       "VVS1     2523.114637  3334.838888\n",
       "VVS2     3283.737071  3821.647537"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(diamonds\n",
    " .groupby(\"clarity\")\n",
    " ['price']\n",
    " .agg(['mean', 'std'])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6b07a5a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "424c8394",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat      cut color clarity  depth  table  price     x     y     z\n",
       "0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43\n",
       "1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31\n",
       "2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31\n",
       "3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63\n",
       "4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# transform\n",
    "diamonds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "cdffdd36",
   "metadata": {},
   "outputs": [],
   "source": [
    "diamonds['clarity_price'] = (\n",
    "    diamonds\n",
    "    .groupby(\"clarity\")\n",
    "    ['price']\n",
    "    .transform(\"mean\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c74a8bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "447cb394",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "clarity\n",
       "I1      3924.168691\n",
       "IF      2864.839106\n",
       "SI1     3996.001148\n",
       "SI2     5063.028606\n",
       "VS1     3839.455391\n",
       "VS2     3924.989395\n",
       "VVS1    2523.114637\n",
       "VVS2    3283.737071\n",
       "Name: price, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(diamonds\n",
    " .groupby(\"clarity\")\n",
    " ['price']\n",
    " .mean()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3807fe6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a02e4fb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c57880b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "286e763f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11ded172",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "73e31fe1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0dc49b07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42a1ed06",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d990fde",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a1d0a78",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19e57447",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c1782382",
   "metadata": {},
   "source": [
    "# 7. Working with Time Series Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "c5bad24d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aapl = stocks[[\"AAPL\"]]\n",
    "aapl.plot(logy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "5bcdee5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.5454545454545454"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2.5/5.5-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dc9a5835",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aapl['2007-01-01':'2010-01-01'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "8611a5ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>0.961916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.980306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.981066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>1.048092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-11</th>\n",
       "      <td>0.981218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-12</th>\n",
       "      <td>0.994897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-13</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-14</th>\n",
       "      <td>1.066937</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL\n",
       "Date                \n",
       "2005-01-03  0.961916\n",
       "2005-01-04       NaN\n",
       "2005-01-05  0.980306\n",
       "2005-01-06  0.981066\n",
       "2005-01-07       NaN\n",
       "2005-01-10  1.048092\n",
       "2005-01-11  0.981218\n",
       "2005-01-12  0.994897\n",
       "2005-01-13       NaN\n",
       "2005-01-14  1.066937"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fill missing values\n",
    "x = aapl.head(10).copy()\n",
    "x.iloc[1,:] = np.NaN\n",
    "x.iloc[4,:] = np.NaN\n",
    "x.iloc[8,:] = np.NaN\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0414de0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "?x.fillna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8490f68b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>AAPL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>0.961916</td>\n",
       "      <td>0.961916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.961916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.980306</td>\n",
       "      <td>0.980306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.981066</td>\n",
       "      <td>0.981066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.981066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>1.048092</td>\n",
       "      <td>1.048092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-11</th>\n",
       "      <td>0.981218</td>\n",
       "      <td>0.981218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-12</th>\n",
       "      <td>0.994897</td>\n",
       "      <td>0.994897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.994897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-14</th>\n",
       "      <td>1.066937</td>\n",
       "      <td>1.066937</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL      AAPL\n",
       "Date                          \n",
       "2005-01-03  0.961916  0.961916\n",
       "2005-01-04       NaN  0.961916\n",
       "2005-01-05  0.980306  0.980306\n",
       "2005-01-06  0.981066  0.981066\n",
       "2005-01-07       NaN  0.981066\n",
       "2005-01-10  1.048092  1.048092\n",
       "2005-01-11  0.981218  0.981218\n",
       "2005-01-12  0.994897  0.994897\n",
       "2005-01-13       NaN  0.994897\n",
       "2005-01-14  1.066937  1.066937"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ffill: propagate last valid observation forward to next valid\n",
    "pd.concat([x, x.fillna(method='ffill')], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "74ef9869",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>0.961916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>0.971795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.980306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.981066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>1.052499</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL\n",
       "Date                \n",
       "2005-01-03  0.961916\n",
       "2005-01-04  0.971795\n",
       "2005-01-05  0.980306\n",
       "2005-01-06  0.981066\n",
       "2005-01-07  1.052499"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aapl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "2c614d61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Resample as monthly data\n",
    "aapl.resample(\"M\").last().plot(logy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "d8a6b66e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Shift a column and compute % change manually"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "f51ee6ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0197907397319661"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "160.770004/157.649994 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "0fd48b86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>tm1</th>\n",
       "      <th>pct_change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-24</th>\n",
       "      <td>160.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>158.279999</td>\n",
       "      <td>160.250000</td>\n",
       "      <td>-0.012293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>157.649994</td>\n",
       "      <td>158.279999</td>\n",
       "      <td>-0.003980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>160.770004</td>\n",
       "      <td>157.649994</td>\n",
       "      <td>0.019791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>162.360001</td>\n",
       "      <td>160.770004</td>\n",
       "      <td>0.009890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>164.899994</td>\n",
       "      <td>162.360001</td>\n",
       "      <td>0.015644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-03</th>\n",
       "      <td>166.169998</td>\n",
       "      <td>164.899994</td>\n",
       "      <td>0.007702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-04</th>\n",
       "      <td>165.630005</td>\n",
       "      <td>166.169998</td>\n",
       "      <td>-0.003250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-05</th>\n",
       "      <td>163.759995</td>\n",
       "      <td>165.630005</td>\n",
       "      <td>-0.011290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-06</th>\n",
       "      <td>164.660004</td>\n",
       "      <td>163.759995</td>\n",
       "      <td>0.005496</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  AAPL         tm1  pct_change\n",
       "Date                                          \n",
       "2023-03-24  160.250000         NaN         NaN\n",
       "2023-03-27  158.279999  160.250000   -0.012293\n",
       "2023-03-28  157.649994  158.279999   -0.003980\n",
       "2023-03-29  160.770004  157.649994    0.019791\n",
       "2023-03-30  162.360001  160.770004    0.009890\n",
       "2023-03-31  164.899994  162.360001    0.015644\n",
       "2023-04-03  166.169998  164.899994    0.007702\n",
       "2023-04-04  165.630005  166.169998   -0.003250\n",
       "2023-04-05  163.759995  165.630005   -0.011290\n",
       "2023-04-06  164.660004  163.759995    0.005496"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = aapl.tail(10).copy()\n",
    "x['tm1'] = x.AAPL.shift(1)\n",
    "x['pct_change'] = x['AAPL'] / x['tm1'] - 1\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "7a6d19ac",
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>tm1</th>\n",
       "      <th>pct_change</th>\n",
       "      <th>pct_change2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-24</th>\n",
       "      <td>160.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>158.279999</td>\n",
       "      <td>160.250000</td>\n",
       "      <td>-0.012293</td>\n",
       "      <td>-0.012293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>157.649994</td>\n",
       "      <td>158.279999</td>\n",
       "      <td>-0.003980</td>\n",
       "      <td>-0.003980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>160.770004</td>\n",
       "      <td>157.649994</td>\n",
       "      <td>0.019791</td>\n",
       "      <td>0.019791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>162.360001</td>\n",
       "      <td>160.770004</td>\n",
       "      <td>0.009890</td>\n",
       "      <td>0.009890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>164.899994</td>\n",
       "      <td>162.360001</td>\n",
       "      <td>0.015644</td>\n",
       "      <td>0.015644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-03</th>\n",
       "      <td>166.169998</td>\n",
       "      <td>164.899994</td>\n",
       "      <td>0.007702</td>\n",
       "      <td>0.007702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-04</th>\n",
       "      <td>165.630005</td>\n",
       "      <td>166.169998</td>\n",
       "      <td>-0.003250</td>\n",
       "      <td>-0.003250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-05</th>\n",
       "      <td>163.759995</td>\n",
       "      <td>165.630005</td>\n",
       "      <td>-0.011290</td>\n",
       "      <td>-0.011290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-06</th>\n",
       "      <td>164.660004</td>\n",
       "      <td>163.759995</td>\n",
       "      <td>0.005496</td>\n",
       "      <td>0.005496</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  AAPL         tm1  pct_change  pct_change2\n",
       "Date                                                       \n",
       "2023-03-24  160.250000         NaN         NaN          NaN\n",
       "2023-03-27  158.279999  160.250000   -0.012293    -0.012293\n",
       "2023-03-28  157.649994  158.279999   -0.003980    -0.003980\n",
       "2023-03-29  160.770004  157.649994    0.019791     0.019791\n",
       "2023-03-30  162.360001  160.770004    0.009890     0.009890\n",
       "2023-03-31  164.899994  162.360001    0.015644     0.015644\n",
       "2023-04-03  166.169998  164.899994    0.007702     0.007702\n",
       "2023-04-04  165.630005  166.169998   -0.003250    -0.003250\n",
       "2023-04-05  163.759995  165.630005   -0.011290    -0.011290\n",
       "2023-04-06  164.660004  163.759995    0.005496     0.005496"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Percent Change\n",
    "x['pct_change2'] = x.AAPL.pct_change()\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d087eba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "464d3e05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>0.961916</td>\n",
       "      <td>18.813698</td>\n",
       "      <td>5.048826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>0.971795</td>\n",
       "      <td>18.884050</td>\n",
       "      <td>4.844342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.980306</td>\n",
       "      <td>18.841835</td>\n",
       "      <td>4.819685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.981066</td>\n",
       "      <td>18.820738</td>\n",
       "      <td>4.696148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>1.052499</td>\n",
       "      <td>18.764450</td>\n",
       "      <td>4.828153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL       MSFT      GOOG\n",
       "Date                                     \n",
       "2005-01-03  0.961916  18.813698  5.048826\n",
       "2005-01-04  0.971795  18.884050  4.844342\n",
       "2005-01-05  0.980306  18.841835  4.819685\n",
       "2005-01-06  0.981066  18.820738  4.696148\n",
       "2005-01-07  1.052499  18.764450  4.828153"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Same with more stocks\n",
    "top_stocks = stocks[['AAPL', 'MSFT', 'GOOG']]\n",
    "top_stocks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0cfdbe07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>0.010270</td>\n",
       "      <td>0.003739</td>\n",
       "      <td>-0.040501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.008758</td>\n",
       "      <td>-0.002236</td>\n",
       "      <td>-0.005090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.000776</td>\n",
       "      <td>-0.001120</td>\n",
       "      <td>-0.025632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>0.072811</td>\n",
       "      <td>-0.002991</td>\n",
       "      <td>0.028109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>0.015644</td>\n",
       "      <td>0.014962</td>\n",
       "      <td>0.026451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-03</th>\n",
       "      <td>0.007702</td>\n",
       "      <td>-0.003711</td>\n",
       "      <td>0.008750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-04</th>\n",
       "      <td>-0.003250</td>\n",
       "      <td>-0.000174</td>\n",
       "      <td>0.002002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-05</th>\n",
       "      <td>-0.011290</td>\n",
       "      <td>-0.009889</td>\n",
       "      <td>-0.001617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-06</th>\n",
       "      <td>0.005496</td>\n",
       "      <td>0.025533</td>\n",
       "      <td>0.037637</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4597 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL      MSFT      GOOG\n",
       "Date                                    \n",
       "2005-01-03       NaN       NaN       NaN\n",
       "2005-01-04  0.010270  0.003739 -0.040501\n",
       "2005-01-05  0.008758 -0.002236 -0.005090\n",
       "2005-01-06  0.000776 -0.001120 -0.025632\n",
       "2005-01-07  0.072811 -0.002991  0.028109\n",
       "...              ...       ...       ...\n",
       "2023-03-31  0.015644  0.014962  0.026451\n",
       "2023-04-03  0.007702 -0.003711  0.008750\n",
       "2023-04-04 -0.003250 -0.000174  0.002002\n",
       "2023-04-05 -0.011290 -0.009889 -0.001617\n",
       "2023-04-06  0.005496  0.025533  0.037637\n",
       "\n",
       "[4597 rows x 3 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret_stocks = top_stocks.pct_change()\n",
    "ret_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b880df6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a23e8bcb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd2d51ab",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac459718",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "484b8e63",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1b109a7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ea19350",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4787eca8",
   "metadata": {},
   "source": [
    "# 8. Plotting\n",
    "\n",
    "[Pandas .plot() Documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "3f5312bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>0.010270</td>\n",
       "      <td>0.003739</td>\n",
       "      <td>-0.040501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>0.008758</td>\n",
       "      <td>-0.002236</td>\n",
       "      <td>-0.005090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>0.000776</td>\n",
       "      <td>-0.001120</td>\n",
       "      <td>-0.025632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>0.072811</td>\n",
       "      <td>-0.002991</td>\n",
       "      <td>0.028109</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                AAPL      MSFT      GOOG\n",
       "Date                                    \n",
       "2005-01-03       NaN       NaN       NaN\n",
       "2005-01-04  0.010270  0.003739 -0.040501\n",
       "2005-01-05  0.008758 -0.002236 -0.005090\n",
       "2005-01-06  0.000776 -0.001120 -0.025632\n",
       "2005-01-07  0.072811 -0.002991  0.028109"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret_stocks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "e5dc56a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:ylabel='Frequency'>, <AxesSubplot:ylabel='Frequency'>,\n",
       "       <AxesSubplot:ylabel='Frequency'>], dtype=object)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(top_stocks\n",
    " .resample(\"M\")\n",
    " .last()\n",
    " .pct_change()\n",
    " .plot(kind='hist', subplots=True, bins=50)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a21cb69",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0c45365",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fadf08b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70015035",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2863e695",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c3d87f7f",
   "metadata": {},
   "source": [
    "# 9. Reshaping Data - Wide to Long Format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "4dd91136",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.melt - Wide to Long Format: https://pandas.pydata.org/docs/reference/api/pandas.melt.html\n",
    "# base_path + \"mortality_data.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "bdcd788e",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'base_path' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[76], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_excel(\u001b[43mbase_path\u001b[49m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mclimate_change.xls\u001b[39m\u001b[38;5;124m\"\u001b[39m, na_values\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m..\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m      2\u001b[0m df\u001b[38;5;241m.\u001b[39mhead(\u001b[38;5;241m2\u001b[39m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'base_path' is not defined"
     ]
    }
   ],
   "source": [
    "df = pd.read_excel(base_path + \"climate_change.xls\", na_values=['..'])\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1cd9eb1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "103a26a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_melted = df.melt(\n",
    "    id_vars = list(df.columns[:6]), \n",
    "    value_vars = df.columns[6:],\n",
    "    var_name='year'\n",
    ")\n",
    "df_melted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c5e06f0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb07d7bb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02f9a614",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "933b5d83",
   "metadata": {},
   "source": [
    "# 10. Reshaping Data - Stack, unstack, Pivot\n",
    "\n",
    "https://pandas.pydata.org/docs/user_guide/reshaping.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f695390",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas._testing as tm\n",
    "\n",
    "def unpivot(frame):\n",
    "    N, K = frame.shape\n",
    "    data = {\n",
    "        \"value\": frame.to_numpy().ravel(\"F\"),\n",
    "        \"variable\": np.asarray(frame.columns).repeat(N),\n",
    "        \"date\": np.tile(np.asarray(frame.index), K),\n",
    "    }\n",
    "    return pd.DataFrame(data, columns=[\"date\", \"variable\", \"value\"])\n",
    "\n",
    "\n",
    "df = unpivot(tm.makeTimeDataFrame(3))\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c650694f",
   "metadata": {},
   "source": [
    "## Pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44e53666",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.pivot(index=\"date\", columns=\"variable\", values=\"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f6dc551",
   "metadata": {},
   "source": [
    "## Stack and Unstack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5be6a31",
   "metadata": {},
   "outputs": [],
   "source": [
    "tuples = list(\n",
    "    zip(\n",
    "        *[\n",
    "            [\"bar\", \"bar\", \"baz\", \"baz\", \"foo\", \"foo\", \"qux\", \"qux\"],\n",
    "            [\"one\", \"two\", \"one\", \"two\", \"one\", \"two\", \"one\", \"two\"],\n",
    "        ]\n",
    "    )\n",
    ")\n",
    "\n",
    "\n",
    "index = pd.MultiIndex.from_tuples(tuples, names=[\"first\", \"second\"])\n",
    "df = pd.DataFrame(np.random.randn(8, 2), index=index, columns=[\"A\", \"B\"])\n",
    "df2 = df[:4]\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "216400c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "stacked = df2.stack()\n",
    "stacked.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc9f4433",
   "metadata": {},
   "outputs": [],
   "source": [
    "stacked.unstack(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1ad6718",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e497f9ec",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b9274fd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a6cdad2b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd56b55f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dec96a04",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb875d81",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b040157b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5c75d6f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e757d965",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c45d2a1b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fde80e62",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7c9a52b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca2bf2a1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python [conda env:tabular]",
   "language": "python",
   "name": "conda-env-tabular-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}