DataFrames 2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a6ae2d6a",
   "metadata": {},
   "source": [
    "# Memory Optimization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d4419d63",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   First Name         933 non-null    object \n",
      " 1   Gender             855 non-null    object \n",
      " 2   Start Date         1000 non-null   object \n",
      " 3   Last Login Time    1000 non-null   object \n",
      " 4   Salary             1000 non-null   int64  \n",
      " 5   Bonus %            1000 non-null   float64\n",
      " 6   Senior Management  933 non-null    object \n",
      " 7   Team               957 non-null    object \n",
      "dtypes: float64(1), int64(1), object(6)\n",
      "memory usage: 62.6+ KB\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\"employees.csv\")\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4d196d43",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Start Date\"] = pd.to_datetime(df[\"Start Date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c187f3fa",
   "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",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>12:42 PM</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>6:53 AM</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>11:17 AM</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>1:00 PM</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>4:47 PM</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06        12:42 PM   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31         6:53 AM   61933    4.170   \n",
       "2      Maria  Female 1993-04-23        11:17 AM  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04         1:00 PM  138705    9.340   \n",
       "4      Larry    Male 1998-01-24         4:47 PM  101004    1.389   \n",
       "\n",
       "  Senior Management             Team  \n",
       "0              True        Marketing  \n",
       "1              True              NaN  \n",
       "2             False          Finance  \n",
       "3              True          Finance  \n",
       "4              True  Client Services  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "34c0e0f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Last Login Time\"] = pd.to_datetime(df[\"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5c0cff51",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count  Dtype         \n",
      "---  ------             --------------  -----         \n",
      " 0   First Name         933 non-null    object        \n",
      " 1   Gender             855 non-null    category      \n",
      " 2   Start Date         1000 non-null   datetime64[ns]\n",
      " 3   Last Login Time    1000 non-null   datetime64[ns]\n",
      " 4   Salary             1000 non-null   int64         \n",
      " 5   Bonus %            1000 non-null   float64       \n",
      " 6   Senior Management  1000 non-null   bool          \n",
      " 7   Team               957 non-null    object        \n",
      "dtypes: bool(1), category(1), datetime64[ns](2), float64(1), int64(1), object(2)\n",
      "memory usage: 49.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e9d89ce7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2      Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4      Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "\n",
       "   Senior Management             Team  \n",
       "0               True        Marketing  \n",
       "1               True              NaN  \n",
       "2              False          Finance  \n",
       "3               True          Finance  \n",
       "4               True  Client Services  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Last Login Time\", \"Start Date\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c21edbb0",
   "metadata": {},
   "source": [
    "# Filter a DataFrame based on A Condition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a4bcee77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       True\n",
       "1       True\n",
       "2      False\n",
       "3       True\n",
       "4       True\n",
       "       ...  \n",
       "995    False\n",
       "996     True\n",
       "997     True\n",
       "998     True\n",
       "999     True\n",
       "Name: Gender, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Gender\"] == \"Male\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7147ba81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2022-12-06 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2022-12-06 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2022-12-06 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2022-12-06 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>424 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas   Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1       Thomas   Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "3        Jerry   Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4        Larry   Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "5       Dennis   Male 1987-04-18 2022-12-06 01:35:00  115163   10.125   \n",
       "..         ...    ...        ...                 ...     ...      ...   \n",
       "994     George   Male 2013-06-21 2022-12-06 17:47:00   98874    4.479   \n",
       "996    Phillip   Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "997    Russell   Male 2013-05-20 2022-12-06 12:39:00   96914    1.421   \n",
       "998      Larry   Male 2013-04-20 2022-12-06 16:45:00   60500   11.985   \n",
       "999     Albert   Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "0                 True             Marketing  \n",
       "1                 True                   NaN  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "5                False                 Legal  \n",
       "..                 ...                   ...  \n",
       "994               True             Marketing  \n",
       "996              False               Finance  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[424 rows x 8 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Gender\"] == \"Male\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0de43287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ruby</td>\n",
       "      <td>Female</td>\n",
       "      <td>1987-08-17</td>\n",
       "      <td>2022-12-06 16:20:00</td>\n",
       "      <td>65476</td>\n",
       "      <td>10.012</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>Rose</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-08-25</td>\n",
       "      <td>2022-12-06 05:12:00</td>\n",
       "      <td>134505</td>\n",
       "      <td>11.051</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2022-12-06 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>Tina</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997-05-15</td>\n",
       "      <td>2022-12-06 15:53:00</td>\n",
       "      <td>56450</td>\n",
       "      <td>19.040</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2022-12-06 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>535 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1       Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "3        Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4        Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "6         Ruby  Female 1987-08-17 2022-12-06 16:20:00   65476   10.012   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "991       Rose  Female 2002-08-25 2022-12-06 05:12:00  134505   11.051   \n",
       "992    Anthony    Male 2011-10-16 2022-12-06 08:35:00  112769   11.625   \n",
       "993       Tina  Female 1997-05-15 2022-12-06 15:53:00   56450   19.040   \n",
       "994     George    Male 2013-06-21 2022-12-06 17:47:00   98874    4.479   \n",
       "999     Albert    Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management             Team  \n",
       "0                 True        Marketing  \n",
       "1                 True              NaN  \n",
       "3                 True          Finance  \n",
       "4                 True  Client Services  \n",
       "6                 True          Product  \n",
       "..                 ...              ...  \n",
       "991               True        Marketing  \n",
       "992               True          Finance  \n",
       "993               True      Engineering  \n",
       "994               True        Marketing  \n",
       "999               True            Sales  \n",
       "\n",
       "[535 rows x 8 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = df[\"Senior Management\"]\n",
    "df[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c8f08481",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-07-20</td>\n",
       "      <td>2022-12-06 10:43:00</td>\n",
       "      <td>45906</td>\n",
       "      <td>11.598</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Angela</td>\n",
       "      <td>Female</td>\n",
       "      <td>2005-11-22</td>\n",
       "      <td>2022-12-06 06:29:00</td>\n",
       "      <td>95570</td>\n",
       "      <td>18.523</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2022-12-06 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>Henry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>2022-12-06 06:09:00</td>\n",
       "      <td>132483</td>\n",
       "      <td>16.655</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2022-12-06 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2022-12-06 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>670 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "1       Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "3        Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4        Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "7          NaN  Female 2015-07-20 2022-12-06 10:43:00   45906   11.598   \n",
       "8       Angela  Female 2005-11-22 2022-12-06 06:29:00   95570   18.523   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "994     George    Male 2013-06-21 2022-12-06 17:47:00   98874    4.479   \n",
       "995      Henry     NaN 2014-11-23 2022-12-06 06:09:00  132483   16.655   \n",
       "997    Russell    Male 2013-05-20 2022-12-06 12:39:00   96914    1.421   \n",
       "998      Larry    Male 2013-04-20 2022-12-06 16:45:00   60500   11.985   \n",
       "999     Albert    Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "1                 True                   NaN  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "7                 True               Finance  \n",
       "8                 True           Engineering  \n",
       "..                 ...                   ...  \n",
       "994               True             Marketing  \n",
       "995              False          Distribution  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[670 rows x 8 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Start Date\"] > \"1993-08-06\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa1afc88",
   "metadata": {},
   "source": [
    "# Filter DataFrame with more than one condition (AND-&)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0c4e742b",
   "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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2      Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4      Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "\n",
       "   Senior Management             Team  \n",
       "0               True        Marketing  \n",
       "1               True              NaN  \n",
       "2              False          Finance  \n",
       "3               True          Finance  \n",
       "4               True  Client Services  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Last Login Time\", \"Start Date\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ed7e5d42",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
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       "      <th>Team</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
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       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Bruce</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-11-28</td>\n",
       "      <td>2022-12-06 22:47:00</td>\n",
       "      <td>114796</td>\n",
       "      <td>6.796</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Carl</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-05-03</td>\n",
       "      <td>2022-12-06 17:55:00</td>\n",
       "      <td>130276</td>\n",
       "      <td>16.084</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Jose</td>\n",
       "      <td>Male</td>\n",
       "      <td>2004-10-30</td>\n",
       "      <td>2022-12-06 13:39:00</td>\n",
       "      <td>84834</td>\n",
       "      <td>14.330</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Shawn</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-09-23</td>\n",
       "      <td>2022-12-06 02:55:00</td>\n",
       "      <td>148115</td>\n",
       "      <td>6.539</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Steven</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-03-01</td>\n",
       "      <td>2022-12-06 15:03:00</td>\n",
       "      <td>109095</td>\n",
       "      <td>9.494</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-08-12</td>\n",
       "      <td>2022-12-06 00:04:00</td>\n",
       "      <td>89661</td>\n",
       "      <td>8.525</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>Brandon</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-03-27</td>\n",
       "      <td>2022-12-06 17:54:00</td>\n",
       "      <td>115711</td>\n",
       "      <td>8.012</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>Billy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-03-13</td>\n",
       "      <td>2022-12-06 12:05:00</td>\n",
       "      <td>120444</td>\n",
       "      <td>7.768</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>Jason</td>\n",
       "      <td>Male</td>\n",
       "      <td>1999-10-17</td>\n",
       "      <td>2022-12-06 22:09:00</td>\n",
       "      <td>78417</td>\n",
       "      <td>3.067</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>Walter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1983-07-06</td>\n",
       "      <td>2022-12-06 23:54:00</td>\n",
       "      <td>127813</td>\n",
       "      <td>5.961</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>Todd</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-02-02</td>\n",
       "      <td>2022-12-06 10:13:00</td>\n",
       "      <td>69989</td>\n",
       "      <td>10.985</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1981-08-12</td>\n",
       "      <td>2022-12-06 00:05:00</td>\n",
       "      <td>46930</td>\n",
       "      <td>18.702</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>Roy</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-08-06</td>\n",
       "      <td>2022-12-06 07:52:00</td>\n",
       "      <td>148225</td>\n",
       "      <td>1.841</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-12-19</td>\n",
       "      <td>2022-12-06 02:54:00</td>\n",
       "      <td>76076</td>\n",
       "      <td>5.319</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335</th>\n",
       "      <td>Robert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2014-11-18</td>\n",
       "      <td>2022-12-06 05:00:00</td>\n",
       "      <td>85799</td>\n",
       "      <td>19.930</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>Carlos</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-09-19</td>\n",
       "      <td>2022-12-06 01:01:00</td>\n",
       "      <td>77327</td>\n",
       "      <td>11.580</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>Philip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-08-02</td>\n",
       "      <td>2022-12-06 11:21:00</td>\n",
       "      <td>129968</td>\n",
       "      <td>19.897</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>Justin</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-05-22</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>121508</td>\n",
       "      <td>19.334</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>Christopher</td>\n",
       "      <td>Male</td>\n",
       "      <td>1999-05-13</td>\n",
       "      <td>2022-12-06 10:48:00</td>\n",
       "      <td>68028</td>\n",
       "      <td>7.869</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-09-30</td>\n",
       "      <td>2022-12-06 17:34:00</td>\n",
       "      <td>102626</td>\n",
       "      <td>15.843</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-11-01</td>\n",
       "      <td>2022-12-06 23:31:00</td>\n",
       "      <td>44857</td>\n",
       "      <td>13.266</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1982-11-19</td>\n",
       "      <td>2022-12-06 11:25:00</td>\n",
       "      <td>59277</td>\n",
       "      <td>10.200</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>618</th>\n",
       "      <td>Peter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-11-24</td>\n",
       "      <td>2022-12-06 17:43:00</td>\n",
       "      <td>69297</td>\n",
       "      <td>1.268</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <td>Ralph</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-03-07</td>\n",
       "      <td>2022-12-06 02:25:00</td>\n",
       "      <td>81215</td>\n",
       "      <td>8.400</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>685</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-10-20</td>\n",
       "      <td>2022-12-06 09:37:00</td>\n",
       "      <td>88086</td>\n",
       "      <td>19.387</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>Edward</td>\n",
       "      <td>Male</td>\n",
       "      <td>1997-11-27</td>\n",
       "      <td>2022-12-06 01:00:00</td>\n",
       "      <td>58327</td>\n",
       "      <td>17.095</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-05-19</td>\n",
       "      <td>2022-12-06 13:40:00</td>\n",
       "      <td>131513</td>\n",
       "      <td>1.876</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>Henry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-05-12</td>\n",
       "      <td>2022-12-06 02:04:00</td>\n",
       "      <td>59943</td>\n",
       "      <td>1.432</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-10-24</td>\n",
       "      <td>2022-12-06 09:23:00</td>\n",
       "      <td>47176</td>\n",
       "      <td>10.736</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>790</th>\n",
       "      <td>Fred</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-03-03</td>\n",
       "      <td>2022-12-06 02:27:00</td>\n",
       "      <td>129712</td>\n",
       "      <td>11.058</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>809</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-09-27</td>\n",
       "      <td>2022-12-06 17:04:00</td>\n",
       "      <td>36749</td>\n",
       "      <td>19.754</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>831</th>\n",
       "      <td>Kenneth</td>\n",
       "      <td>Male</td>\n",
       "      <td>2015-01-15</td>\n",
       "      <td>2022-12-06 14:41:00</td>\n",
       "      <td>69112</td>\n",
       "      <td>7.588</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>Male</td>\n",
       "      <td>1985-05-23</td>\n",
       "      <td>2022-12-06 22:16:00</td>\n",
       "      <td>139570</td>\n",
       "      <td>15.804</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1985-02-10</td>\n",
       "      <td>2022-12-06 19:46:00</td>\n",
       "      <td>63046</td>\n",
       "      <td>10.411</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>861</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-03-26</td>\n",
       "      <td>2022-12-06 04:15:00</td>\n",
       "      <td>140850</td>\n",
       "      <td>18.855</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2015-11-24</td>\n",
       "      <td>2022-12-06 03:11:00</td>\n",
       "      <td>145329</td>\n",
       "      <td>7.100</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>Timothy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-08-25</td>\n",
       "      <td>2022-12-06 10:37:00</td>\n",
       "      <td>92587</td>\n",
       "      <td>8.475</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>954</th>\n",
       "      <td>Joe</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-01-19</td>\n",
       "      <td>2022-12-06 16:06:00</td>\n",
       "      <td>119667</td>\n",
       "      <td>1.148</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2022-12-06 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      First Name Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "3          Jerry   Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "46         Bruce   Male 2009-11-28 2022-12-06 22:47:00  114796    6.796   \n",
       "56          Carl   Male 2006-05-03 2022-12-06 17:55:00  130276   16.084   \n",
       "68          Jose   Male 2004-10-30 2022-12-06 13:39:00   84834   14.330   \n",
       "83         Shawn   Male 2005-09-23 2022-12-06 02:55:00  148115    6.539   \n",
       "117       Steven   Male 1995-03-01 2022-12-06 15:03:00  109095    9.494   \n",
       "200         Gary   Male 1987-08-12 2022-12-06 00:04:00   89661    8.525   \n",
       "205      Brandon   Male 2006-03-27 2022-12-06 17:54:00  115711    8.012   \n",
       "219        Billy   Male 1995-03-13 2022-12-06 12:05:00  120444    7.768   \n",
       "222        Jason   Male 1999-10-17 2022-12-06 22:09:00   78417    3.067   \n",
       "241       Walter   Male 1983-07-06 2022-12-06 23:54:00  127813    5.961   \n",
       "286         Todd   Male 1984-02-02 2022-12-06 10:13:00   69989   10.985   \n",
       "304       Jeremy   Male 1981-08-12 2022-12-06 00:05:00   46930   18.702   \n",
       "318          Roy   Male 2006-08-06 2022-12-06 07:52:00  148225    1.841   \n",
       "328       Samuel   Male 1991-12-19 2022-12-06 02:54:00   76076    5.319   \n",
       "335       Robert   Male 2014-11-18 2022-12-06 05:00:00   85799   19.930   \n",
       "341       Carlos   Male 2007-09-19 2022-12-06 01:01:00   77327   11.580   \n",
       "348       Philip   Male 1989-08-02 2022-12-06 11:21:00  129968   19.897   \n",
       "420       Justin   Male 1986-05-22 2022-12-06 06:30:00  121508   19.334   \n",
       "428  Christopher   Male 1999-05-13 2022-12-06 10:48:00   68028    7.869   \n",
       "458       Albert   Male 2007-09-30 2022-12-06 17:34:00  102626   15.843   \n",
       "493        Craig   Male 2005-11-01 2022-12-06 23:31:00   44857   13.266   \n",
       "582        Harry   Male 1982-11-19 2022-12-06 11:25:00   59277   10.200   \n",
       "618        Peter   Male 1992-11-24 2022-12-06 17:43:00   69297    1.268   \n",
       "620        Ralph   Male 2012-03-07 2022-12-06 02:25:00   81215    8.400   \n",
       "685          NaN   Male 1989-10-20 2022-12-06 09:37:00   88086   19.387   \n",
       "710       Edward   Male 1997-11-27 2022-12-06 01:00:00   58327   17.095   \n",
       "725       Jeremy   Male 1991-05-19 2022-12-06 13:40:00  131513    1.876   \n",
       "732        Henry   Male 1986-05-12 2022-12-06 02:04:00   59943    1.432   \n",
       "773          NaN   Male 1986-10-24 2022-12-06 09:23:00   47176   10.736   \n",
       "790         Fred   Male 1989-03-03 2022-12-06 02:27:00  129712   11.058   \n",
       "809       George   Male 1995-09-27 2022-12-06 17:04:00   36749   19.754   \n",
       "831      Kenneth   Male 2015-01-15 2022-12-06 14:41:00   69112    7.588   \n",
       "837       Joseph   Male 1985-05-23 2022-12-06 22:16:00  139570   15.804   \n",
       "854        Harry   Male 1985-02-10 2022-12-06 19:46:00   63046   10.411   \n",
       "861        Jerry   Male 1989-03-26 2022-12-06 04:15:00  140850   18.855   \n",
       "890          NaN   Male 2015-11-24 2022-12-06 03:11:00  145329    7.100   \n",
       "891      Timothy   Male 1991-08-25 2022-12-06 10:37:00   92587    8.475   \n",
       "954          Joe   Male 1980-01-19 2022-12-06 16:06:00  119667    1.148   \n",
       "992      Anthony   Male 2011-10-16 2022-12-06 08:35:00  112769   11.625   \n",
       "996      Phillip   Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "\n",
       "     Senior Management     Team  \n",
       "3                 True  Finance  \n",
       "46               False  Finance  \n",
       "56                True  Finance  \n",
       "68                True  Finance  \n",
       "83                True  Finance  \n",
       "117              False  Finance  \n",
       "200              False  Finance  \n",
       "205               True  Finance  \n",
       "219               True  Finance  \n",
       "222              False  Finance  \n",
       "241              False  Finance  \n",
       "286               True  Finance  \n",
       "304               True  Finance  \n",
       "318              False  Finance  \n",
       "328               True  Finance  \n",
       "335              False  Finance  \n",
       "341               True  Finance  \n",
       "348              False  Finance  \n",
       "420               True  Finance  \n",
       "428               True  Finance  \n",
       "458              False  Finance  \n",
       "493              False  Finance  \n",
       "582              False  Finance  \n",
       "618              False  Finance  \n",
       "620              False  Finance  \n",
       "685               True  Finance  \n",
       "710               True  Finance  \n",
       "725               True  Finance  \n",
       "732              False  Finance  \n",
       "773               True  Finance  \n",
       "790              False  Finance  \n",
       "809              False  Finance  \n",
       "831               True  Finance  \n",
       "837               True  Finance  \n",
       "854              False  Finance  \n",
       "861              False  Finance  \n",
       "890               True  Finance  \n",
       "891              False  Finance  \n",
       "954               True  Finance  \n",
       "992               True  Finance  \n",
       "996              False  Finance  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask1 = df[\"Gender\"] == \"Male\"\n",
    "mask2 = df[\"Team\"] == \"Finance\"\n",
    "df[mask1 & mask2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "623d6f65",
   "metadata": {},
   "source": [
    "# Filter DataFrame with more than one condition (OR-|)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "05e24d05",
   "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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2022-12-06 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2022-12-06 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2022-12-06 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>485 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1       Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2        Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3        Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4        Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "994     George    Male 2013-06-21 2022-12-06 17:47:00   98874    4.479   \n",
       "996    Phillip    Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "997    Russell    Male 2013-05-20 2022-12-06 12:39:00   96914    1.421   \n",
       "998      Larry    Male 2013-04-20 2022-12-06 16:45:00   60500   11.985   \n",
       "999     Albert    Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "0                 True             Marketing  \n",
       "1                 True                   NaN  \n",
       "2                False               Finance  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "..                 ...                   ...  \n",
       "994               True             Marketing  \n",
       "996              False               Finance  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[485 rows x 8 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask1 = df[\"Gender\"] == \"Male\"\n",
    "mask2 = df[\"Team\"] == \"Finance\"\n",
    "df[mask1 | mask2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2d7f7f52",
   "metadata": {
    "scrolled": true
   },
   "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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lillian</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016-06-05</td>\n",
       "      <td>2022-12-06 06:09:00</td>\n",
       "      <td>59414</td>\n",
       "      <td>1.256</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Bruce</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-11-28</td>\n",
       "      <td>2022-12-06 22:47:00</td>\n",
       "      <td>114796</td>\n",
       "      <td>6.796</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Carl</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-05-03</td>\n",
       "      <td>2022-12-06 17:55:00</td>\n",
       "      <td>130276</td>\n",
       "      <td>16.084</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Jose</td>\n",
       "      <td>Male</td>\n",
       "      <td>2004-10-30</td>\n",
       "      <td>2022-12-06 13:39:00</td>\n",
       "      <td>84834</td>\n",
       "      <td>14.330</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Shawn</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-09-23</td>\n",
       "      <td>2022-12-06 02:55:00</td>\n",
       "      <td>148115</td>\n",
       "      <td>6.539</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Tina</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016-06-16</td>\n",
       "      <td>2022-12-06 19:47:00</td>\n",
       "      <td>100705</td>\n",
       "      <td>16.961</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Steven</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-03-01</td>\n",
       "      <td>2022-12-06 15:03:00</td>\n",
       "      <td>109095</td>\n",
       "      <td>9.494</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-08-12</td>\n",
       "      <td>2022-12-06 00:04:00</td>\n",
       "      <td>89661</td>\n",
       "      <td>8.525</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>Brandon</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-03-27</td>\n",
       "      <td>2022-12-06 17:54:00</td>\n",
       "      <td>115711</td>\n",
       "      <td>8.012</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>Billy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-03-13</td>\n",
       "      <td>2022-12-06 12:05:00</td>\n",
       "      <td>120444</td>\n",
       "      <td>7.768</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>Jason</td>\n",
       "      <td>Male</td>\n",
       "      <td>1999-10-17</td>\n",
       "      <td>2022-12-06 22:09:00</td>\n",
       "      <td>78417</td>\n",
       "      <td>3.067</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>Walter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1983-07-06</td>\n",
       "      <td>2022-12-06 23:54:00</td>\n",
       "      <td>127813</td>\n",
       "      <td>5.961</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>Todd</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-02-02</td>\n",
       "      <td>2022-12-06 10:13:00</td>\n",
       "      <td>69989</td>\n",
       "      <td>10.985</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1981-08-12</td>\n",
       "      <td>2022-12-06 00:05:00</td>\n",
       "      <td>46930</td>\n",
       "      <td>18.702</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>Roy</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-08-06</td>\n",
       "      <td>2022-12-06 07:52:00</td>\n",
       "      <td>148225</td>\n",
       "      <td>1.841</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-12-19</td>\n",
       "      <td>2022-12-06 02:54:00</td>\n",
       "      <td>76076</td>\n",
       "      <td>5.319</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335</th>\n",
       "      <td>Robert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2014-11-18</td>\n",
       "      <td>2022-12-06 05:00:00</td>\n",
       "      <td>85799</td>\n",
       "      <td>19.930</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>Carlos</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-09-19</td>\n",
       "      <td>2022-12-06 01:01:00</td>\n",
       "      <td>77327</td>\n",
       "      <td>11.580</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>Philip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-08-02</td>\n",
       "      <td>2022-12-06 11:21:00</td>\n",
       "      <td>129968</td>\n",
       "      <td>19.897</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>Justin</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-05-22</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>121508</td>\n",
       "      <td>19.334</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>Christopher</td>\n",
       "      <td>Male</td>\n",
       "      <td>1999-05-13</td>\n",
       "      <td>2022-12-06 10:48:00</td>\n",
       "      <td>68028</td>\n",
       "      <td>7.869</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>Terry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-15</td>\n",
       "      <td>2022-12-06 00:29:00</td>\n",
       "      <td>140002</td>\n",
       "      <td>19.490</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-09-30</td>\n",
       "      <td>2022-12-06 17:34:00</td>\n",
       "      <td>102626</td>\n",
       "      <td>15.843</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-11-01</td>\n",
       "      <td>2022-12-06 23:31:00</td>\n",
       "      <td>44857</td>\n",
       "      <td>13.266</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1982-11-19</td>\n",
       "      <td>2022-12-06 11:25:00</td>\n",
       "      <td>59277</td>\n",
       "      <td>10.200</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>618</th>\n",
       "      <td>Peter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-11-24</td>\n",
       "      <td>2022-12-06 17:43:00</td>\n",
       "      <td>69297</td>\n",
       "      <td>1.268</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <td>Ralph</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-03-07</td>\n",
       "      <td>2022-12-06 02:25:00</td>\n",
       "      <td>81215</td>\n",
       "      <td>8.400</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>685</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-10-20</td>\n",
       "      <td>2022-12-06 09:37:00</td>\n",
       "      <td>88086</td>\n",
       "      <td>19.387</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>Edward</td>\n",
       "      <td>Male</td>\n",
       "      <td>1997-11-27</td>\n",
       "      <td>2022-12-06 01:00:00</td>\n",
       "      <td>58327</td>\n",
       "      <td>17.095</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-05-19</td>\n",
       "      <td>2022-12-06 13:40:00</td>\n",
       "      <td>131513</td>\n",
       "      <td>1.876</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>Henry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-05-12</td>\n",
       "      <td>2022-12-06 02:04:00</td>\n",
       "      <td>59943</td>\n",
       "      <td>1.432</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-10-24</td>\n",
       "      <td>2022-12-06 09:23:00</td>\n",
       "      <td>47176</td>\n",
       "      <td>10.736</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>790</th>\n",
       "      <td>Fred</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-03-03</td>\n",
       "      <td>2022-12-06 02:27:00</td>\n",
       "      <td>129712</td>\n",
       "      <td>11.058</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>809</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-09-27</td>\n",
       "      <td>2022-12-06 17:04:00</td>\n",
       "      <td>36749</td>\n",
       "      <td>19.754</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>831</th>\n",
       "      <td>Kenneth</td>\n",
       "      <td>Male</td>\n",
       "      <td>2015-01-15</td>\n",
       "      <td>2022-12-06 14:41:00</td>\n",
       "      <td>69112</td>\n",
       "      <td>7.588</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>Male</td>\n",
       "      <td>1985-05-23</td>\n",
       "      <td>2022-12-06 22:16:00</td>\n",
       "      <td>139570</td>\n",
       "      <td>15.804</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1985-02-10</td>\n",
       "      <td>2022-12-06 19:46:00</td>\n",
       "      <td>63046</td>\n",
       "      <td>10.411</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>861</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-03-26</td>\n",
       "      <td>2022-12-06 04:15:00</td>\n",
       "      <td>140850</td>\n",
       "      <td>18.855</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2015-11-24</td>\n",
       "      <td>2022-12-06 03:11:00</td>\n",
       "      <td>145329</td>\n",
       "      <td>7.100</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>Timothy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-08-25</td>\n",
       "      <td>2022-12-06 10:37:00</td>\n",
       "      <td>92587</td>\n",
       "      <td>8.475</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>954</th>\n",
       "      <td>Joe</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-01-19</td>\n",
       "      <td>2022-12-06 16:06:00</td>\n",
       "      <td>119667</td>\n",
       "      <td>1.148</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2022-12-06 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "3          Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "15       Lillian  Female 2016-06-05 2022-12-06 06:09:00   59414    1.256   \n",
       "46         Bruce    Male 2009-11-28 2022-12-06 22:47:00  114796    6.796   \n",
       "56          Carl    Male 2006-05-03 2022-12-06 17:55:00  130276   16.084   \n",
       "68          Jose    Male 2004-10-30 2022-12-06 13:39:00   84834   14.330   \n",
       "83         Shawn    Male 2005-09-23 2022-12-06 02:55:00  148115    6.539   \n",
       "98          Tina  Female 2016-06-16 2022-12-06 19:47:00  100705   16.961   \n",
       "117       Steven    Male 1995-03-01 2022-12-06 15:03:00  109095    9.494   \n",
       "200         Gary    Male 1987-08-12 2022-12-06 00:04:00   89661    8.525   \n",
       "205      Brandon    Male 2006-03-27 2022-12-06 17:54:00  115711    8.012   \n",
       "219        Billy    Male 1995-03-13 2022-12-06 12:05:00  120444    7.768   \n",
       "222        Jason    Male 1999-10-17 2022-12-06 22:09:00   78417    3.067   \n",
       "241       Walter    Male 1983-07-06 2022-12-06 23:54:00  127813    5.961   \n",
       "286         Todd    Male 1984-02-02 2022-12-06 10:13:00   69989   10.985   \n",
       "304       Jeremy    Male 1981-08-12 2022-12-06 00:05:00   46930   18.702   \n",
       "318          Roy    Male 2006-08-06 2022-12-06 07:52:00  148225    1.841   \n",
       "328       Samuel    Male 1991-12-19 2022-12-06 02:54:00   76076    5.319   \n",
       "335       Robert    Male 2014-11-18 2022-12-06 05:00:00   85799   19.930   \n",
       "341       Carlos    Male 2007-09-19 2022-12-06 01:01:00   77327   11.580   \n",
       "348       Philip    Male 1989-08-02 2022-12-06 11:21:00  129968   19.897   \n",
       "420       Justin    Male 1986-05-22 2022-12-06 06:30:00  121508   19.334   \n",
       "428  Christopher    Male 1999-05-13 2022-12-06 10:48:00   68028    7.869   \n",
       "451        Terry     NaN 2016-07-15 2022-12-06 00:29:00  140002   19.490   \n",
       "458       Albert    Male 2007-09-30 2022-12-06 17:34:00  102626   15.843   \n",
       "493        Craig    Male 2005-11-01 2022-12-06 23:31:00   44857   13.266   \n",
       "582        Harry    Male 1982-11-19 2022-12-06 11:25:00   59277   10.200   \n",
       "618        Peter    Male 1992-11-24 2022-12-06 17:43:00   69297    1.268   \n",
       "620        Ralph    Male 2012-03-07 2022-12-06 02:25:00   81215    8.400   \n",
       "685          NaN    Male 1989-10-20 2022-12-06 09:37:00   88086   19.387   \n",
       "710       Edward    Male 1997-11-27 2022-12-06 01:00:00   58327   17.095   \n",
       "725       Jeremy    Male 1991-05-19 2022-12-06 13:40:00  131513    1.876   \n",
       "732        Henry    Male 1986-05-12 2022-12-06 02:04:00   59943    1.432   \n",
       "773          NaN    Male 1986-10-24 2022-12-06 09:23:00   47176   10.736   \n",
       "790         Fred    Male 1989-03-03 2022-12-06 02:27:00  129712   11.058   \n",
       "809       George    Male 1995-09-27 2022-12-06 17:04:00   36749   19.754   \n",
       "831      Kenneth    Male 2015-01-15 2022-12-06 14:41:00   69112    7.588   \n",
       "837       Joseph    Male 1985-05-23 2022-12-06 22:16:00  139570   15.804   \n",
       "854        Harry    Male 1985-02-10 2022-12-06 19:46:00   63046   10.411   \n",
       "861        Jerry    Male 1989-03-26 2022-12-06 04:15:00  140850   18.855   \n",
       "890          NaN    Male 2015-11-24 2022-12-06 03:11:00  145329    7.100   \n",
       "891      Timothy    Male 1991-08-25 2022-12-06 10:37:00   92587    8.475   \n",
       "954          Joe    Male 1980-01-19 2022-12-06 16:06:00  119667    1.148   \n",
       "992      Anthony    Male 2011-10-16 2022-12-06 08:35:00  112769   11.625   \n",
       "996      Phillip    Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "\n",
       "     Senior Management       Team  \n",
       "3                 True    Finance  \n",
       "15               False    Product  \n",
       "46               False    Finance  \n",
       "56                True    Finance  \n",
       "68                True    Finance  \n",
       "83                True    Finance  \n",
       "98                True  Marketing  \n",
       "117              False    Finance  \n",
       "200              False    Finance  \n",
       "205               True    Finance  \n",
       "219               True    Finance  \n",
       "222              False    Finance  \n",
       "241              False    Finance  \n",
       "286               True    Finance  \n",
       "304               True    Finance  \n",
       "318              False    Finance  \n",
       "328               True    Finance  \n",
       "335              False    Finance  \n",
       "341               True    Finance  \n",
       "348              False    Finance  \n",
       "420               True    Finance  \n",
       "428               True    Finance  \n",
       "451               True  Marketing  \n",
       "458              False    Finance  \n",
       "493              False    Finance  \n",
       "582              False    Finance  \n",
       "618              False    Finance  \n",
       "620              False    Finance  \n",
       "685               True    Finance  \n",
       "710               True    Finance  \n",
       "725               True    Finance  \n",
       "732              False    Finance  \n",
       "773               True    Finance  \n",
       "790              False    Finance  \n",
       "809              False    Finance  \n",
       "831               True    Finance  \n",
       "837               True    Finance  \n",
       "854              False    Finance  \n",
       "861              False    Finance  \n",
       "890               True    Finance  \n",
       "891              False    Finance  \n",
       "954               True    Finance  \n",
       "992               True    Finance  \n",
       "996              False    Finance  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask1 = df[\"Gender\"] == \"Male\"\n",
    "mask2 = df[\"Team\"] == \"Finance\"\n",
    "mask3 = df[\"Start Date\"] > \"2016-06-01\"\n",
    "df[(mask1 & mask2) | mask3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c08d9c2",
   "metadata": {},
   "source": [
    "# isin() Mehod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1fe7ae7c",
   "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",
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       "    }\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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2      Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4      Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "\n",
       "   Senior Management             Team  \n",
       "0               True        Marketing  \n",
       "1               True              NaN  \n",
       "2              False          Finance  \n",
       "3               True          Finance  \n",
       "4               True  Client Services  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Start Date\", \"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4f7ff60e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       True\n",
       "1      False\n",
       "2       True\n",
       "3       True\n",
       "4      False\n",
       "       ...  \n",
       "995    False\n",
       "996     True\n",
       "997    False\n",
       "998    False\n",
       "999     True\n",
       "Name: Team, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Team\"].isin([\"Marketing\", \"Finance\", \"Sales\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "39ff6aec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-07-20</td>\n",
       "      <td>2022-12-06 10:43:00</td>\n",
       "      <td>45906</td>\n",
       "      <td>11.598</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-01-27</td>\n",
       "      <td>2022-12-06 23:40:00</td>\n",
       "      <td>109831</td>\n",
       "      <td>5.831</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>Rose</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-08-25</td>\n",
       "      <td>2022-12-06 05:12:00</td>\n",
       "      <td>134505</td>\n",
       "      <td>11.051</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2022-12-06 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2022-12-06 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>294 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "2        Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3        Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "7          NaN  Female 2015-07-20 2022-12-06 10:43:00   45906   11.598   \n",
       "13        Gary    Male 2008-01-27 2022-12-06 23:40:00  109831    5.831   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "991       Rose  Female 2002-08-25 2022-12-06 05:12:00  134505   11.051   \n",
       "992    Anthony    Male 2011-10-16 2022-12-06 08:35:00  112769   11.625   \n",
       "994     George    Male 2013-06-21 2022-12-06 17:47:00   98874    4.479   \n",
       "996    Phillip    Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "999     Albert    Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management       Team  \n",
       "0                 True  Marketing  \n",
       "2                False    Finance  \n",
       "3                 True    Finance  \n",
       "7                 True    Finance  \n",
       "13               False      Sales  \n",
       "..                 ...        ...  \n",
       "991               True  Marketing  \n",
       "992               True    Finance  \n",
       "994               True  Marketing  \n",
       "996              False    Finance  \n",
       "999               True      Sales  \n",
       "\n",
       "[294 rows x 8 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = df[\"Team\"].isin([\"Marketing\", \"Finance\", \"Sales\"])\n",
    "df[mask]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "952f9ef5",
   "metadata": {},
   "source": [
    "# isnull() & notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "73875d52",
   "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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2      Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4      Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "\n",
       "   Senior Management             Team  \n",
       "0               True        Marketing  \n",
       "1               True              NaN  \n",
       "2              False          Finance  \n",
       "3               True          Finance  \n",
       "4               True  Client Services  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Start Date\", \"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a75047eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1       True\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "995    False\n",
       "996    False\n",
       "997    False\n",
       "998    False\n",
       "999    False\n",
       "Name: Team, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Team\"].isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5f990f4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       True\n",
       "1      False\n",
       "2       True\n",
       "3       True\n",
       "4       True\n",
       "       ...  \n",
       "995     True\n",
       "996     True\n",
       "997     True\n",
       "998     True\n",
       "999     True\n",
       "Name: Team, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Team\"].notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fb6ea847",
   "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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2022-12-06 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>Henry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>2022-12-06 06:09:00</td>\n",
       "      <td>132483</td>\n",
       "      <td>16.655</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2022-12-06 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2022-12-06 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2022-12-06 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2022-12-06 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>957 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "2        Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3        Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4        Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "5       Dennis    Male 1987-04-18 2022-12-06 01:35:00  115163   10.125   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "995      Henry     NaN 2014-11-23 2022-12-06 06:09:00  132483   16.655   \n",
       "996    Phillip    Male 1984-01-31 2022-12-06 06:30:00   42392   19.675   \n",
       "997    Russell    Male 2013-05-20 2022-12-06 12:39:00   96914    1.421   \n",
       "998      Larry    Male 2013-04-20 2022-12-06 16:45:00   60500   11.985   \n",
       "999     Albert    Male 2012-05-15 2022-12-06 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "0                 True             Marketing  \n",
       "2                False               Finance  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "5                False                 Legal  \n",
       "..                 ...                   ...  \n",
       "995              False          Distribution  \n",
       "996              False               Finance  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[957 rows x 8 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Team\"].notnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eae43ab6",
   "metadata": {},
   "source": [
    "# between()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "13e64a05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "        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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2022-12-06 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2022-12-06 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2022-12-06 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2022-12-06 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0    Douglas    Male 1993-08-06 2022-12-06 12:42:00   97308    6.945   \n",
       "1     Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "2      Maria  Female 1993-04-23 2022-12-06 11:17:00  130590   11.858   \n",
       "3      Jerry    Male 2005-03-04 2022-12-06 13:00:00  138705    9.340   \n",
       "4      Larry    Male 1998-01-24 2022-12-06 16:47:00  101004    1.389   \n",
       "\n",
       "   Senior Management             Team  \n",
       "0               True        Marketing  \n",
       "1               True              NaN  \n",
       "2              False          Finance  \n",
       "3               True          Finance  \n",
       "4               True  Client Services  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Start Date\", \"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "42da969a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1       True\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "995    False\n",
       "996    False\n",
       "997    False\n",
       "998     True\n",
       "999    False\n",
       "Name: Salary, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Salary\"].between(60000, 70000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9e268f2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2022-12-06 06:53:00</td>\n",
       "      <td>61933</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ruby</td>\n",
       "      <td>Female</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Louise</td>\n",
       "      <td>Female</td>\n",
       "      <td>1980-08-12</td>\n",
       "      <td>2022-12-06 09:01:00</td>\n",
       "      <td>63241</td>\n",
       "      <td>15.132</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Lois</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995-04-22</td>\n",
       "      <td>2022-12-06 19:18:00</td>\n",
       "      <td>64714</td>\n",
       "      <td>4.934</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Christine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-06-28</td>\n",
       "      <td>2022-12-06 01:08:00</td>\n",
       "      <td>66582</td>\n",
       "      <td>11.308</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>Catherine</td>\n",
       "      <td>Female</td>\n",
       "      <td>1989-09-25</td>\n",
       "      <td>2022-12-06 01:31:00</td>\n",
       "      <td>68164</td>\n",
       "      <td>18.393</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>Alice</td>\n",
       "      <td>Female</td>\n",
       "      <td>1988-09-03</td>\n",
       "      <td>2022-12-06 20:54:00</td>\n",
       "      <td>63571</td>\n",
       "      <td>15.397</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-08-30</td>\n",
       "      <td>2022-12-06 18:31:00</td>\n",
       "      <td>67656</td>\n",
       "      <td>16.455</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>Sean</td>\n",
       "      <td>Male</td>\n",
       "      <td>1983-01-17</td>\n",
       "      <td>2022-12-06 14:23:00</td>\n",
       "      <td>66146</td>\n",
       "      <td>11.178</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2022-12-06 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>86 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "1       Thomas    Male 1996-03-31 2022-12-06 06:53:00   61933    4.170   \n",
       "6         Ruby  Female 1987-08-17 2022-12-06 16:20:00   65476   10.012   \n",
       "10      Louise  Female 1980-08-12 2022-12-06 09:01:00   63241   15.132   \n",
       "20        Lois     NaN 1995-04-22 2022-12-06 19:18:00   64714    4.934   \n",
       "41   Christine     NaN 2015-06-28 2022-12-06 01:08:00   66582   11.308   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "965  Catherine  Female 1989-09-25 2022-12-06 01:31:00   68164   18.393   \n",
       "970      Alice  Female 1988-09-03 2022-12-06 20:54:00   63571   15.397   \n",
       "974      Harry    Male 2011-08-30 2022-12-06 18:31:00   67656   16.455   \n",
       "978       Sean    Male 1983-01-17 2022-12-06 14:23:00   66146   11.178   \n",
       "998      Larry    Male 2013-04-20 2022-12-06 16:45:00   60500   11.985   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "1                 True                   NaN  \n",
       "6                 True               Product  \n",
       "10                True                   NaN  \n",
       "20                True                 Legal  \n",
       "41                True  Business Development  \n",
       "..                 ...                   ...  \n",
       "965              False       Client Services  \n",
       "970               True               Product  \n",
       "974               True       Client Services  \n",
       "978              False       Human Resources  \n",
       "998              False  Business Development  \n",
       "\n",
       "[86 rows x 8 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Salary\"].between(60000, 70000)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3dbc12a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Scott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-07-11</td>\n",
       "      <td>2022-12-06 18:58:00</td>\n",
       "      <td>122367</td>\n",
       "      <td>5.218</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
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       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Bonnie</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-07-02</td>\n",
       "      <td>2022-12-06 01:27:00</td>\n",
       "      <td>104897</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Donna</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-11-27</td>\n",
       "      <td>2022-12-06 13:59:00</td>\n",
       "      <td>64088</td>\n",
       "      <td>6.155</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
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       "      <td>2022-12-06 20:58:00</td>\n",
       "      <td>76189</td>\n",
       "      <td>18.988</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>Patrick</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>172</th>\n",
       "      <td>Sara</td>\n",
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       "      <td>1991-09-23</td>\n",
       "      <td>2022-12-06 18:17:00</td>\n",
       "      <td>97058</td>\n",
       "      <td>9.402</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
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       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-06-17</td>\n",
       "      <td>2022-12-06 12:49:00</td>\n",
       "      <td>71945</td>\n",
       "      <td>5.560</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>Victor</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-04-11</td>\n",
       "      <td>2022-12-06 07:44:00</td>\n",
       "      <td>70817</td>\n",
       "      <td>17.138</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>Brenda</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-05-29</td>\n",
       "      <td>2022-12-06 06:32:00</td>\n",
       "      <td>82439</td>\n",
       "      <td>19.062</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>Judy</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-07-01</td>\n",
       "      <td>2022-12-06 02:33:00</td>\n",
       "      <td>109510</td>\n",
       "      <td>13.457</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-12-19</td>\n",
       "      <td>2022-12-06 02:54:00</td>\n",
       "      <td>76076</td>\n",
       "      <td>5.319</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>Michael</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-11-22</td>\n",
       "      <td>2022-12-06 12:57:00</td>\n",
       "      <td>98753</td>\n",
       "      <td>16.443</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>537</th>\n",
       "      <td>Cynthia</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-09-14</td>\n",
       "      <td>2022-12-06 13:08:00</td>\n",
       "      <td>51633</td>\n",
       "      <td>13.472</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
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       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>Barbara</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-09-02</td>\n",
       "      <td>2022-12-06 15:41:00</td>\n",
       "      <td>127297</td>\n",
       "      <td>11.905</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
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       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>Carl</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-10-26</td>\n",
       "      <td>2022-12-06 08:11:00</td>\n",
       "      <td>100888</td>\n",
       "      <td>12.490</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>639</th>\n",
       "      <td>Amanda</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-08-11</td>\n",
       "      <td>2022-12-06 14:15:00</td>\n",
       "      <td>46665</td>\n",
       "      <td>19.391</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-09-07</td>\n",
       "      <td>2022-12-06 09:51:00</td>\n",
       "      <td>65251</td>\n",
       "      <td>11.211</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-05-19</td>\n",
       "      <td>2022-12-06 13:40:00</td>\n",
       "      <td>131513</td>\n",
       "      <td>1.876</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>Justin</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-07-25</td>\n",
       "      <td>2022-12-06 00:45:00</td>\n",
       "      <td>112975</td>\n",
       "      <td>9.699</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>771</th>\n",
       "      <td>Peter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-05-22</td>\n",
       "      <td>2022-12-06 01:39:00</td>\n",
       "      <td>102577</td>\n",
       "      <td>12.026</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-04-15</td>\n",
       "      <td>2022-12-06 03:39:00</td>\n",
       "      <td>132505</td>\n",
       "      <td>13.592</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>Timothy</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-08-25</td>\n",
       "      <td>2022-12-06 10:37:00</td>\n",
       "      <td>92587</td>\n",
       "      <td>8.475</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Janice</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-11-19</td>\n",
       "      <td>2022-12-06 18:02:00</td>\n",
       "      <td>139791</td>\n",
       "      <td>16.968</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>909</th>\n",
       "      <td>Donald</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-08-01</td>\n",
       "      <td>2022-12-06 02:25:00</td>\n",
       "      <td>61999</td>\n",
       "      <td>6.466</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>923</th>\n",
       "      <td>Irene</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>2022-12-06 22:23:00</td>\n",
       "      <td>135369</td>\n",
       "      <td>4.380</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>Justin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>2022-12-06 16:58:00</td>\n",
       "      <td>38344</td>\n",
       "      <td>3.794</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "27       Scott     NaN 1991-07-11 2022-12-06 18:58:00  122367    5.218   \n",
       "75      Bonnie  Female 1991-07-02 2022-12-06 01:27:00  104897    5.118   \n",
       "88       Donna  Female 1991-11-27 2022-12-06 13:59:00   64088    6.155   \n",
       "116        NaN    Male 1991-06-22 2022-12-06 20:58:00   76189   18.988   \n",
       "148    Patrick     NaN 1991-07-14 2022-12-06 02:24:00  124488   14.837   \n",
       "166        NaN  Female 1991-07-09 2022-12-06 18:52:00   42341    7.014   \n",
       "172       Sara  Female 1991-09-23 2022-12-06 18:17:00   97058    9.402   \n",
       "220        NaN  Female 1991-06-17 2022-12-06 12:49:00   71945    5.560   \n",
       "245     Victor    Male 1991-04-11 2022-12-06 07:44:00   70817   17.138   \n",
       "277     Brenda     NaN 1991-05-29 2022-12-06 06:32:00   82439   19.062   \n",
       "313       Judy  Female 1991-07-01 2022-12-06 02:33:00  109510   13.457   \n",
       "328     Samuel    Male 1991-12-19 2022-12-06 02:54:00   76076    5.319   \n",
       "339    Michael    Male 1991-11-22 2022-12-06 12:57:00   98753   16.443   \n",
       "537    Cynthia  Female 1991-09-14 2022-12-06 13:08:00   51633   13.472   \n",
       "552    Barbara  Female 1991-09-02 2022-12-06 15:41:00  127297   11.905   \n",
       "603       Carl     NaN 1991-10-26 2022-12-06 08:11:00  100888   12.490   \n",
       "639     Amanda     NaN 1991-08-11 2022-12-06 14:15:00   46665   19.391   \n",
       "704     Thomas    Male 1991-09-07 2022-12-06 09:51:00   65251   11.211   \n",
       "725     Jeremy    Male 1991-05-19 2022-12-06 13:40:00  131513    1.876   \n",
       "766     Justin    Male 1991-07-25 2022-12-06 00:45:00  112975    9.699   \n",
       "771      Peter    Male 1991-05-22 2022-12-06 01:39:00  102577   12.026   \n",
       "783        NaN     NaN 1991-04-15 2022-12-06 03:39:00  132505   13.592   \n",
       "891    Timothy    Male 1991-08-25 2022-12-06 10:37:00   92587    8.475   \n",
       "895     Janice     NaN 1991-11-19 2022-12-06 18:02:00  139791   16.968   \n",
       "909     Donald    Male 1991-08-01 2022-12-06 02:25:00   61999    6.466   \n",
       "923      Irene     NaN 1991-02-28 2022-12-06 22:23:00  135369    4.380   \n",
       "989     Justin     NaN 1991-02-10 2022-12-06 16:58:00   38344    3.794   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "27               False                 Legal  \n",
       "75                True       Human Resources  \n",
       "88                True                 Legal  \n",
       "116               True                 Legal  \n",
       "148               True                 Sales  \n",
       "166               True                 Sales  \n",
       "172              False               Finance  \n",
       "220               True             Marketing  \n",
       "245              False           Engineering  \n",
       "277              False                 Sales  \n",
       "313               True                 Legal  \n",
       "328               True               Finance  \n",
       "339               True       Human Resources  \n",
       "537               True  Business Development  \n",
       "552               True               Product  \n",
       "603               True  Business Development  \n",
       "639               True       Client Services  \n",
       "704              False          Distribution  \n",
       "725               True               Finance  \n",
       "766              False       Human Resources  \n",
       "771               True               Product  \n",
       "783               True               Product  \n",
       "891              False               Finance  \n",
       "895              False  Business Development  \n",
       "909              False               Product  \n",
       "923              False  Business Development  \n",
       "989              False                 Legal  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Start Date\"].between(\"1991-01-01\", \"1992-01-01\")]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6af0ba7",
   "metadata": {},
   "source": [
    "# duplicated Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "11740591",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-17</td>\n",
       "      <td>2022-12-06 10:20:00</td>\n",
       "      <td>61602</td>\n",
       "      <td>11.849</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1994-01-29</td>\n",
       "      <td>2022-12-06 18:48:00</td>\n",
       "      <td>58755</td>\n",
       "      <td>5.097</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-07-22</td>\n",
       "      <td>2022-12-06 14:53:00</td>\n",
       "      <td>52119</td>\n",
       "      <td>11.343</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986-01-22</td>\n",
       "      <td>2022-12-06 19:39:00</td>\n",
       "      <td>63126</td>\n",
       "      <td>18.424</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-05-21</td>\n",
       "      <td>2022-12-06 01:45:00</td>\n",
       "      <td>95327</td>\n",
       "      <td>15.120</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "101      Aaron   Male 2012-02-17 2022-12-06 10:20:00   61602   11.849   \n",
       "327      Aaron   Male 1994-01-29 2022-12-06 18:48:00   58755    5.097   \n",
       "440      Aaron   Male 1990-07-22 2022-12-06 14:53:00   52119   11.343   \n",
       "937      Aaron    NaN 1986-01-22 2022-12-06 19:39:00   63126   18.424   \n",
       "137       Adam   Male 2011-05-21 2022-12-06 01:45:00   95327   15.120   \n",
       "\n",
       "     Senior Management             Team  \n",
       "101               True        Marketing  \n",
       "327               True        Marketing  \n",
       "440               True  Client Services  \n",
       "937              False  Client Services  \n",
       "137              False     Distribution  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Start Date\", \"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.sort_values(by = \"First Name\", inplace = True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "58b54b84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101    False\n",
       "327     True\n",
       "440     True\n",
       "937     True\n",
       "137    False\n",
       "       ...  \n",
       "902     True\n",
       "925     True\n",
       "946     True\n",
       "947     True\n",
       "951     True\n",
       "Name: First Name, Length: 1000, dtype: bool"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"First Name\"].duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7d14a849",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1994-01-29</td>\n",
       "      <td>2022-12-06 18:48:00</td>\n",
       "      <td>58755</td>\n",
       "      <td>5.097</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-07-22</td>\n",
       "      <td>2022-12-06 14:53:00</td>\n",
       "      <td>52119</td>\n",
       "      <td>11.343</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986-01-22</td>\n",
       "      <td>2022-12-06 19:39:00</td>\n",
       "      <td>63126</td>\n",
       "      <td>18.424</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-12-24</td>\n",
       "      <td>2022-12-06 20:57:00</td>\n",
       "      <td>110194</td>\n",
       "      <td>14.727</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-07-05</td>\n",
       "      <td>2022-12-06 11:59:00</td>\n",
       "      <td>71276</td>\n",
       "      <td>5.027</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>902</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2001-05-23</td>\n",
       "      <td>2022-12-06 19:52:00</td>\n",
       "      <td>103877</td>\n",
       "      <td>6.322</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>925</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2000-08-23</td>\n",
       "      <td>2022-12-06 16:19:00</td>\n",
       "      <td>95866</td>\n",
       "      <td>19.388</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>1985-09-15</td>\n",
       "      <td>2022-12-06 01:50:00</td>\n",
       "      <td>133472</td>\n",
       "      <td>16.941</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-07-30</td>\n",
       "      <td>2022-12-06 15:07:00</td>\n",
       "      <td>107351</td>\n",
       "      <td>5.329</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>951</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>2022-12-06 05:19:00</td>\n",
       "      <td>143638</td>\n",
       "      <td>9.662</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>799 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "327      Aaron    Male 1994-01-29 2022-12-06 18:48:00   58755    5.097   \n",
       "440      Aaron    Male 1990-07-22 2022-12-06 14:53:00   52119   11.343   \n",
       "937      Aaron     NaN 1986-01-22 2022-12-06 19:39:00   63126   18.424   \n",
       "141       Adam    Male 1990-12-24 2022-12-06 20:57:00  110194   14.727   \n",
       "302       Adam    Male 2007-07-05 2022-12-06 11:59:00   71276    5.027   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "902        NaN    Male 2001-05-23 2022-12-06 19:52:00  103877    6.322   \n",
       "925        NaN  Female 2000-08-23 2022-12-06 16:19:00   95866   19.388   \n",
       "946        NaN  Female 1985-09-15 2022-12-06 01:50:00  133472   16.941   \n",
       "947        NaN    Male 2012-07-30 2022-12-06 15:07:00  107351    5.329   \n",
       "951        NaN  Female 2010-09-14 2022-12-06 05:19:00  143638    9.662   \n",
       "\n",
       "     Senior Management             Team  \n",
       "327               True        Marketing  \n",
       "440               True  Client Services  \n",
       "937              False  Client Services  \n",
       "141               True          Product  \n",
       "302               True  Human Resources  \n",
       "..                 ...              ...  \n",
       "902               True     Distribution  \n",
       "925               True            Sales  \n",
       "946               True     Distribution  \n",
       "947               True        Marketing  \n",
       "951               True              NaN  \n",
       "\n",
       "[799 rows x 8 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"First Name\"].duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "32d08e2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-17</td>\n",
       "      <td>2022-12-06 10:20:00</td>\n",
       "      <td>61602</td>\n",
       "      <td>11.849</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1994-01-29</td>\n",
       "      <td>2022-12-06 18:48:00</td>\n",
       "      <td>58755</td>\n",
       "      <td>5.097</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-07-22</td>\n",
       "      <td>2022-12-06 14:53:00</td>\n",
       "      <td>52119</td>\n",
       "      <td>11.343</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986-01-22</td>\n",
       "      <td>2022-12-06 19:39:00</td>\n",
       "      <td>63126</td>\n",
       "      <td>18.424</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-05-21</td>\n",
       "      <td>2022-12-06 01:45:00</td>\n",
       "      <td>95327</td>\n",
       "      <td>15.120</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>902</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2001-05-23</td>\n",
       "      <td>2022-12-06 19:52:00</td>\n",
       "      <td>103877</td>\n",
       "      <td>6.322</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>925</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2000-08-23</td>\n",
       "      <td>2022-12-06 16:19:00</td>\n",
       "      <td>95866</td>\n",
       "      <td>19.388</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>1985-09-15</td>\n",
       "      <td>2022-12-06 01:50:00</td>\n",
       "      <td>133472</td>\n",
       "      <td>16.941</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-07-30</td>\n",
       "      <td>2022-12-06 15:07:00</td>\n",
       "      <td>107351</td>\n",
       "      <td>5.329</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>951</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>2022-12-06 05:19:00</td>\n",
       "      <td>143638</td>\n",
       "      <td>9.662</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>991 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "101      Aaron    Male 2012-02-17 2022-12-06 10:20:00   61602   11.849   \n",
       "327      Aaron    Male 1994-01-29 2022-12-06 18:48:00   58755    5.097   \n",
       "440      Aaron    Male 1990-07-22 2022-12-06 14:53:00   52119   11.343   \n",
       "937      Aaron     NaN 1986-01-22 2022-12-06 19:39:00   63126   18.424   \n",
       "137       Adam    Male 2011-05-21 2022-12-06 01:45:00   95327   15.120   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "902        NaN    Male 2001-05-23 2022-12-06 19:52:00  103877    6.322   \n",
       "925        NaN  Female 2000-08-23 2022-12-06 16:19:00   95866   19.388   \n",
       "946        NaN  Female 1985-09-15 2022-12-06 01:50:00  133472   16.941   \n",
       "947        NaN    Male 2012-07-30 2022-12-06 15:07:00  107351    5.329   \n",
       "951        NaN  Female 2010-09-14 2022-12-06 05:19:00  143638    9.662   \n",
       "\n",
       "     Senior Management             Team  \n",
       "101               True        Marketing  \n",
       "327               True        Marketing  \n",
       "440               True  Client Services  \n",
       "937              False  Client Services  \n",
       "137              False     Distribution  \n",
       "..                 ...              ...  \n",
       "902               True     Distribution  \n",
       "925               True            Sales  \n",
       "946               True     Distribution  \n",
       "947               True        Marketing  \n",
       "951               True              NaN  \n",
       "\n",
       "[991 rows x 8 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"First Name\"].duplicated(keep = False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "09defa76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
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       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Angela</td>\n",
       "      <td>Female</td>\n",
       "      <td>2005-11-22</td>\n",
       "      <td>2022-12-06 06:29:00</td>\n",
       "      <td>95570</td>\n",
       "      <td>18.523</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688</th>\n",
       "      <td>Brian</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-04-07</td>\n",
       "      <td>2022-12-06 22:47:00</td>\n",
       "      <td>93901</td>\n",
       "      <td>17.821</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Carol</td>\n",
       "      <td>Female</td>\n",
       "      <td>1996-03-19</td>\n",
       "      <td>2022-12-06 03:39:00</td>\n",
       "      <td>57783</td>\n",
       "      <td>9.129</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>David</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-12-05</td>\n",
       "      <td>2022-12-06 08:48:00</td>\n",
       "      <td>92242</td>\n",
       "      <td>15.407</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2022-12-06 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>Eugene</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-05-24</td>\n",
       "      <td>2022-12-06 10:54:00</td>\n",
       "      <td>81077</td>\n",
       "      <td>2.117</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Jean</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-12-18</td>\n",
       "      <td>2022-12-06 09:07:00</td>\n",
       "      <td>119082</td>\n",
       "      <td>16.180</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Keith</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-02-12</td>\n",
       "      <td>2022-12-06 15:02:00</td>\n",
       "      <td>120672</td>\n",
       "      <td>19.467</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>Tammy</td>\n",
       "      <td>Female</td>\n",
       "      <td>1984-11-11</td>\n",
       "      <td>2022-12-06 10:30:00</td>\n",
       "      <td>132839</td>\n",
       "      <td>17.463</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "8       Angela  Female 2005-11-22 2022-12-06 06:29:00   95570   18.523   \n",
       "688      Brian    Male 2007-04-07 2022-12-06 22:47:00   93901   17.821   \n",
       "190      Carol  Female 1996-03-19 2022-12-06 03:39:00   57783    9.129   \n",
       "887      David    Male 2009-12-05 2022-12-06 08:48:00   92242   15.407   \n",
       "5       Dennis    Male 1987-04-18 2022-12-06 01:35:00  115163   10.125   \n",
       "495     Eugene    Male 1984-05-24 2022-12-06 10:54:00   81077    2.117   \n",
       "33        Jean  Female 1993-12-18 2022-12-06 09:07:00  119082   16.180   \n",
       "832      Keith    Male 2003-02-12 2022-12-06 15:02:00  120672   19.467   \n",
       "291      Tammy  Female 1984-11-11 2022-12-06 10:30:00  132839   17.463   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "8                 True           Engineering  \n",
       "688               True                 Legal  \n",
       "190              False               Finance  \n",
       "887              False                 Legal  \n",
       "5                False                 Legal  \n",
       "495              False                 Sales  \n",
       "33               False  Business Development  \n",
       "832              False                 Legal  \n",
       "291               True       Client Services  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[~df[\"First Name\"].duplicated(keep = False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b1b03af",
   "metadata": {},
   "source": [
    "# drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8e4f0bd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-17</td>\n",
       "      <td>2022-12-06 10:20:00</td>\n",
       "      <td>61602</td>\n",
       "      <td>11.849</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1994-01-29</td>\n",
       "      <td>2022-12-06 18:48:00</td>\n",
       "      <td>58755</td>\n",
       "      <td>5.097</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-07-22</td>\n",
       "      <td>2022-12-06 14:53:00</td>\n",
       "      <td>52119</td>\n",
       "      <td>11.343</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986-01-22</td>\n",
       "      <td>2022-12-06 19:39:00</td>\n",
       "      <td>63126</td>\n",
       "      <td>18.424</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-05-21</td>\n",
       "      <td>2022-12-06 01:45:00</td>\n",
       "      <td>95327</td>\n",
       "      <td>15.120</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "101      Aaron   Male 2012-02-17 2022-12-06 10:20:00   61602   11.849   \n",
       "327      Aaron   Male 1994-01-29 2022-12-06 18:48:00   58755    5.097   \n",
       "440      Aaron   Male 1990-07-22 2022-12-06 14:53:00   52119   11.343   \n",
       "937      Aaron    NaN 1986-01-22 2022-12-06 19:39:00   63126   18.424   \n",
       "137       Adam   Male 2011-05-21 2022-12-06 01:45:00   95327   15.120   \n",
       "\n",
       "     Senior Management             Team  \n",
       "101               True        Marketing  \n",
       "327               True        Marketing  \n",
       "440               True  Client Services  \n",
       "937              False  Client Services  \n",
       "137              False     Distribution  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates = [\"Start Date\", \"Last Login Time\"])\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df.sort_values(by = \"First Name\", inplace = True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "9c525561",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ec43885d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.drop_duplicates())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "98add824",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th>Gender</th>\n",
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       "      <th>Last Login Time</th>\n",
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       "      <th>Bonus %</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-17</td>\n",
       "      <td>2022-12-06 10:20:00</td>\n",
       "      <td>61602</td>\n",
       "      <td>11.849</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Adam</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-05-21</td>\n",
       "      <td>2022-12-06 01:45:00</td>\n",
       "      <td>95327</td>\n",
       "      <td>15.120</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>Alan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1988-06-26</td>\n",
       "      <td>2022-12-06 03:54:00</td>\n",
       "      <td>111786</td>\n",
       "      <td>3.592</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>1997-02-01</td>\n",
       "      <td>2022-12-06 16:20:00</td>\n",
       "      <td>67827</td>\n",
       "      <td>19.717</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>Alice</td>\n",
       "      <td>Female</td>\n",
       "      <td>2004-10-05</td>\n",
       "      <td>2022-12-06 09:34:00</td>\n",
       "      <td>47638</td>\n",
       "      <td>11.209</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>Wanda</td>\n",
       "      <td>Female</td>\n",
       "      <td>2008-07-20</td>\n",
       "      <td>2022-12-06 13:44:00</td>\n",
       "      <td>65362</td>\n",
       "      <td>7.132</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>Wayne</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-04-07</td>\n",
       "      <td>2022-12-06 08:00:00</td>\n",
       "      <td>102652</td>\n",
       "      <td>14.085</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>820</th>\n",
       "      <td>William</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-11-18</td>\n",
       "      <td>2022-12-06 12:27:00</td>\n",
       "      <td>54058</td>\n",
       "      <td>5.182</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>Willie</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-08-22</td>\n",
       "      <td>2022-12-06 13:03:00</td>\n",
       "      <td>55038</td>\n",
       "      <td>19.691</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-07-20</td>\n",
       "      <td>2022-12-06 10:43:00</td>\n",
       "      <td>45906</td>\n",
       "      <td>11.598</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>201 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "101      Aaron    Male 2012-02-17 2022-12-06 10:20:00   61602   11.849   \n",
       "137       Adam    Male 2011-05-21 2022-12-06 01:45:00   95327   15.120   \n",
       "300       Alan    Male 1988-06-26 2022-12-06 03:54:00  111786    3.592   \n",
       "372     Albert    Male 1997-02-01 2022-12-06 16:20:00   67827   19.717   \n",
       "988      Alice  Female 2004-10-05 2022-12-06 09:34:00   47638   11.209   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "433      Wanda  Female 2008-07-20 2022-12-06 13:44:00   65362    7.132   \n",
       "177      Wayne    Male 2012-04-07 2022-12-06 08:00:00  102652   14.085   \n",
       "820    William    Male 1993-11-18 2022-12-06 12:27:00   54058    5.182   \n",
       "450     Willie    Male 2009-08-22 2022-12-06 13:03:00   55038   19.691   \n",
       "7          NaN  Female 2015-07-20 2022-12-06 10:43:00   45906   11.598   \n",
       "\n",
       "     Senior Management             Team  \n",
       "101               True        Marketing  \n",
       "137              False     Distribution  \n",
       "300               True      Engineering  \n",
       "372               True      Engineering  \n",
       "988              False  Human Resources  \n",
       "..                 ...              ...  \n",
       "433               True            Legal  \n",
       "177               True     Distribution  \n",
       "820               True  Human Resources  \n",
       "450              False            Legal  \n",
       "7                 True          Finance  \n",
       "\n",
       "[201 rows x 8 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop_duplicates(subset = [\"First Name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "55fc01d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "201"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.drop_duplicates(subset = [\"First Name\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3ff53cec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "769"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.drop_duplicates(subset = [\"First Name\", \"Team\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7f495ce5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "len(df.drop_duplicates(subset = [\"First Name\"], keep = False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3c77355c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(subset = [\"First Name\"], keep = False, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8528dcb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
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       "      <th>Team</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Angela</td>\n",
       "      <td>Female</td>\n",
       "      <td>2005-11-22</td>\n",
       "      <td>2022-12-06 06:29:00</td>\n",
       "      <td>95570</td>\n",
       "      <td>18.523</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688</th>\n",
       "      <td>Brian</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-04-07</td>\n",
       "      <td>2022-12-06 22:47:00</td>\n",
       "      <td>93901</td>\n",
       "      <td>17.821</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Carol</td>\n",
       "      <td>Female</td>\n",
       "      <td>1996-03-19</td>\n",
       "      <td>2022-12-06 03:39:00</td>\n",
       "      <td>57783</td>\n",
       "      <td>9.129</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>David</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-12-05</td>\n",
       "      <td>2022-12-06 08:48:00</td>\n",
       "      <td>92242</td>\n",
       "      <td>15.407</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2022-12-06 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "8       Angela  Female 2005-11-22 2022-12-06 06:29:00   95570   18.523   \n",
       "688      Brian    Male 2007-04-07 2022-12-06 22:47:00   93901   17.821   \n",
       "190      Carol  Female 1996-03-19 2022-12-06 03:39:00   57783    9.129   \n",
       "887      David    Male 2009-12-05 2022-12-06 08:48:00   92242   15.407   \n",
       "5       Dennis    Male 1987-04-18 2022-12-06 01:35:00  115163   10.125   \n",
       "\n",
       "     Senior Management         Team  \n",
       "8                 True  Engineering  \n",
       "688               True        Legal  \n",
       "190              False      Finance  \n",
       "887              False        Legal  \n",
       "5                False        Legal  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "5de422eb",
   "metadata": {},
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