Task Assigned in the Full Stack Data Science Class -- 31-07-2022 [Task1 - FitBit Dataset].ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "69d9d124",
   "metadata": {},
   "source": [
    "### TASK 1 - Fitbit Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "863122d5",
   "metadata": {},
   "source": [
    "#### 1. Read this dataset in pandas, mysql and mongodb."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93d01748",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mysql\n",
    "import mysql.connector as conn\n",
    "\n",
    "mydb = conn.connect(host = \"localhost\", user = \"root\", passwd = \"password\")\n",
    "cursor = mydb.cursor()\n",
    "cursor.execute(\"create database fit_bit\")\n",
    "cursor.execute(\"show databases\")\n",
    "for i in cursor.fetchall():\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e06bdcee",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mongodb\n",
    "import json \n",
    "fit_bit_json = fit_bit.to_json(r'C:\\Users\\Computers\\Downloads\\FitBit data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d08f640",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mongodb\n",
    "\n",
    "import pymongo\n",
    "client = pymongo.MongoClient(\"mongodb+srv://yashadas:<password>@cluster0.yd8um.mongodb.net/?retryWrites=true&w=majority\")\n",
    "db = client.test\n",
    "\n",
    "database = client['Task1']\n",
    "collection = database[\"fit_bit\"]\n",
    "collection.insert_many(fit_bit_json)\n",
    "x = collection.find()\n",
    "for i in x:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9362a878",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pandas \n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e57582b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "fit_bit = pd.read_csv(r'C:\\Users\\Computers\\Downloads\\FitBit data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f24f7e68",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/25/2016</td>\n",
       "      <td>11004</td>\n",
       "      <td>7.110000</td>\n",
       "      <td>7.110000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.57</td>\n",
       "      <td>0.46</td>\n",
       "      <td>4.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>33</td>\n",
       "      <td>12</td>\n",
       "      <td>205</td>\n",
       "      <td>804</td>\n",
       "      <td>1819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/26/2016</td>\n",
       "      <td>17609</td>\n",
       "      <td>11.550000</td>\n",
       "      <td>11.550000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.92</td>\n",
       "      <td>0.73</td>\n",
       "      <td>3.91</td>\n",
       "      <td>0.00</td>\n",
       "      <td>89</td>\n",
       "      <td>17</td>\n",
       "      <td>274</td>\n",
       "      <td>588</td>\n",
       "      <td>2154</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/27/2016</td>\n",
       "      <td>12736</td>\n",
       "      <td>8.530000</td>\n",
       "      <td>8.530000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.66</td>\n",
       "      <td>0.16</td>\n",
       "      <td>3.71</td>\n",
       "      <td>0.00</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>268</td>\n",
       "      <td>605</td>\n",
       "      <td>1944</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/28/2016</td>\n",
       "      <td>13231</td>\n",
       "      <td>8.930000</td>\n",
       "      <td>8.930000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.79</td>\n",
       "      <td>4.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>39</td>\n",
       "      <td>20</td>\n",
       "      <td>224</td>\n",
       "      <td>1080</td>\n",
       "      <td>1932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/29/2016</td>\n",
       "      <td>12041</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1.09</td>\n",
       "      <td>4.61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>243</td>\n",
       "      <td>763</td>\n",
       "      <td>1886</td>\n",
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       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>4/8/2016</td>\n",
       "      <td>23014</td>\n",
       "      <td>20.389999</td>\n",
       "      <td>20.389999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.10</td>\n",
       "      <td>0.63</td>\n",
       "      <td>8.62</td>\n",
       "      <td>0.00</td>\n",
       "      <td>70</td>\n",
       "      <td>29</td>\n",
       "      <td>359</td>\n",
       "      <td>982</td>\n",
       "      <td>4196</td>\n",
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       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>4/9/2016</td>\n",
       "      <td>16470</td>\n",
       "      <td>8.070000</td>\n",
       "      <td>8.070000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>8.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>90</td>\n",
       "      <td>9</td>\n",
       "      <td>289</td>\n",
       "      <td>1052</td>\n",
       "      <td>3841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>4/10/2016</td>\n",
       "      <td>28497</td>\n",
       "      <td>27.530001</td>\n",
       "      <td>27.530001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.92</td>\n",
       "      <td>1.12</td>\n",
       "      <td>4.46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>128</td>\n",
       "      <td>46</td>\n",
       "      <td>211</td>\n",
       "      <td>1055</td>\n",
       "      <td>4526</td>\n",
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       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>4/11/2016</td>\n",
       "      <td>10622</td>\n",
       "      <td>8.060000</td>\n",
       "      <td>8.060000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.47</td>\n",
       "      <td>0.15</td>\n",
       "      <td>6.37</td>\n",
       "      <td>0.01</td>\n",
       "      <td>18</td>\n",
       "      <td>7</td>\n",
       "      <td>225</td>\n",
       "      <td>1190</td>\n",
       "      <td>2820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>4/12/2016</td>\n",
       "      <td>2350</td>\n",
       "      <td>1.780000</td>\n",
       "      <td>1.780000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.78</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>531</td>\n",
       "      <td>938</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>457 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "0    1503960366    3/25/2016       11004       7.110000         7.110000   \n",
       "1    1503960366    3/26/2016       17609      11.550000        11.550000   \n",
       "2    1503960366    3/27/2016       12736       8.530000         8.530000   \n",
       "3    1503960366    3/28/2016       13231       8.930000         8.930000   \n",
       "4    1503960366    3/29/2016       12041       7.850000         7.850000   \n",
       "..          ...          ...         ...            ...              ...   \n",
       "452  8877689391     4/8/2016       23014      20.389999        20.389999   \n",
       "453  8877689391     4/9/2016       16470       8.070000         8.070000   \n",
       "454  8877689391    4/10/2016       28497      27.530001        27.530001   \n",
       "455  8877689391    4/11/2016       10622       8.060000         8.060000   \n",
       "456  8877689391    4/12/2016        2350       1.780000         1.780000   \n",
       "\n",
       "     LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "0                         0.0                2.57                      0.46   \n",
       "1                         0.0                6.92                      0.73   \n",
       "2                         0.0                4.66                      0.16   \n",
       "3                         0.0                3.19                      0.79   \n",
       "4                         0.0                2.16                      1.09   \n",
       "..                        ...                 ...                       ...   \n",
       "452                       0.0               11.10                      0.63   \n",
       "453                       0.0                0.00                      0.02   \n",
       "454                       0.0               21.92                      1.12   \n",
       "455                       0.0                1.47                      0.15   \n",
       "456                       0.0                0.00                      0.00   \n",
       "\n",
       "     LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "0                   4.07                     0.00                 33   \n",
       "1                   3.91                     0.00                 89   \n",
       "2                   3.71                     0.00                 56   \n",
       "3                   4.95                     0.00                 39   \n",
       "4                   4.61                     0.00                 28   \n",
       "..                   ...                      ...                ...   \n",
       "452                 8.62                     0.00                 70   \n",
       "453                 8.02                     0.00                 90   \n",
       "454                 4.46                     0.00                128   \n",
       "455                 6.37                     0.01                 18   \n",
       "456                 1.78                     0.00                  0   \n",
       "\n",
       "     FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \n",
       "0                     12                   205               804      1819  \n",
       "1                     17                   274               588      2154  \n",
       "2                      5                   268               605      1944  \n",
       "3                     20                   224              1080      1932  \n",
       "4                     28                   243               763      1886  \n",
       "..                   ...                   ...               ...       ...  \n",
       "452                   29                   359               982      4196  \n",
       "453                    9                   289              1052      3841  \n",
       "454                   46                   211              1055      4526  \n",
       "455                    7                   225              1190      2820  \n",
       "456                    0                    58               531       938  \n",
       "\n",
       "[457 rows x 15 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f408cee2",
   "metadata": {},
   "source": [
    "#### 2. While creating a table in mysql dont use manual approach to create it, always use a automation to create a table in mysql.\n",
    " ###### hint - use csvkit library to automate this task and to load a data in bulk in you mysql "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23670134",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymysql\n",
    "import os\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c3046d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine('mysql+pymysql://root:3306@localhost/fit_bit')\n",
    "fit_bit.to_sql('fit_bit', con=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77b840ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "createdb task1\n",
    "csvsql --db mysql:///task1  --tables fit_bit --insert C:\\Users\\Computers\\Downloads\\FitBit data.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8578af29",
   "metadata": {},
   "source": [
    "#### 3. Convert all the dates avaible in dataset to timestamp format in pandas and in sql you to convert it in date format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "59a132c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                            int64\n",
       "ActivityDate                 object\n",
       "TotalSteps                    int64\n",
       "TotalDistance               float64\n",
       "TrackerDistance             float64\n",
       "LoggedActivitiesDistance    float64\n",
       "VeryActiveDistance          float64\n",
       "ModeratelyActiveDistance    float64\n",
       "LightActiveDistance         float64\n",
       "SedentaryActiveDistance     float64\n",
       "VeryActiveMinutes             int64\n",
       "FairlyActiveMinutes           int64\n",
       "LightlyActiveMinutes          int64\n",
       "SedentaryMinutes              int64\n",
       "Calories                      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.dtypes \n",
    "# Here the 'ActivityDate' column which contains the dates is of object type, i.e., string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "83463950",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting all the dates avaible in dataset to timestamp format in pandas\n",
    "fit_bit['ActivityDate'] = pd.to_datetime(fit_bit['ActivityDate'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d715b4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                                   int64\n",
       "ActivityDate                datetime64[ns]\n",
       "TotalSteps                           int64\n",
       "TotalDistance                      float64\n",
       "TrackerDistance                    float64\n",
       "LoggedActivitiesDistance           float64\n",
       "VeryActiveDistance                 float64\n",
       "ModeratelyActiveDistance           float64\n",
       "LightActiveDistance                float64\n",
       "SedentaryActiveDistance            float64\n",
       "VeryActiveMinutes                    int64\n",
       "FairlyActiveMinutes                  int64\n",
       "LightlyActiveMinutes                 int64\n",
       "SedentaryMinutes                     int64\n",
       "Calories                             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.dtypes \n",
    "# Here the 'ActivityDate' column in the dataset is converted to datetime64[ns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55c7223f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#mysql\n",
    "alter table fit_bit\n",
    "add column ActivityDate1 date after ActivityDate;\n",
    "SET SQL_SAFE_UPDATES = 0;\n",
    "update fit_bit\n",
    "set ActivityDate1 = str_to_date(ActivityDate,'%m/%d/%Y');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "083e7026",
   "metadata": {},
   "source": [
    "#### 4. Find out in this data that how many unique id's we have. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "35f083e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1503960366, 1624580081, 1644430081, 1844505072, 1927972279,\n",
       "       2022484408, 2026352035, 2320127002, 2347167796, 2873212765,\n",
       "       2891001357, 3372868164, 3977333714, 4020332650, 4057192912,\n",
       "       4319703577, 4388161847, 4445114986, 4558609924, 4702921684,\n",
       "       5553957443, 5577150313, 6117666160, 6290855005, 6391747486,\n",
       "       6775888955, 6962181067, 7007744171, 7086361926, 8053475328,\n",
       "       8253242879, 8378563200, 8583815059, 8792009665, 8877689391],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit['Id'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e8aa83ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total number of unique id's that this dataset has is 35\n",
    "len(fit_bit['Id'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f83be47f",
   "metadata": {},
   "source": [
    "#### 5. Which id is one of the active id that you have in whole dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7b059ec1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a column called 'TotalActiveMinutes'\n",
    "fit_bit['TotalActiveMinutes'] = (fit_bit['VeryActiveMinutes']+fit_bit['FairlyActiveMinutes'] + fit_bit['LightlyActiveMinutes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8614abfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "      <th>TotalActiveMinutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/25/2016</td>\n",
       "      <td>11004</td>\n",
       "      <td>7.11</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.57</td>\n",
       "      <td>0.46</td>\n",
       "      <td>4.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33</td>\n",
       "      <td>12</td>\n",
       "      <td>205</td>\n",
       "      <td>804</td>\n",
       "      <td>1819</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/26/2016</td>\n",
       "      <td>17609</td>\n",
       "      <td>11.55</td>\n",
       "      <td>11.55</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.92</td>\n",
       "      <td>0.73</td>\n",
       "      <td>3.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89</td>\n",
       "      <td>17</td>\n",
       "      <td>274</td>\n",
       "      <td>588</td>\n",
       "      <td>2154</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/27/2016</td>\n",
       "      <td>12736</td>\n",
       "      <td>8.53</td>\n",
       "      <td>8.53</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.66</td>\n",
       "      <td>0.16</td>\n",
       "      <td>3.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>268</td>\n",
       "      <td>605</td>\n",
       "      <td>1944</td>\n",
       "      <td>329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/28/2016</td>\n",
       "      <td>13231</td>\n",
       "      <td>8.93</td>\n",
       "      <td>8.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.79</td>\n",
       "      <td>4.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39</td>\n",
       "      <td>20</td>\n",
       "      <td>224</td>\n",
       "      <td>1080</td>\n",
       "      <td>1932</td>\n",
       "      <td>283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>3/29/2016</td>\n",
       "      <td>12041</td>\n",
       "      <td>7.85</td>\n",
       "      <td>7.85</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1.09</td>\n",
       "      <td>4.61</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>243</td>\n",
       "      <td>763</td>\n",
       "      <td>1886</td>\n",
       "      <td>299</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "0  1503960366    3/25/2016       11004           7.11             7.11   \n",
       "1  1503960366    3/26/2016       17609          11.55            11.55   \n",
       "2  1503960366    3/27/2016       12736           8.53             8.53   \n",
       "3  1503960366    3/28/2016       13231           8.93             8.93   \n",
       "4  1503960366    3/29/2016       12041           7.85             7.85   \n",
       "\n",
       "   LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "0                       0.0                2.57                      0.46   \n",
       "1                       0.0                6.92                      0.73   \n",
       "2                       0.0                4.66                      0.16   \n",
       "3                       0.0                3.19                      0.79   \n",
       "4                       0.0                2.16                      1.09   \n",
       "\n",
       "   LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "0                 4.07                      0.0                 33   \n",
       "1                 3.91                      0.0                 89   \n",
       "2                 3.71                      0.0                 56   \n",
       "3                 4.95                      0.0                 39   \n",
       "4                 4.61                      0.0                 28   \n",
       "\n",
       "   FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "0                   12                   205               804      1819   \n",
       "1                   17                   274               588      2154   \n",
       "2                    5                   268               605      1944   \n",
       "3                   20                   224              1080      1932   \n",
       "4                   28                   243               763      1886   \n",
       "\n",
       "   TotalActiveMinutes  \n",
       "0                 250  \n",
       "1                 380  \n",
       "2                 329  \n",
       "3                 283  \n",
       "4                 299  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7d26fa2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Id', 'ActivityDate', 'TotalSteps', 'TotalDistance', 'TrackerDistance',\n",
       "       'LoggedActivitiesDistance', 'VeryActiveDistance',\n",
       "       'ModeratelyActiveDistance', 'LightActiveDistance',\n",
       "       'SedentaryActiveDistance', 'VeryActiveMinutes', 'FairlyActiveMinutes',\n",
       "       'LightlyActiveMinutes', 'SedentaryMinutes', 'Calories',\n",
       "       'TotalActiveMinutes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "31a12b48",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
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       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "      <th>TotalActiveMinutes</th>\n",
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       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2891001357</td>\n",
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      "text/plain": [
       "             Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "139  2891001357     4/2/2016        4126           3.22              0.0   \n",
       "\n",
       "     LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "139                  3.218688                 0.0                       0.0   \n",
       "\n",
       "     LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "139                 3.22                      0.0                  0   \n",
       "\n",
       "     FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "139                    0                   720               720      2881   \n",
       "\n",
       "     TotalActiveMinutes  \n",
       "139                 720  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.sort_values('TotalActiveMinutes', ascending=False).iloc[[0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a98b13c6",
   "metadata": {},
   "source": [
    "#### 6. How many of them have not logged there activity find out in terms of number of ids. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "4535a6f1",
   "metadata": {},
   "outputs": [
    {
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       "      <th>51</th>\n",
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       "<p>68 rows × 16 columns</p>\n",
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      ],
      "text/plain": [
       "             Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "51   1844505072     4/4/2016           0            0.0              0.0   \n",
       "52   1844505072     4/5/2016           0            0.0              0.0   \n",
       "59   1844505072    4/12/2016           0            0.0              0.0   \n",
       "96   2320127002     4/1/2016           0            0.0              0.0   \n",
       "97   2320127002     4/2/2016           0            0.0              0.0   \n",
       "..          ...          ...         ...            ...              ...   \n",
       "402  8253242879     4/2/2016           0            0.0              0.0   \n",
       "403  8253242879     4/3/2016           0            0.0              0.0   \n",
       "404  8253242879     4/4/2016           0            0.0              0.0   \n",
       "405  8253242879     4/5/2016           0            0.0              0.0   \n",
       "412  8253242879    4/12/2016           0            0.0              0.0   \n",
       "\n",
       "     LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "51                        0.0                 0.0                       0.0   \n",
       "52                        0.0                 0.0                       0.0   \n",
       "59                        0.0                 0.0                       0.0   \n",
       "96                        0.0                 0.0                       0.0   \n",
       "97                        0.0                 0.0                       0.0   \n",
       "..                        ...                 ...                       ...   \n",
       "402                       0.0                 0.0                       0.0   \n",
       "403                       0.0                 0.0                       0.0   \n",
       "404                       0.0                 0.0                       0.0   \n",
       "405                       0.0                 0.0                       0.0   \n",
       "412                       0.0                 0.0                       0.0   \n",
       "\n",
       "     LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "51                   0.0                      0.0                  0   \n",
       "52                   0.0                      0.0                  0   \n",
       "59                   0.0                      0.0                  0   \n",
       "96                   0.0                      0.0                  0   \n",
       "97                   0.0                      0.0                  0   \n",
       "..                   ...                      ...                ...   \n",
       "402                  0.0                      0.0                  0   \n",
       "403                  0.0                      0.0                  0   \n",
       "404                  0.0                      0.0                  0   \n",
       "405                  0.0                      0.0                  0   \n",
       "412                  0.0                      0.0                  0   \n",
       "\n",
       "     FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "51                     0                     0               669      1347   \n",
       "52                     0                     0              1440      1347   \n",
       "59                     0                     0               426       399   \n",
       "96                     0                     0              1440      1324   \n",
       "97                     0                     0              1440      1324   \n",
       "..                   ...                   ...               ...       ...   \n",
       "402                    0                     0              1440      1429   \n",
       "403                    0                     0              1440      1429   \n",
       "404                    0                     0              1440      1429   \n",
       "405                    0                     0              1440      1429   \n",
       "412                    0                     0              1440         0   \n",
       "\n",
       "     TotalActiveMinutes  \n",
       "51                    0  \n",
       "52                    0  \n",
       "59                    0  \n",
       "96                    0  \n",
       "97                    0  \n",
       "..                  ...  \n",
       "402                   0  \n",
       "403                   0  \n",
       "404                   0  \n",
       "405                   0  \n",
       "412                   0  \n",
       "\n",
       "[68 rows x 16 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit[fit_bit['TotalActiveMinutes']== 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6528c708",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fit_bit[fit_bit['TotalActiveMinutes']== 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7de18758",
   "metadata": {},
   "source": [
    "#### 7. Find out who is the laziest person id that we have in dataset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "229e1365",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
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       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "      <th>TotalActiveMinutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>18</td>\n",
       "      <td>1503960366</td>\n",
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       "      <td>50</td>\n",
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      ],
      "text/plain": [
       "   index          Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "0     18  1503960366    4/12/2016         224           0.14             0.14   \n",
       "\n",
       "   LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "0                       0.0                 0.0                       0.0   \n",
       "\n",
       "   LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "0                 0.13                      0.0                  0   \n",
       "\n",
       "   FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "0                    0                     9                32        50   \n",
       "\n",
       "   TotalActiveMinutes  \n",
       "0                   9  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit[fit_bit['Calories']>0].sort_values(['Calories']).reset_index().iloc[[0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2a3a6c9",
   "metadata": {},
   "source": [
    "#### 8. Explore over an internet that how much calories burn is required for a healthy person and find out how many healthy person we have in our dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e57bf53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1503960366, 1644430081, 1927972279, 2022484408, 2320127002,\n",
       "       2347167796, 2873212765, 2891001357, 3372868164, 4020332650,\n",
       "       4057192912, 4319703577, 4445114986, 4558609924, 4702921684,\n",
       "       5553957443, 5577150313, 6117666160, 6290855005, 6391747486,\n",
       "       6775888955, 6962181067, 7007744171, 7086361926, 8053475328,\n",
       "       8253242879, 8378563200, 8583815059, 8792009665, 8877689391],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# According to the internet, calorie burn that is requied for a healthy person is 2400 calories \n",
    "\n",
    "fit_bit[fit_bit['Calories']>2000]['Id'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "42159487",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fit_bit[fit_bit['Calories']>2000]['Id'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "143380f3",
   "metadata": {},
   "source": [
    "#### 9. How many person are not a regular person with respect to activity try to find out those."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "dbd2069a",
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "             Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "51   1844505072     4/4/2016           0            0.0              0.0   \n",
       "52   1844505072     4/5/2016           0            0.0              0.0   \n",
       "59   1844505072    4/12/2016           0            0.0              0.0   \n",
       "96   2320127002     4/1/2016           0            0.0              0.0   \n",
       "97   2320127002     4/2/2016           0            0.0              0.0   \n",
       "..          ...          ...         ...            ...              ...   \n",
       "402  8253242879     4/2/2016           0            0.0              0.0   \n",
       "403  8253242879     4/3/2016           0            0.0              0.0   \n",
       "404  8253242879     4/4/2016           0            0.0              0.0   \n",
       "405  8253242879     4/5/2016           0            0.0              0.0   \n",
       "412  8253242879    4/12/2016           0            0.0              0.0   \n",
       "\n",
       "     LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "51                        0.0                 0.0                       0.0   \n",
       "52                        0.0                 0.0                       0.0   \n",
       "59                        0.0                 0.0                       0.0   \n",
       "96                        0.0                 0.0                       0.0   \n",
       "97                        0.0                 0.0                       0.0   \n",
       "..                        ...                 ...                       ...   \n",
       "402                       0.0                 0.0                       0.0   \n",
       "403                       0.0                 0.0                       0.0   \n",
       "404                       0.0                 0.0                       0.0   \n",
       "405                       0.0                 0.0                       0.0   \n",
       "412                       0.0                 0.0                       0.0   \n",
       "\n",
       "     LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "51                   0.0                      0.0                  0   \n",
       "52                   0.0                      0.0                  0   \n",
       "59                   0.0                      0.0                  0   \n",
       "96                   0.0                      0.0                  0   \n",
       "97                   0.0                      0.0                  0   \n",
       "..                   ...                      ...                ...   \n",
       "402                  0.0                      0.0                  0   \n",
       "403                  0.0                      0.0                  0   \n",
       "404                  0.0                      0.0                  0   \n",
       "405                  0.0                      0.0                  0   \n",
       "412                  0.0                      0.0                  0   \n",
       "\n",
       "     FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "51                     0                     0               669      1347   \n",
       "52                     0                     0              1440      1347   \n",
       "59                     0                     0               426       399   \n",
       "96                     0                     0              1440      1324   \n",
       "97                     0                     0              1440      1324   \n",
       "..                   ...                   ...               ...       ...   \n",
       "402                    0                     0              1440      1429   \n",
       "403                    0                     0              1440      1429   \n",
       "404                    0                     0              1440      1429   \n",
       "405                    0                     0              1440      1429   \n",
       "412                    0                     0              1440         0   \n",
       "\n",
       "     TotalActiveMinutes  \n",
       "51                    0  \n",
       "52                    0  \n",
       "59                    0  \n",
       "96                    0  \n",
       "97                    0  \n",
       "..                  ...  \n",
       "402                   0  \n",
       "403                   0  \n",
       "404                   0  \n",
       "405                   0  \n",
       "412                   0  \n",
       "\n",
       "[61 rows x 16 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit[fit_bit['TotalSteps']==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "a72c3ca9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fit_bit[fit_bit['TotalSteps']==0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52871fe5",
   "metadata": {},
   "source": [
    "#### 10. Who is the third most active person in this dataset find out those in pandas and in sql both. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "8bdd7127",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "      <th>TotalActiveMinutes</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>142</td>\n",
       "      <td>2891001357</td>\n",
       "      <td>4/5/2016</td>\n",
       "      <td>2063</td>\n",
       "      <td>1.61</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.609344</td>\n",
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       "      <td>1.61</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>630</td>\n",
       "      <td>99</td>\n",
       "      <td>1144</td>\n",
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      "text/plain": [
       "   index          Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "2    142  2891001357     4/5/2016        2063           1.61              0.0   \n",
       "\n",
       "   LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "2                  1.609344                 0.0                       0.0   \n",
       "\n",
       "   LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "2                 1.61                      0.0                  0   \n",
       "\n",
       "   FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "2                    0                   630                99      1144   \n",
       "\n",
       "   TotalActiveMinutes  \n",
       "2                 630  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.sort_values(\"TotalActiveMinutes\", ascending = False).reset_index().iloc[[2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "780a61bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#mysql code\n",
    "select id, sum(TotalActiveMinutes) \n",
    "from fit_bit \n",
    "groupby Id \n",
    "ORDER BY sum(TotalActiveMinutes) DESC \n",
    "LIMIT 1 \n",
    "OFFSET 2;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ccebd97",
   "metadata": {},
   "source": [
    "#### 11 . Who is the 5th most laziest person avilable in dataset find it out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "9712b733",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "      <th>TotalActiveMinutes</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>341</td>\n",
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       "      <td>4/8/2016</td>\n",
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       "      <td>0</td>\n",
       "      <td>1440</td>\n",
       "      <td>1820</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index          Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "4    341  6391747486     4/8/2016           0            0.0              0.0   \n",
       "\n",
       "   LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "4                       0.0                 0.0                       0.0   \n",
       "\n",
       "   LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "4                  0.0                      0.0                  0   \n",
       "\n",
       "   FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \\\n",
       "4                    0                     0              1440      1820   \n",
       "\n",
       "   TotalActiveMinutes  \n",
       "4                   0  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit_bit.sort_values('TotalSteps').reset_index().iloc[[4]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc8a7729",
   "metadata": {},
   "source": [
    "#### 12. What is a total acumulative calories burn for a person find out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "919aa29b",
   "metadata": {},
   "outputs": [],
   "source": [
    "total_cal = fit_bit.groupby('Id',as_index = False).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "b7d319ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Calories</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>34128</td>\n",
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       "      <th>1</th>\n",
       "      <td>1624580081</td>\n",
       "      <td>25705</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644430081</td>\n",
       "      <td>29164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1844505072</td>\n",
       "      <td>19391</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1927972279</td>\n",
       "      <td>27048</td>\n",
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       "      <th>5</th>\n",
       "      <td>2022484408</td>\n",
       "      <td>29704</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2026352035</td>\n",
       "      <td>16266</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2320127002</td>\n",
       "      <td>18385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2347167796</td>\n",
       "      <td>30320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2873212765</td>\n",
       "      <td>20349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2891001357</td>\n",
       "      <td>18187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3372868164</td>\n",
       "      <td>18603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3977333714</td>\n",
       "      <td>16777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4020332650</td>\n",
       "      <td>98412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4057192912</td>\n",
       "      <td>60913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4319703577</td>\n",
       "      <td>23931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>4388161847</td>\n",
       "      <td>14442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>4445114986</td>\n",
       "      <td>31617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>4558609924</td>\n",
       "      <td>21962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4702921684</td>\n",
       "      <td>42322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5553957443</td>\n",
       "      <td>21630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5577150313</td>\n",
       "      <td>36303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6117666160</td>\n",
       "      <td>20993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>6290855005</td>\n",
       "      <td>21656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>6391747486</td>\n",
       "      <td>15868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>6775888955</td>\n",
       "      <td>24523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>6962181067</td>\n",
       "      <td>29249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7007744171</td>\n",
       "      <td>31525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>7086361926</td>\n",
       "      <td>26124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>8053475328</td>\n",
       "      <td>31825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>8253242879</td>\n",
       "      <td>17556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>8378563200</td>\n",
       "      <td>40274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>8583815059</td>\n",
       "      <td>19130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>8792009665</td>\n",
       "      <td>24884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>8877689391</td>\n",
       "      <td>41414</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Id  Calories\n",
       "0   1503960366     34128\n",
       "1   1624580081     25705\n",
       "2   1644430081     29164\n",
       "3   1844505072     19391\n",
       "4   1927972279     27048\n",
       "5   2022484408     29704\n",
       "6   2026352035     16266\n",
       "7   2320127002     18385\n",
       "8   2347167796     30320\n",
       "9   2873212765     20349\n",
       "10  2891001357     18187\n",
       "11  3372868164     18603\n",
       "12  3977333714     16777\n",
       "13  4020332650     98412\n",
       "14  4057192912     60913\n",
       "15  4319703577     23931\n",
       "16  4388161847     14442\n",
       "17  4445114986     31617\n",
       "18  4558609924     21962\n",
       "19  4702921684     42322\n",
       "20  5553957443     21630\n",
       "21  5577150313     36303\n",
       "22  6117666160     20993\n",
       "23  6290855005     21656\n",
       "24  6391747486     15868\n",
       "25  6775888955     24523\n",
       "26  6962181067     29249\n",
       "27  7007744171     31525\n",
       "28  7086361926     26124\n",
       "29  8053475328     31825\n",
       "30  8253242879     17556\n",
       "31  8378563200     40274\n",
       "32  8583815059     19130\n",
       "33  8792009665     24884\n",
       "34  8877689391     41414"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_cal[[ \"Id\", 'Calories']]"
   ]
  }
 ],
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