Bike_Share_Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bike Share Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Import all required packages\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "import sklearn\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "from sklearn.feature_selection import RFE\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "#Supress Warning\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>01-01-2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14.110847</td>\n",
       "      <td>18.18125</td>\n",
       "      <td>80.5833</td>\n",
       "      <td>10.749882</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>02-01-2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14.902598</td>\n",
       "      <td>17.68695</td>\n",
       "      <td>69.6087</td>\n",
       "      <td>16.652113</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>03-01-2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8.050924</td>\n",
       "      <td>9.47025</td>\n",
       "      <td>43.7273</td>\n",
       "      <td>16.636703</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>04-01-2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>10.60610</td>\n",
       "      <td>59.0435</td>\n",
       "      <td>10.739832</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>05-01-2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9.305237</td>\n",
       "      <td>11.46350</td>\n",
       "      <td>43.6957</td>\n",
       "      <td>12.522300</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  01-01-2018       1   0     1        0        6           0   \n",
       "1        2  02-01-2018       1   0     1        0        0           0   \n",
       "2        3  03-01-2018       1   0     1        0        1           1   \n",
       "3        4  04-01-2018       1   0     1        0        2           1   \n",
       "4        5  05-01-2018       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit       temp     atemp      hum  windspeed  casual  registered  \\\n",
       "0           2  14.110847  18.18125  80.5833  10.749882     331         654   \n",
       "1           2  14.902598  17.68695  69.6087  16.652113     131         670   \n",
       "2           1   8.050924   9.47025  43.7273  16.636703     120        1229   \n",
       "3           1   8.200000  10.60610  59.0435  10.739832     108        1454   \n",
       "4           1   9.305237  11.46350  43.6957  12.522300      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import dataset\n",
    "bikes = pd.read_csv('day.csv')\n",
    "bikes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(730, 16)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bikes.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 730 entries, 0 to 729\n",
      "Data columns (total 16 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   instant     730 non-null    int64  \n",
      " 1   dteday      730 non-null    object \n",
      " 2   season      730 non-null    int64  \n",
      " 3   yr          730 non-null    int64  \n",
      " 4   mnth        730 non-null    int64  \n",
      " 5   holiday     730 non-null    int64  \n",
      " 6   weekday     730 non-null    int64  \n",
      " 7   workingday  730 non-null    int64  \n",
      " 8   weathersit  730 non-null    int64  \n",
      " 9   temp        730 non-null    float64\n",
      " 10  atemp       730 non-null    float64\n",
      " 11  hum         730 non-null    float64\n",
      " 12  windspeed   730 non-null    float64\n",
      " 13  casual      730 non-null    int64  \n",
      " 14  registered  730 non-null    int64  \n",
      " 15  cnt         730 non-null    int64  \n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.4+ KB\n"
     ]
    }
   ],
   "source": [
    "#Null value count and Data type of variables\n",
    "bikes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yr              2\n",
       "holiday         2\n",
       "workingday      2\n",
       "weathersit      3\n",
       "season          4\n",
       "weekday         7\n",
       "mnth           12\n",
       "temp          498\n",
       "hum           594\n",
       "casual        605\n",
       "windspeed     649\n",
       "registered    678\n",
       "atemp         689\n",
       "cnt           695\n",
       "instant       730\n",
       "dteday        730\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Unique value present in the variables\n",
    "bikes.apply(lambda col: col.nunique()).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "      <td>730.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>365.500000</td>\n",
       "      <td>2.498630</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>6.526027</td>\n",
       "      <td>0.028767</td>\n",
       "      <td>2.997260</td>\n",
       "      <td>0.683562</td>\n",
       "      <td>1.394521</td>\n",
       "      <td>20.319259</td>\n",
       "      <td>23.726322</td>\n",
       "      <td>62.765175</td>\n",
       "      <td>12.763620</td>\n",
       "      <td>849.249315</td>\n",
       "      <td>3658.757534</td>\n",
       "      <td>4508.006849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>210.877136</td>\n",
       "      <td>1.110184</td>\n",
       "      <td>0.500343</td>\n",
       "      <td>3.450215</td>\n",
       "      <td>0.167266</td>\n",
       "      <td>2.006161</td>\n",
       "      <td>0.465405</td>\n",
       "      <td>0.544807</td>\n",
       "      <td>7.506729</td>\n",
       "      <td>8.150308</td>\n",
       "      <td>14.237589</td>\n",
       "      <td>5.195841</td>\n",
       "      <td>686.479875</td>\n",
       "      <td>1559.758728</td>\n",
       "      <td>1936.011647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.424346</td>\n",
       "      <td>3.953480</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500244</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.250000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>13.811885</td>\n",
       "      <td>16.889713</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>9.041650</td>\n",
       "      <td>316.250000</td>\n",
       "      <td>2502.250000</td>\n",
       "      <td>3169.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>365.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.465826</td>\n",
       "      <td>24.368225</td>\n",
       "      <td>62.625000</td>\n",
       "      <td>12.125325</td>\n",
       "      <td>717.000000</td>\n",
       "      <td>3664.500000</td>\n",
       "      <td>4548.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>547.750000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>26.880615</td>\n",
       "      <td>30.445775</td>\n",
       "      <td>72.989575</td>\n",
       "      <td>15.625589</td>\n",
       "      <td>1096.500000</td>\n",
       "      <td>4783.250000</td>\n",
       "      <td>5966.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>730.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>35.328347</td>\n",
       "      <td>42.044800</td>\n",
       "      <td>97.250000</td>\n",
       "      <td>34.000021</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  730.000000  730.000000  730.000000  730.000000  730.000000  730.000000   \n",
       "mean   365.500000    2.498630    0.500000    6.526027    0.028767    2.997260   \n",
       "std    210.877136    1.110184    0.500343    3.450215    0.167266    2.006161   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.250000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    365.500000    3.000000    0.500000    7.000000    0.000000    3.000000   \n",
       "75%    547.750000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    730.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  730.000000  730.000000  730.000000  730.000000  730.000000  730.000000   \n",
       "mean     0.683562    1.394521   20.319259   23.726322   62.765175   12.763620   \n",
       "std      0.465405    0.544807    7.506729    8.150308   14.237589    5.195841   \n",
       "min      0.000000    1.000000    2.424346    3.953480    0.000000    1.500244   \n",
       "25%      0.000000    1.000000   13.811885   16.889713   52.000000    9.041650   \n",
       "50%      1.000000    1.000000   20.465826   24.368225   62.625000   12.125325   \n",
       "75%      1.000000    2.000000   26.880615   30.445775   72.989575   15.625589   \n",
       "max      1.000000    3.000000   35.328347   42.044800   97.250000   34.000021   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   730.000000   730.000000   730.000000  \n",
       "mean    849.249315  3658.757534  4508.006849  \n",
       "std     686.479875  1559.758728  1936.011647  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     316.250000  2502.250000  3169.750000  \n",
       "50%     717.000000  3664.500000  4548.500000  \n",
       "75%    1096.500000  4783.250000  5966.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bikes.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sanity check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 16)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check whether count of total rental bikes not including both casual and registered\n",
    "bikes[((bikes.casual+bikes.registered)!=bikes.cnt)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 16)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check if weekday is 6 or 0 whether workingday is yes(1)\n",
    "bikes.loc[((bikes['weekday']==6)|(bikes['weekday']==0))&(bikes['workingday']==1)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 16)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check if it is a holiday(1) whether workingday is yes(1)\n",
    "bikes.loc[(bikes['holiday']==1)&(bikes['workingday']==1)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>01-01-2018</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>0</td>\n",
       "      <td>Mon</td>\n",
       "      <td>0</td>\n",
       "      <td>Mist + Cloudy</td>\n",
       "      <td>14.110847</td>\n",
       "      <td>18.18125</td>\n",
       "      <td>80.5833</td>\n",
       "      <td>10.749882</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>02-01-2018</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>0</td>\n",
       "      <td>Tues</td>\n",
       "      <td>0</td>\n",
       "      <td>Mist + Cloudy</td>\n",
       "      <td>14.902598</td>\n",
       "      <td>17.68695</td>\n",
       "      <td>69.6087</td>\n",
       "      <td>16.652113</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>03-01-2018</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>0</td>\n",
       "      <td>Wed</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>8.050924</td>\n",
       "      <td>9.47025</td>\n",
       "      <td>43.7273</td>\n",
       "      <td>16.636703</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>04-01-2018</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>0</td>\n",
       "      <td>Thurs</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>10.60610</td>\n",
       "      <td>59.0435</td>\n",
       "      <td>10.739832</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>05-01-2018</td>\n",
       "      <td>spring</td>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>0</td>\n",
       "      <td>Fri</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>9.305237</td>\n",
       "      <td>11.46350</td>\n",
       "      <td>43.6957</td>\n",
       "      <td>12.522300</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr mnth  holiday weekday  workingday  \\\n",
       "0        1  01-01-2018  spring   0  Jan        0     Mon           0   \n",
       "1        2  02-01-2018  spring   0  Jan        0    Tues           0   \n",
       "2        3  03-01-2018  spring   0  Jan        0     Wed           1   \n",
       "3        4  04-01-2018  spring   0  Jan        0   Thurs           1   \n",
       "4        5  05-01-2018  spring   0  Jan        0     Fri           1   \n",
       "\n",
       "      weathersit       temp     atemp      hum  windspeed  casual  registered  \\\n",
       "0  Mist + Cloudy  14.110847  18.18125  80.5833  10.749882     331         654   \n",
       "1  Mist + Cloudy  14.902598  17.68695  69.6087  16.652113     131         670   \n",
       "2          Clear   8.050924   9.47025  43.7273  16.636703     120        1229   \n",
       "3          Clear   8.200000  10.60610  59.0435  10.739832     108        1454   \n",
       "4          Clear   9.305237  11.46350  43.6957  12.522300      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Mapping variables season, month, weathersit, weekday\n",
    "\n",
    "bikes['season']=bikes.season.map({1: 'spring', 2: 'summer',3:'fall', 4:'winter' })\n",
    "bikes['mnth']=bikes.mnth.map({1:'Jan',2:'Feb',3:'Mar',4:'Apr',5:'May',6:'June',7:'July',8:'Aug',9:'Sep',10:'Oct',11:'Nov',12:'Dec'})\n",
    "bikes['weathersit']=bikes.weathersit.map({1: 'Clear',2:'Mist + Cloudy',3:'Light Snow',4:'Snow + Fog'})\n",
    "bikes['weekday']=bikes.weekday.map({1: 'Wed', 2: 'Thurs', 3: 'Fri', 4: 'Sat', 5: 'Sun', 6: 'Mon', 0: 'Tues'})\n",
    "\n",
    "bikes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x180 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualizing the numerical variable.\n",
    "#check relationship between target variable \"cnt\" and the predictor variables\n",
    "sns.pairplot(bikes,y_vars='cnt',x_vars=['temp','atemp','hum','windspeed','casual','registered'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualizing the categorical varible\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.subplot(3,3,1)\n",
    "sns.boxplot(x='season',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,2)\n",
    "sns.barplot('season','cnt',data=bikes,palette=\"rocket\")\n",
    "plt.subplot(3,3,3)\n",
    "sns.boxplot(x='mnth',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,4)\n",
    "ax=bikes.groupby(('mnth'),sort=False)['cnt'].sum()\n",
    "ax=ax.plot.bar()\n",
    "ax.set_ylabel('cnt')\n",
    "plt.grid()\n",
    "plt.subplot(3,3,5)\n",
    "sns.boxplot(x='holiday',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,6)\n",
    "sns.boxplot(x='weekday',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,7)\n",
    "sns.boxplot(x='workingday',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,8)\n",
    "sns.boxplot(x='weathersit',y='cnt',data=bikes)\n",
    "plt.subplot(3,3,9)\n",
    "sns.boxplot(x='yr',y='cnt',data=bikes)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Bike rental is more when season is fall then summer and then winter\n",
    "- Bike rental is more between May to October month.\n",
    "- Bike rental is more when there is no holiday\n",
    "- Bike rental is more on Monday, Friday and Saturday.\n",
    "- Bike rental is more on clear weather.\n",
    "- Bike rental is more in 2019 compared to 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Heatmap\n",
    "plt.figure(figsize=(20,10))\n",
    "sns.heatmap(bikes.corr(),annot=True,cmap=\"YlGnBu\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observation:\n",
    "  - Multicollinearity between registered and cnt, temp and atemp, cnt and casual"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparing Data for Modelling."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating Dummy variables\n",
    "\n",
    "Example\n",
    "\n",
    "- Seasons:\n",
    "     - 000 will corresponds to 1:spring\n",
    "     - 100 will corresponds to 2:summer\n",
    "     - 010 will corresponds to 3:fall\n",
    "     - 001 will corresponds to 4:winter\n",
    " \n",
    "\n",
    "- weathersit:only 3 in the dataset\n",
    "     - 00 will corresponds to  1: Clear, Few clouds, Partly cloudy, Partly cloudy\n",
    "     - 10 will corresponds to  2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist\n",
    "     - 01 will corresponds to  3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating Dummy Variables and dropping a redundant variable:\n",
    "seasons = pd.get_dummies(bikes['season'],drop_first=True)\n",
    "weathers = pd.get_dummies(bikes['weathersit'],drop_first=True)\n",
    "days = pd.get_dummies(bikes['weekday'],drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>spring</th>\n",
       "      <th>summer</th>\n",
       "      <th>winter</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>Mon</th>\n",
       "      <th>Sat</th>\n",
       "      <th>Sun</th>\n",
       "      <th>Thurs</th>\n",
       "      <th>Tues</th>\n",
       "      <th>...</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Mon</td>\n",
       "      <td>0</td>\n",
       "      <td>Mist + Cloudy</td>\n",
       "      <td>14.110847</td>\n",
       "      <td>18.18125</td>\n",
       "      <td>80.5833</td>\n",
       "      <td>10.749882</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>Tues</td>\n",
       "      <td>0</td>\n",
       "      <td>Mist + Cloudy</td>\n",
       "      <td>14.902598</td>\n",
       "      <td>17.68695</td>\n",
       "      <td>69.6087</td>\n",
       "      <td>16.652113</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Wed</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>8.050924</td>\n",
       "      <td>9.47025</td>\n",
       "      <td>43.7273</td>\n",
       "      <td>16.636703</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Thurs</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>10.60610</td>\n",
       "      <td>59.0435</td>\n",
       "      <td>10.739832</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>Fri</td>\n",
       "      <td>1</td>\n",
       "      <td>Clear</td>\n",
       "      <td>9.305237</td>\n",
       "      <td>11.46350</td>\n",
       "      <td>43.6957</td>\n",
       "      <td>12.522300</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   spring  summer  winter  Light Snow  Mist + Cloudy  Mon  Sat  Sun  Thurs  \\\n",
       "0       1       0       0           0              1    1    0    0      0   \n",
       "1       1       0       0           0              1    0    0    0      0   \n",
       "2       1       0       0           0              0    0    0    0      0   \n",
       "3       1       0       0           0              0    0    0    0      1   \n",
       "4       1       0       0           0              0    0    0    0      0   \n",
       "\n",
       "   Tues  ...  weekday  workingday     weathersit       temp     atemp  \\\n",
       "0     0  ...      Mon           0  Mist + Cloudy  14.110847  18.18125   \n",
       "1     1  ...     Tues           0  Mist + Cloudy  14.902598  17.68695   \n",
       "2     0  ...      Wed           1          Clear   8.050924   9.47025   \n",
       "3     0  ...    Thurs           1          Clear   8.200000  10.60610   \n",
       "4     0  ...      Fri           1          Clear   9.305237  11.46350   \n",
       "\n",
       "       hum  windspeed casual  registered   cnt  \n",
       "0  80.5833  10.749882    331         654   985  \n",
       "1  69.6087  16.652113    131         670   801  \n",
       "2  43.7273  16.636703    120        1229  1349  \n",
       "3  59.0435  10.739832    108        1454  1562  \n",
       "4  43.6957  12.522300     82        1518  1600  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#concat the dummy variables column with original dataset\n",
    "bikes = pd.concat([seasons,weathers,days,bikes],axis=1)\n",
    "bikes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Doing label enconding because The number of categories in month is quite large as dummy variable can lead to high memory consumption.\n",
    "#In Label encoding each label is assigned a unique integer based on alphabetical ordering.\n",
    "label_encoder = preprocessing.LabelEncoder()\n",
    "bikes['mnth']= label_encoder.fit_transform(bikes['mnth'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>spring</th>\n",
       "      <th>summer</th>\n",
       "      <th>winter</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>Mon</th>\n",
       "      <th>Sat</th>\n",
       "      <th>Sun</th>\n",
       "      <th>Thurs</th>\n",
       "      <th>Tues</th>\n",
       "      <th>Wed</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>temp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>14.110847</td>\n",
       "      <td>80.5833</td>\n",
       "      <td>10.749882</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.902598</td>\n",
       "      <td>69.6087</td>\n",
       "      <td>16.652113</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.050924</td>\n",
       "      <td>43.7273</td>\n",
       "      <td>16.636703</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>59.0435</td>\n",
       "      <td>10.739832</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.305237</td>\n",
       "      <td>43.6957</td>\n",
       "      <td>12.522300</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   spring  summer  winter  Light Snow  Mist + Cloudy  Mon  Sat  Sun  Thurs  \\\n",
       "0       1       0       0           0              1    1    0    0      0   \n",
       "1       1       0       0           0              1    0    0    0      0   \n",
       "2       1       0       0           0              0    0    0    0      0   \n",
       "3       1       0       0           0              0    0    0    0      1   \n",
       "4       1       0       0           0              0    0    0    0      0   \n",
       "\n",
       "   Tues  Wed  yr  mnth  holiday  workingday       temp      hum  windspeed  \\\n",
       "0     0    0   0     4        0           0  14.110847  80.5833  10.749882   \n",
       "1     1    0   0     4        0           0  14.902598  69.6087  16.652113   \n",
       "2     0    1   0     4        0           1   8.050924  43.7273  16.636703   \n",
       "3     0    0   0     4        0           1   8.200000  59.0435  10.739832   \n",
       "4     0    0   0     4        0           1   9.305237  43.6957  12.522300   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Drop the varibles.\n",
    "#Droping season, weathersit, and weekday because dummy variable is created.\n",
    "#Droping casual and registered because of target lekage. Droping atemp because of Multicollinearity.\n",
    "bikes = bikes.drop(['season','weathersit','weekday','instant','dteday','atemp','casual','registered'],axis=1)\n",
    "bikes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Splitting data into Train and Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Dataset shape (510, 19)\n",
      "Test Dataset shape (220, 19)\n"
     ]
    }
   ],
   "source": [
    "#Split Train data into 70% and Test data in 30%.\n",
    "df_train,df_test = train_test_split(bikes,train_size=0.7,random_state=100)\n",
    "print(\"Train Dataset shape \"+str(df_train.shape))\n",
    "print(\"Test Dataset shape \"+str(df_test.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rescaling the features\n",
    "- Using MinMax scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spring</th>\n",
       "      <th>summer</th>\n",
       "      <th>winter</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>Mon</th>\n",
       "      <th>Sat</th>\n",
       "      <th>Sun</th>\n",
       "      <th>Thurs</th>\n",
       "      <th>Tues</th>\n",
       "      <th>Wed</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>temp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>510.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.243137</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.029412</td>\n",
       "      <td>0.345098</td>\n",
       "      <td>0.154902</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.127451</td>\n",
       "      <td>0.131373</td>\n",
       "      <td>0.143137</td>\n",
       "      <td>0.150980</td>\n",
       "      <td>0.507843</td>\n",
       "      <td>5.523529</td>\n",
       "      <td>0.025490</td>\n",
       "      <td>0.676471</td>\n",
       "      <td>0.537440</td>\n",
       "      <td>0.650480</td>\n",
       "      <td>0.320883</td>\n",
       "      <td>0.513499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.429398</td>\n",
       "      <td>0.431725</td>\n",
       "      <td>0.431725</td>\n",
       "      <td>0.169124</td>\n",
       "      <td>0.475867</td>\n",
       "      <td>0.362166</td>\n",
       "      <td>0.340268</td>\n",
       "      <td>0.333805</td>\n",
       "      <td>0.338139</td>\n",
       "      <td>0.350557</td>\n",
       "      <td>0.358381</td>\n",
       "      <td>0.500429</td>\n",
       "      <td>3.459907</td>\n",
       "      <td>0.157763</td>\n",
       "      <td>0.468282</td>\n",
       "      <td>0.225858</td>\n",
       "      <td>0.145846</td>\n",
       "      <td>0.169803</td>\n",
       "      <td>0.224421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.339853</td>\n",
       "      <td>0.538643</td>\n",
       "      <td>0.199179</td>\n",
       "      <td>0.356420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.542596</td>\n",
       "      <td>0.653714</td>\n",
       "      <td>0.296763</td>\n",
       "      <td>0.518638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.735215</td>\n",
       "      <td>0.754830</td>\n",
       "      <td>0.414447</td>\n",
       "      <td>0.684710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           spring      summer      winter  Light Snow  Mist + Cloudy  \\\n",
       "count  510.000000  510.000000  510.000000  510.000000     510.000000   \n",
       "mean     0.243137    0.247059    0.247059    0.029412       0.345098   \n",
       "std      0.429398    0.431725    0.431725    0.169124       0.475867   \n",
       "min      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "25%      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "50%      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "75%      0.000000    0.000000    0.000000    0.000000       1.000000   \n",
       "max      1.000000    1.000000    1.000000    1.000000       1.000000   \n",
       "\n",
       "              Mon         Sat         Sun       Thurs        Tues         Wed  \\\n",
       "count  510.000000  510.000000  510.000000  510.000000  510.000000  510.000000   \n",
       "mean     0.154902    0.133333    0.127451    0.131373    0.143137    0.150980   \n",
       "std      0.362166    0.340268    0.333805    0.338139    0.350557    0.358381   \n",
       "min      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "max      1.000000    1.000000    1.000000    1.000000    1.000000    1.000000   \n",
       "\n",
       "               yr        mnth     holiday  workingday        temp         hum  \\\n",
       "count  510.000000  510.000000  510.000000  510.000000  510.000000  510.000000   \n",
       "mean     0.507843    5.523529    0.025490    0.676471    0.537440    0.650480   \n",
       "std      0.500429    3.459907    0.157763    0.468282    0.225858    0.145846   \n",
       "min      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%      0.000000    2.000000    0.000000    0.000000    0.339853    0.538643   \n",
       "50%      1.000000    6.000000    0.000000    1.000000    0.542596    0.653714   \n",
       "75%      1.000000    8.750000    0.000000    1.000000    0.735215    0.754830   \n",
       "max      1.000000   11.000000    1.000000    1.000000    1.000000    1.000000   \n",
       "\n",
       "        windspeed         cnt  \n",
       "count  510.000000  510.000000  \n",
       "mean     0.320883    0.513499  \n",
       "std      0.169803    0.224421  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.199179    0.356420  \n",
       "50%      0.296763    0.518638  \n",
       "75%      0.414447    0.684710  \n",
       "max      1.000000    1.000000  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Instantiate an object\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "#list of numeric variables\n",
    "var = ['temp','hum','windspeed','cnt']\n",
    "\n",
    "#Fit on data\n",
    "df_train[var] = scaler.fit_transform(df_train[var])\n",
    "df_train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Heatmap\n",
    "plt.figure(figsize=(25,15))\n",
    "sns.heatmap(df_train.corr(),annot=True,cmap=\"YlGnBu\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "576    0.827658\n",
      "426    0.465255\n",
      "728    0.204096\n",
      "482    0.482973\n",
      "111    0.191095\n",
      "         ...   \n",
      "578    0.832835\n",
      "53     0.218017\n",
      "350    0.312586\n",
      "79     0.236424\n",
      "520    0.802922\n",
      "Name: cnt, Length: 510, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# X_train, y_train\n",
    "y_train = df_train.pop('cnt')\n",
    "X_train = df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Running RFE with the output number of the variable equal to 8\n",
    "lm = LinearRegression()\n",
    "lm.fit(X_train,y_train)\n",
    "rfe = RFE(lm,8)\n",
    "rfe = rfe.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('spring', True, 1),\n",
       " ('summer', False, 5),\n",
       " ('winter', False, 2),\n",
       " ('Light Snow', True, 1),\n",
       " ('Mist + Cloudy', True, 1),\n",
       " ('Mon', False, 3),\n",
       " ('Sat', False, 9),\n",
       " ('Sun', False, 11),\n",
       " ('Thurs', False, 8),\n",
       " ('Tues', False, 6),\n",
       " ('Wed', False, 7),\n",
       " ('yr', True, 1),\n",
       " ('mnth', False, 10),\n",
       " ('holiday', True, 1),\n",
       " ('workingday', False, 4),\n",
       " ('temp', True, 1),\n",
       " ('hum', True, 1),\n",
       " ('windspeed', True, 1)]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(zip(X_train.columns,rfe.support_,rfe.ranking_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>spring</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>yr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>temp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.815169</td>\n",
       "      <td>0.725633</td>\n",
       "      <td>0.264686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.442393</td>\n",
       "      <td>0.640189</td>\n",
       "      <td>0.255342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.245101</td>\n",
       "      <td>0.498067</td>\n",
       "      <td>0.663106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.395666</td>\n",
       "      <td>0.504508</td>\n",
       "      <td>0.188475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.345824</td>\n",
       "      <td>0.751824</td>\n",
       "      <td>0.380981</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     spring  Light Snow  Mist + Cloudy  yr  holiday      temp       hum  \\\n",
       "576       0           0              0   1        0  0.815169  0.725633   \n",
       "426       1           0              1   1        0  0.442393  0.640189   \n",
       "728       1           0              0   1        0  0.245101  0.498067   \n",
       "482       0           0              1   1        0  0.395666  0.504508   \n",
       "111       0           0              1   0        0  0.345824  0.751824   \n",
       "\n",
       "     windspeed  \n",
       "576   0.264686  \n",
       "426   0.255342  \n",
       "728   0.663106  \n",
       "482   0.188475  \n",
       "111   0.380981  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Creating X_test dataframe with RFE selected variables\n",
    "col = X_train.columns[rfe.support_]\n",
    "X_train = X_train[col]\n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to build model and calculate VIF of the selected variables\n",
    "def build_model(train_df):\n",
    "    X_train_sm = sm.add_constant(train_df) # add constant to the dataset.\n",
    "    model_1 = sm.OLS(y_train,X_train_sm)   #create a model\n",
    "    model_1 = model_1.fit()                #fit the model\n",
    "    print(model_1.summary())\n",
    "    \n",
    "    #calculate VIF of the variables present in the dataset\n",
    "    print(\"---------VIF-----------\")\n",
    "    vif = pd.DataFrame()\n",
    "    vif['Features']=train_df.columns\n",
    "    vif['VIF'] = [variance_inflation_factor(train_df.values,i) for i in range (train_df.shape[1])]\n",
    "    vif['VIF'] = round(vif['VIF'],2)\n",
    "    vif = vif.sort_values(by = \"VIF\",ascending = False)\n",
    "    print(vif)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                    cnt   R-squared:                       0.818\n",
      "Model:                            OLS   Adj. R-squared:                  0.815\n",
      "Method:                 Least Squares   F-statistic:                     280.9\n",
      "Date:                Mon, 31 May 2021   Prob (F-statistic):          9.95e-180\n",
      "Time:                        20:55:05   Log-Likelihood:                 472.93\n",
      "No. Observations:                 510   AIC:                            -927.9\n",
      "Df Residuals:                     501   BIC:                            -889.7\n",
      "Df Model:                           8                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "=================================================================================\n",
      "                    coef    std err          t      P>|t|      [0.025      0.975]\n",
      "---------------------------------------------------------------------------------\n",
      "const             0.3848      0.031     12.416      0.000       0.324       0.446\n",
      "spring           -0.1554      0.013    -12.232      0.000      -0.180      -0.130\n",
      "Light Snow       -0.2454      0.028     -8.730      0.000      -0.301      -0.190\n",
      "Mist + Cloudy    -0.0594      0.011     -5.338      0.000      -0.081      -0.038\n",
      "yr                0.2339      0.009     26.977      0.000       0.217       0.251\n",
      "holiday          -0.0814      0.027     -2.988      0.003      -0.135      -0.028\n",
      "temp              0.3693      0.025     15.022      0.000       0.321       0.418\n",
      "hum              -0.0989      0.039     -2.523      0.012      -0.176      -0.022\n",
      "windspeed        -0.1764      0.027     -6.500      0.000      -0.230      -0.123\n",
      "==============================================================================\n",
      "Omnibus:                       51.076   Durbin-Watson:                   2.040\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              117.654\n",
      "Skew:                          -0.541   Prob(JB):                     2.83e-26\n",
      "Kurtosis:                       5.089   Cond. No.                         18.1\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "---------VIF-----------\n",
      "        Features    VIF\n",
      "6            hum  14.16\n",
      "5           temp   9.49\n",
      "7      windspeed   3.86\n",
      "2  Mist + Cloudy   2.11\n",
      "3             yr   2.03\n",
      "0         spring   1.82\n",
      "1     Light Snow   1.19\n",
      "4        holiday   1.03\n"
     ]
    }
   ],
   "source": [
    "#build model with RFE selected variables.\n",
    "build_model(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                    cnt   R-squared:                       0.815\n",
      "Model:                            OLS   Adj. R-squared:                  0.813\n",
      "Method:                 Least Squares   F-statistic:                     316.7\n",
      "Date:                Mon, 31 May 2021   Prob (F-statistic):          1.26e-179\n",
      "Time:                        20:55:05   Log-Likelihood:                 469.71\n",
      "No. Observations:                 510   AIC:                            -923.4\n",
      "Df Residuals:                     502   BIC:                            -889.5\n",
      "Df Model:                           7                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "=================================================================================\n",
      "                    coef    std err          t      P>|t|      [0.025      0.975]\n",
      "---------------------------------------------------------------------------------\n",
      "const             0.3232      0.019     16.843      0.000       0.285       0.361\n",
      "spring           -0.1530      0.013    -12.013      0.000      -0.178      -0.128\n",
      "Light Snow       -0.2736      0.026    -10.546      0.000      -0.325      -0.223\n",
      "Mist + Cloudy    -0.0753      0.009     -8.192      0.000      -0.093      -0.057\n",
      "yr                0.2360      0.009     27.216      0.000       0.219       0.253\n",
      "holiday          -0.0829      0.027     -3.028      0.003      -0.137      -0.029\n",
      "temp              0.3606      0.024     14.736      0.000       0.313       0.409\n",
      "windspeed        -0.1558      0.026     -5.988      0.000      -0.207      -0.105\n",
      "==============================================================================\n",
      "Omnibus:                       51.693   Durbin-Watson:                   2.034\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              118.176\n",
      "Skew:                          -0.550   Prob(JB):                     2.18e-26\n",
      "Kurtosis:                       5.086   Cond. No.                         10.4\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "---------VIF-----------\n",
      "        Features   VIF\n",
      "6      windspeed  3.70\n",
      "5           temp  3.52\n",
      "3             yr  2.02\n",
      "0         spring  1.52\n",
      "2  Mist + Cloudy  1.46\n",
      "1     Light Snow  1.06\n",
      "4        holiday  1.03\n"
     ]
    }
   ],
   "source": [
    "#drop 'hum' because of high VIF and build the model.\n",
    "X_train = X_train.drop('hum',axis=1)\n",
    "build_model(X_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Residual Analysis of the train data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#build the final model with the variable present in the train dataset and predict the target train variable.\n",
    "\n",
    "X_train_sm = sm.add_constant(X_train) # add constant to the final dataset.\n",
    "model = sm.OLS(y_train,X_train_sm)    #create a model\n",
    "model = model.fit()                   #fit the model\n",
    "y_train_cnt = model.predict(X_train_sm)\n",
    "res = model.resid                     #residuals "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot the histogram of the error terms\n",
    "fig = plt.figure\n",
    "sns.distplot((y_train -  y_train_cnt),bins=20)\n",
    "plt.title(\"Error Terms\",fontsize=20)\n",
    "plt.xlabel(\"Errors\",fontsize=15)\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check for Homoscedasticity and Independence of Error\n",
    "p = sns.scatterplot(y_train_cnt,(res))\n",
    "plt.xlabel('Predicted Y value')\n",
    "plt.ylabel('Residuals')\n",
    "p = sns.lineplot([0,1.0],[0,0],color='red')\n",
    "p = sns.lineplot([0,1.0],[0.2,0.2],color='red')\n",
    "p = sns.lineplot([0,1.0],[-0.2,-0.2],color='red')\n",
    "p = plt.title('Residuals vs Predicted values')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Making Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>spring</th>\n",
       "      <th>summer</th>\n",
       "      <th>winter</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>Mon</th>\n",
       "      <th>Sat</th>\n",
       "      <th>Sun</th>\n",
       "      <th>Thurs</th>\n",
       "      <th>Tues</th>\n",
       "      <th>Wed</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>temp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>220.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.254545</td>\n",
       "      <td>0.263636</td>\n",
       "      <td>0.236364</td>\n",
       "      <td>0.027273</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.118182</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.177273</td>\n",
       "      <td>0.168182</td>\n",
       "      <td>0.145455</td>\n",
       "      <td>0.127273</td>\n",
       "      <td>0.481818</td>\n",
       "      <td>5.477273</td>\n",
       "      <td>0.036364</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.558718</td>\n",
       "      <td>0.638221</td>\n",
       "      <td>0.313293</td>\n",
       "      <td>0.522154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.436599</td>\n",
       "      <td>0.441609</td>\n",
       "      <td>0.425817</td>\n",
       "      <td>0.163248</td>\n",
       "      <td>0.466833</td>\n",
       "      <td>0.323559</td>\n",
       "      <td>0.370789</td>\n",
       "      <td>0.382770</td>\n",
       "      <td>0.374881</td>\n",
       "      <td>0.353363</td>\n",
       "      <td>0.334038</td>\n",
       "      <td>0.500809</td>\n",
       "      <td>3.438226</td>\n",
       "      <td>0.187620</td>\n",
       "      <td>0.459303</td>\n",
       "      <td>0.233187</td>\n",
       "      <td>0.148694</td>\n",
       "      <td>0.159584</td>\n",
       "      <td>0.219163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.046591</td>\n",
       "      <td>0.261915</td>\n",
       "      <td>-0.042808</td>\n",
       "      <td>0.048205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.355429</td>\n",
       "      <td>0.529197</td>\n",
       "      <td>0.198843</td>\n",
       "      <td>0.378595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.558172</td>\n",
       "      <td>0.625590</td>\n",
       "      <td>0.300126</td>\n",
       "      <td>0.524678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.755981</td>\n",
       "      <td>0.743798</td>\n",
       "      <td>0.402718</td>\n",
       "      <td>0.677750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.984424</td>\n",
       "      <td>1.002146</td>\n",
       "      <td>0.807474</td>\n",
       "      <td>0.963300</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           spring      summer      winter  Light Snow  Mist + Cloudy  \\\n",
       "count  220.000000  220.000000  220.000000  220.000000     220.000000   \n",
       "mean     0.254545    0.263636    0.236364    0.027273       0.318182   \n",
       "std      0.436599    0.441609    0.425817    0.163248       0.466833   \n",
       "min      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "25%      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "50%      0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "75%      1.000000    1.000000    0.000000    0.000000       1.000000   \n",
       "max      1.000000    1.000000    1.000000    1.000000       1.000000   \n",
       "\n",
       "              Mon         Sat         Sun       Thurs        Tues         Wed  \\\n",
       "count  220.000000  220.000000  220.000000  220.000000  220.000000  220.000000   \n",
       "mean     0.118182    0.163636    0.177273    0.168182    0.145455    0.127273   \n",
       "std      0.323559    0.370789    0.382770    0.374881    0.353363    0.334038   \n",
       "min      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "max      1.000000    1.000000    1.000000    1.000000    1.000000    1.000000   \n",
       "\n",
       "               yr        mnth     holiday  workingday        temp         hum  \\\n",
       "count  220.000000  220.000000  220.000000  220.000000  220.000000  220.000000   \n",
       "mean     0.481818    5.477273    0.036364    0.700000    0.558718    0.638221   \n",
       "std      0.500809    3.438226    0.187620    0.459303    0.233187    0.148694   \n",
       "min      0.000000    0.000000    0.000000    0.000000    0.046591    0.261915   \n",
       "25%      0.000000    3.000000    0.000000    0.000000    0.355429    0.529197   \n",
       "50%      0.000000    5.000000    0.000000    1.000000    0.558172    0.625590   \n",
       "75%      1.000000    8.000000    0.000000    1.000000    0.755981    0.743798   \n",
       "max      1.000000   11.000000    1.000000    1.000000    0.984424    1.002146   \n",
       "\n",
       "        windspeed         cnt  \n",
       "count  220.000000  220.000000  \n",
       "mean     0.313293    0.522154  \n",
       "std      0.159584    0.219163  \n",
       "min     -0.042808    0.048205  \n",
       "25%      0.198843    0.378595  \n",
       "50%      0.300126    0.524678  \n",
       "75%      0.402718    0.677750  \n",
       "max      0.807474    0.963300  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Applying scaling on test dataset\n",
    "test_var = ['temp','hum','windspeed','cnt']\n",
    "\n",
    "#Fit on data\n",
    "df_test[test_var] = scaler.transform(df_test[test_var])\n",
    "df_test.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create X_test and y_test\n",
    "y_test = df_test.pop('cnt')\n",
    "X_test = df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Remove columns from X_test which is not present on X_train\n",
    "X_test = X_test[X_train.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>const</th>\n",
       "      <th>spring</th>\n",
       "      <th>Light Snow</th>\n",
       "      <th>Mist + Cloudy</th>\n",
       "      <th>yr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>temp</th>\n",
       "      <th>windspeed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.831783</td>\n",
       "      <td>0.084219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.901354</td>\n",
       "      <td>0.153728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.511964</td>\n",
       "      <td>0.334206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.881625</td>\n",
       "      <td>0.339570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.817246</td>\n",
       "      <td>0.537414</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     const  spring  Light Snow  Mist + Cloudy  yr  holiday      temp  \\\n",
       "184    1.0       0           0              1   0        1  0.831783   \n",
       "535    1.0       0           0              0   1        0  0.901354   \n",
       "299    1.0       0           0              1   0        0  0.511964   \n",
       "221    1.0       0           0              0   0        0  0.881625   \n",
       "152    1.0       0           0              0   0        0  0.817246   \n",
       "\n",
       "     windspeed  \n",
       "184   0.084219  \n",
       "535   0.153728  \n",
       "299   0.334206  \n",
       "221   0.339570  \n",
       "152   0.537414  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Adding a constant variable\n",
    "X_test = sm.add_constant(X_test)\n",
    "X_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Making Prediction\n",
    "y_predict = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Regression plot\n",
    "plt.figure(figsize=(10,5))\n",
    "sns.regplot(x=y_test, y=y_predict, ci=68, fit_reg=True,scatter_kws={\"color\": \"blue\"}, line_kws={\"color\": \"red\"})\n",
    "plt.title('y_test vs y_pred', fontsize=20)            \n",
    "plt.xlabel('y_test', fontsize=18)                         \n",
    "plt.ylabel('y_pred', fontsize=16)\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## R-squared score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7958771639220968"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#R-squared score on the test set\n",
    "r2_score(y_true=y_test,y_pred=y_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7891372589572604"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adjusted R squared of test set\n",
    "# Adj R_2 = 1 - ((1 - R2)(N - 1)/ N - P - 1)      \n",
    "#N = Number of rows in the test dataset; P is number of predictor variables excluding constant.\n",
    "r2 = r2_score(y_true=y_test,y_pred=y_predict)\n",
    "adjr2 = 1 - ((1-r2)*(220-1) / (220 - 7- 1))\n",
    "adjr2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Train: R squared 0.815; Adjusted R squared 0.813\n",
    "- Test : R squared 0.796; Adjusted R squared 0.789\n",
    "- Difference in R squared between Test and Train dataset is 1.9%\n",
    "- Difference in Adjusted R squared between Test and Train dataset is 2.4%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the equation of our best fitted line is:\n",
    "\n",
    "y = 0.3232 + (-0.1530) X spring +  (-0.2736) X Light snow + (-0.0753) X Mist+cloudy + ( 0.2360) X yr  + ( -0.0829) X holiday + (0.3606) X temp + (-0.1558) X windspeed\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "- We can see that temperature variable is having the highest coefficient 0.4915, which means if the temperature increases by one unit the number of bike rentals increases by 0.4915 units.\n",
    "- some variables with negative coefficients, A negative coefficient suggests that as the independent variable increases, the dependent variable tends to decrease. We have spring, light snow, Mist+cloudy, and holiday variables with negative coefficient.\n",
    "\n",
    "## Interpretation\n",
    "- We can see demand for bikes was more in 2019 than 2018,So we can assume after the end of Pandemic the business will surely grow.\n",
    "- BoomBikes focus on Temperature, as Temperature increases in US (From May to September) people uses bikes more.\n",
    "- On Working day people uses bikes more.\n",
    "- On Clear weather with less wind people uses bikes more."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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