Regression Problem.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6dceb0fd",
   "metadata": {},
   "source": [
    "#  Linear Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70800269",
   "metadata": {},
   "source": [
    "## Required Libraries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "4ad6681e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "from matplotlib import pyplot as plt \n",
    "import seaborn as sns \n",
    "\n",
    "from sklearn import linear_model as lin\n",
    "from sklearn import model_selection as mod\n",
    "from sklearn import metrics as met\n",
    "from sklearn import preprocessing as pre\n",
    "from sklearn import pipeline as pip"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d61af257",
   "metadata": {},
   "source": [
    "## Data & Basic Details "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "96f6b591",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_day = pd.read_csv(\"data/day.csv\")\n",
    "df_hour = pd.read_csv(\"data/hour.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "2b03b3f4",
   "metadata": {},
   "outputs": [
    {
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       "  <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>2011-01-01</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",
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       "      <td>0.160446</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>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</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>2011-01-04</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>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</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>2011-01-05</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>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</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  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_day.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "c12f9d2d",
   "metadata": {},
   "outputs": [
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       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
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       "      <th>9</th>\n",
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       "      <td>2011-01-01</td>\n",
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       "      <th>10</th>\n",
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       "      <td>2011-01-01</td>\n",
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       "      <td>2011-01-01</td>\n",
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       "      <td>0.36</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>29</td>\n",
       "      <td>55</td>\n",
       "      <td>84</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
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       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>94</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>35</td>\n",
       "      <td>71</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.4394</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>40</td>\n",
       "      <td>70</td>\n",
       "      <td>110</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>41</td>\n",
       "      <td>52</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.4394</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>15</td>\n",
       "      <td>52</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.4091</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>11</td>\n",
       "      <td>25</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.4091</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.4091</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.2239</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>15</td>\n",
       "      <td>24</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>2011-01-02</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>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</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>2</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.4394</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.4545</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.4091</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.4091</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.2239</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.3939</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.2239</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.2239</td>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>16</td>\n",
       "      <td>54</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>20</td>\n",
       "      <td>73</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>11</td>\n",
       "      <td>64</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>4</td>\n",
       "      <td>55</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>19</td>\n",
       "      <td>55</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>9</td>\n",
       "      <td>67</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>7</td>\n",
       "      <td>58</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.3284</td>\n",
       "      <td>10</td>\n",
       "      <td>43</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.4478</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.3582</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2273</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.3284</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2121</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2273</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.1970</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.3582</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.1667</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.4179</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.3881</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.1061</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.3881</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.1940</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.1212</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>1</td>\n",
       "      <td>153</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.3881</td>\n",
       "      <td>7</td>\n",
       "      <td>81</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.1667</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.1818</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.3284</td>\n",
       "      <td>10</td>\n",
       "      <td>41</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2121</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.2985</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2121</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>8</td>\n",
       "      <td>53</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2424</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.2836</td>\n",
       "      <td>11</td>\n",
       "      <td>66</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    instant      dteday  season  yr  mnth  hr  holiday  weekday  workingday  \\\n",
       "0         1  2011-01-01       1   0     1   0        0        6           0   \n",
       "1         2  2011-01-01       1   0     1   1        0        6           0   \n",
       "2         3  2011-01-01       1   0     1   2        0        6           0   \n",
       "3         4  2011-01-01       1   0     1   3        0        6           0   \n",
       "4         5  2011-01-01       1   0     1   4        0        6           0   \n",
       "5         6  2011-01-01       1   0     1   5        0        6           0   \n",
       "6         7  2011-01-01       1   0     1   6        0        6           0   \n",
       "7         8  2011-01-01       1   0     1   7        0        6           0   \n",
       "8         9  2011-01-01       1   0     1   8        0        6           0   \n",
       "9        10  2011-01-01       1   0     1   9        0        6           0   \n",
       "10       11  2011-01-01       1   0     1  10        0        6           0   \n",
       "11       12  2011-01-01       1   0     1  11        0        6           0   \n",
       "12       13  2011-01-01       1   0     1  12        0        6           0   \n",
       "13       14  2011-01-01       1   0     1  13        0        6           0   \n",
       "14       15  2011-01-01       1   0     1  14        0        6           0   \n",
       "15       16  2011-01-01       1   0     1  15        0        6           0   \n",
       "16       17  2011-01-01       1   0     1  16        0        6           0   \n",
       "17       18  2011-01-01       1   0     1  17        0        6           0   \n",
       "18       19  2011-01-01       1   0     1  18        0        6           0   \n",
       "19       20  2011-01-01       1   0     1  19        0        6           0   \n",
       "20       21  2011-01-01       1   0     1  20        0        6           0   \n",
       "21       22  2011-01-01       1   0     1  21        0        6           0   \n",
       "22       23  2011-01-01       1   0     1  22        0        6           0   \n",
       "23       24  2011-01-01       1   0     1  23        0        6           0   \n",
       "24       25  2011-01-02       1   0     1   0        0        0           0   \n",
       "25       26  2011-01-02       1   0     1   1        0        0           0   \n",
       "26       27  2011-01-02       1   0     1   2        0        0           0   \n",
       "27       28  2011-01-02       1   0     1   3        0        0           0   \n",
       "28       29  2011-01-02       1   0     1   4        0        0           0   \n",
       "29       30  2011-01-02       1   0     1   6        0        0           0   \n",
       "30       31  2011-01-02       1   0     1   7        0        0           0   \n",
       "31       32  2011-01-02       1   0     1   8        0        0           0   \n",
       "32       33  2011-01-02       1   0     1   9        0        0           0   \n",
       "33       34  2011-01-02       1   0     1  10        0        0           0   \n",
       "34       35  2011-01-02       1   0     1  11        0        0           0   \n",
       "35       36  2011-01-02       1   0     1  12        0        0           0   \n",
       "36       37  2011-01-02       1   0     1  13        0        0           0   \n",
       "37       38  2011-01-02       1   0     1  14        0        0           0   \n",
       "38       39  2011-01-02       1   0     1  15        0        0           0   \n",
       "39       40  2011-01-02       1   0     1  16        0        0           0   \n",
       "40       41  2011-01-02       1   0     1  17        0        0           0   \n",
       "41       42  2011-01-02       1   0     1  18        0        0           0   \n",
       "42       43  2011-01-02       1   0     1  19        0        0           0   \n",
       "43       44  2011-01-02       1   0     1  20        0        0           0   \n",
       "44       45  2011-01-02       1   0     1  21        0        0           0   \n",
       "45       46  2011-01-02       1   0     1  22        0        0           0   \n",
       "46       47  2011-01-02       1   0     1  23        0        0           0   \n",
       "47       48  2011-01-03       1   0     1   0        0        1           1   \n",
       "48       49  2011-01-03       1   0     1   1        0        1           1   \n",
       "49       50  2011-01-03       1   0     1   4        0        1           1   \n",
       "50       51  2011-01-03       1   0     1   5        0        1           1   \n",
       "51       52  2011-01-03       1   0     1   6        0        1           1   \n",
       "52       53  2011-01-03       1   0     1   7        0        1           1   \n",
       "53       54  2011-01-03       1   0     1   8        0        1           1   \n",
       "54       55  2011-01-03       1   0     1   9        0        1           1   \n",
       "55       56  2011-01-03       1   0     1  10        0        1           1   \n",
       "56       57  2011-01-03       1   0     1  11        0        1           1   \n",
       "57       58  2011-01-03       1   0     1  12        0        1           1   \n",
       "58       59  2011-01-03       1   0     1  13        0        1           1   \n",
       "59       60  2011-01-03       1   0     1  14        0        1           1   \n",
       "\n",
       "    weathersit  temp   atemp   hum  windspeed  casual  registered  cnt  \n",
       "0            1  0.24  0.2879  0.81     0.0000       3          13   16  \n",
       "1            1  0.22  0.2727  0.80     0.0000       8          32   40  \n",
       "2            1  0.22  0.2727  0.80     0.0000       5          27   32  \n",
       "3            1  0.24  0.2879  0.75     0.0000       3          10   13  \n",
       "4            1  0.24  0.2879  0.75     0.0000       0           1    1  \n",
       "5            2  0.24  0.2576  0.75     0.0896       0           1    1  \n",
       "6            1  0.22  0.2727  0.80     0.0000       2           0    2  \n",
       "7            1  0.20  0.2576  0.86     0.0000       1           2    3  \n",
       "8            1  0.24  0.2879  0.75     0.0000       1           7    8  \n",
       "9            1  0.32  0.3485  0.76     0.0000       8           6   14  \n",
       "10           1  0.38  0.3939  0.76     0.2537      12          24   36  \n",
       "11           1  0.36  0.3333  0.81     0.2836      26          30   56  \n",
       "12           1  0.42  0.4242  0.77     0.2836      29          55   84  \n",
       "13           2  0.46  0.4545  0.72     0.2985      47          47   94  \n",
       "14           2  0.46  0.4545  0.72     0.2836      35          71  106  \n",
       "15           2  0.44  0.4394  0.77     0.2985      40          70  110  \n",
       "16           2  0.42  0.4242  0.82     0.2985      41          52   93  \n",
       "17           2  0.44  0.4394  0.82     0.2836      15          52   67  \n",
       "18           3  0.42  0.4242  0.88     0.2537       9          26   35  \n",
       "19           3  0.42  0.4242  0.88     0.2537       6          31   37  \n",
       "20           2  0.40  0.4091  0.87     0.2537      11          25   36  \n",
       "21           2  0.40  0.4091  0.87     0.1940       3          31   34  \n",
       "22           2  0.40  0.4091  0.94     0.2239      11          17   28  \n",
       "23           2  0.46  0.4545  0.88     0.2985      15          24   39  \n",
       "24           2  0.46  0.4545  0.88     0.2985       4          13   17  \n",
       "25           2  0.44  0.4394  0.94     0.2537       1          16   17  \n",
       "26           2  0.42  0.4242  1.00     0.2836       1           8    9  \n",
       "27           2  0.46  0.4545  0.94     0.1940       2           4    6  \n",
       "28           2  0.46  0.4545  0.94     0.1940       2           1    3  \n",
       "29           3  0.42  0.4242  0.77     0.2985       0           2    2  \n",
       "30           2  0.40  0.4091  0.76     0.1940       0           1    1  \n",
       "31           3  0.40  0.4091  0.71     0.2239       0           8    8  \n",
       "32           2  0.38  0.3939  0.76     0.2239       1          19   20  \n",
       "33           2  0.36  0.3485  0.81     0.2239       7          46   53  \n",
       "34           2  0.36  0.3333  0.71     0.2537      16          54   70  \n",
       "35           2  0.36  0.3333  0.66     0.2985      20          73   93  \n",
       "36           2  0.36  0.3485  0.66     0.1343      11          64   75  \n",
       "37           3  0.36  0.3485  0.76     0.1940       4          55   59  \n",
       "38           3  0.34  0.3333  0.81     0.1642      19          55   74  \n",
       "39           3  0.34  0.3333  0.71     0.1642       9          67   76  \n",
       "40           1  0.34  0.3333  0.57     0.1940       7          58   65  \n",
       "41           2  0.36  0.3333  0.46     0.3284      10          43   53  \n",
       "42           1  0.32  0.2879  0.42     0.4478       1          29   30  \n",
       "43           1  0.30  0.2727  0.39     0.3582       5          17   22  \n",
       "44           1  0.26  0.2273  0.44     0.3284      11          20   31  \n",
       "45           1  0.24  0.2121  0.44     0.2985       0           9    9  \n",
       "46           1  0.22  0.2273  0.47     0.1642       0           8    8  \n",
       "47           1  0.22  0.1970  0.44     0.3582       0           5    5  \n",
       "48           1  0.20  0.1667  0.44     0.4179       0           2    2  \n",
       "49           1  0.16  0.1364  0.47     0.3881       0           1    1  \n",
       "50           1  0.16  0.1364  0.47     0.2836       0           3    3  \n",
       "51           1  0.14  0.1061  0.50     0.3881       0          30   30  \n",
       "52           1  0.14  0.1364  0.50     0.1940       1          63   64  \n",
       "53           1  0.14  0.1212  0.50     0.2836       1         153  154  \n",
       "54           1  0.16  0.1364  0.43     0.3881       7          81   88  \n",
       "55           1  0.18  0.1667  0.43     0.2537      11          33   44  \n",
       "56           1  0.20  0.1818  0.40     0.3284      10          41   51  \n",
       "57           1  0.22  0.2121  0.35     0.2985      13          48   61  \n",
       "58           1  0.24  0.2121  0.35     0.2836       8          53   61  \n",
       "59           1  0.26  0.2424  0.30     0.2836      11          66   77  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hour.head(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "259751d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   instant     731 non-null    int64  \n",
      " 1   dteday      731 non-null    object \n",
      " 2   season      731 non-null    int64  \n",
      " 3   yr          731 non-null    int64  \n",
      " 4   mnth        731 non-null    int64  \n",
      " 5   holiday     731 non-null    int64  \n",
      " 6   weekday     731 non-null    int64  \n",
      " 7   workingday  731 non-null    int64  \n",
      " 8   weathersit  731 non-null    int64  \n",
      " 9   temp        731 non-null    float64\n",
      " 10  atemp       731 non-null    float64\n",
      " 11  hum         731 non-null    float64\n",
      " 12  windspeed   731 non-null    float64\n",
      " 13  casual      731 non-null    int64  \n",
      " 14  registered  731 non-null    int64  \n",
      " 15  cnt         731 non-null    int64  \n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(df_day.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "52e53cbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</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>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</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>183.500000</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>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</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>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</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>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</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>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</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  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_day.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "5ea8bdd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 17379 entries, 0 to 17378\n",
      "Data columns (total 17 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   instant     17379 non-null  int64  \n",
      " 1   dteday      17379 non-null  object \n",
      " 2   season      17379 non-null  int64  \n",
      " 3   yr          17379 non-null  int64  \n",
      " 4   mnth        17379 non-null  int64  \n",
      " 5   hr          17379 non-null  int64  \n",
      " 6   holiday     17379 non-null  int64  \n",
      " 7   weekday     17379 non-null  int64  \n",
      " 8   workingday  17379 non-null  int64  \n",
      " 9   weathersit  17379 non-null  int64  \n",
      " 10  temp        17379 non-null  float64\n",
      " 11  atemp       17379 non-null  float64\n",
      " 12  hum         17379 non-null  float64\n",
      " 13  windspeed   17379 non-null  float64\n",
      " 14  casual      17379 non-null  int64  \n",
      " 15  registered  17379 non-null  int64  \n",
      " 16  cnt         17379 non-null  int64  \n",
      "dtypes: float64(4), int64(12), object(1)\n",
      "memory usage: 2.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df_hour.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "7cd27397",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</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>17379.0000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>2.501640</td>\n",
       "      <td>0.502561</td>\n",
       "      <td>6.537775</td>\n",
       "      <td>11.546752</td>\n",
       "      <td>0.028770</td>\n",
       "      <td>3.003683</td>\n",
       "      <td>0.682721</td>\n",
       "      <td>1.425283</td>\n",
       "      <td>0.496987</td>\n",
       "      <td>0.475775</td>\n",
       "      <td>0.627229</td>\n",
       "      <td>0.190098</td>\n",
       "      <td>35.676218</td>\n",
       "      <td>153.786869</td>\n",
       "      <td>189.463088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5017.0295</td>\n",
       "      <td>1.106918</td>\n",
       "      <td>0.500008</td>\n",
       "      <td>3.438776</td>\n",
       "      <td>6.914405</td>\n",
       "      <td>0.167165</td>\n",
       "      <td>2.005771</td>\n",
       "      <td>0.465431</td>\n",
       "      <td>0.639357</td>\n",
       "      <td>0.192556</td>\n",
       "      <td>0.171850</td>\n",
       "      <td>0.192930</td>\n",
       "      <td>0.122340</td>\n",
       "      <td>49.305030</td>\n",
       "      <td>151.357286</td>\n",
       "      <td>181.387599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0000</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>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4345.5000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>0.333300</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.104500</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.484800</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>142.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>13034.5000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>0.621200</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.253700</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>281.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17379.0000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850700</td>\n",
       "      <td>367.000000</td>\n",
       "      <td>886.000000</td>\n",
       "      <td>977.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant        season            yr          mnth            hr  \\\n",
       "count  17379.0000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean    8690.0000      2.501640      0.502561      6.537775     11.546752   \n",
       "std     5017.0295      1.106918      0.500008      3.438776      6.914405   \n",
       "min        1.0000      1.000000      0.000000      1.000000      0.000000   \n",
       "25%     4345.5000      2.000000      0.000000      4.000000      6.000000   \n",
       "50%     8690.0000      3.000000      1.000000      7.000000     12.000000   \n",
       "75%    13034.5000      3.000000      1.000000     10.000000     18.000000   \n",
       "max    17379.0000      4.000000      1.000000     12.000000     23.000000   \n",
       "\n",
       "            holiday       weekday    workingday    weathersit          temp  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.028770      3.003683      0.682721      1.425283      0.496987   \n",
       "std        0.167165      2.005771      0.465431      0.639357      0.192556   \n",
       "min        0.000000      0.000000      0.000000      1.000000      0.020000   \n",
       "25%        0.000000      1.000000      0.000000      1.000000      0.340000   \n",
       "50%        0.000000      3.000000      1.000000      1.000000      0.500000   \n",
       "75%        0.000000      5.000000      1.000000      2.000000      0.660000   \n",
       "max        1.000000      6.000000      1.000000      4.000000      1.000000   \n",
       "\n",
       "              atemp           hum     windspeed        casual    registered  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.475775      0.627229      0.190098     35.676218    153.786869   \n",
       "std        0.171850      0.192930      0.122340     49.305030    151.357286   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.333300      0.480000      0.104500      4.000000     34.000000   \n",
       "50%        0.484800      0.630000      0.194000     17.000000    115.000000   \n",
       "75%        0.621200      0.780000      0.253700     48.000000    220.000000   \n",
       "max        1.000000      1.000000      0.850700    367.000000    886.000000   \n",
       "\n",
       "                cnt  \n",
       "count  17379.000000  \n",
       "mean     189.463088  \n",
       "std      181.387599  \n",
       "min        1.000000  \n",
       "25%       40.000000  \n",
       "50%      142.000000  \n",
       "75%      281.000000  \n",
       "max      977.000000  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hour.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dd58593",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dce0f55d",
   "metadata": {},
   "source": [
    "Our data is clear and interaptable. Therefore we don't need to make any preprocessing step. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be38c095",
   "metadata": {},
   "source": [
    "## Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3edeb4d",
   "metadata": {},
   "source": [
    "### Correlation Between Features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c287808",
   "metadata": {},
   "source": [
    "#### For Day dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "05b19496",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "heatmap = sns.heatmap(df_day.corr(), vmin=-1, vmax=1, annot=True)\n",
    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':12}, pad=12);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "fba7ae9c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cnt_corr_day = pd.DataFrame(df_day.corr()[\"cnt\"].sort_values(ascending=False))\n",
    "df_cnt_corr_day.columns=[\"CorrelationWithCNT\"]\n",
    "plt.figure(figsize=(8, 6), dpi=80)\n",
    "heatmap = sns.heatmap(df_cnt_corr_day, vmin=-1, vmax=1, annot=True)\n",
    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':12}, pad=12);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "615be60c",
   "metadata": {},
   "source": [
    "#### For Hour dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "a976548d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "heatmap = sns.heatmap(df_hour.corr(), vmin=-1, vmax=1, annot=True)\n",
    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':12}, pad=12);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "444567d5",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cnt_corr_hour = pd.DataFrame(df_hour.corr()[\"cnt\"].sort_values(ascending=False))\n",
    "df_cnt_corr_hour.columns=[\"CorrelationWithCNT\"]\n",
    "plt.figure(figsize=(8, 6), dpi=80)\n",
    "heatmap = sns.heatmap(df_cnt_corr_hour, vmin=-1, vmax=1, annot=True)\n",
    "# Give a title to the heatmap. Pad defines the distance of the title from the top of the heatmap.\n",
    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':12}, pad=12);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89b5f024",
   "metadata": {},
   "source": [
    "I've choose hourly data for machine learning model. After that, I'll just show details of hourly data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1c078408",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hour_numeric = df_hour.select_dtypes(exclude=['object'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "617afa2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_rows=4\n",
    "n_cols=4\n",
    "fig, axes = plt.subplots(nrows=n_rows, ncols=n_cols,figsize=(20, 20))\n",
    "for i, column in enumerate(df_hour_numeric.columns):\n",
    "    sns.histplot(df_hour_numeric[column],ax=axes[i//n_cols,i%n_cols])    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48ab9964",
   "metadata": {},
   "source": [
    "## Machine Learning Steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "8761567e",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df_hour.drop([\"cnt\",\"dteday\"],axis=1)\n",
    "y = df_hour[\"cnt\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "fa4e8a30",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(17379, 15) --> Shape of X\n",
      "(17379,) --> Shape of y\n"
     ]
    }
   ],
   "source": [
    "print(str(X.shape) + ' --> Shape of X')\n",
    "print(str(y.shape) + ' --> Shape of y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "b087554f",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = mod.train_test_split(X, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "8b89b94c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11643, 15) --> Shape of X_train\n",
      "(5736, 15) --> Shape of X_test\n",
      "(11643,) --> Shape of y_train\n",
      "(5736,) --> Shape of y_test\n"
     ]
    }
   ],
   "source": [
    "print(str(X_train.shape) + ' --> Shape of X_train')\n",
    "print(str(X_test.shape) + ' --> Shape of X_test')\n",
    "print(str(y_train.shape) + ' --> Shape of y_train')\n",
    "print(str(y_test.shape) + ' --> Shape of y_test')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "70253d14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('scaler', StandardScaler()),\n",
       "                ('reg', SGDRegressor(max_iter=100))])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe = pip.Pipeline([\n",
    "            (\"scaler\", pre.StandardScaler()), # fit & transform\n",
    "            (\"reg\", lin.SGDRegressor(max_iter=100)) # fit\n",
    "])\n",
    "\n",
    "pipe.fit(X_train, y_train.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "3f57a35d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([424.91590113,  87.97441145,   3.98494946, ..., 161.00145764,\n",
       "       633.91708967, 115.99287572])"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = pipe.predict(X_test)\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "4a05c663",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06713783002982793"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "met.mean_squared_error(y_test, y_pred, squared=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "5f670dec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.05817314, -0.05531972, -0.06345055])"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "pipe = pip.Pipeline([\n",
    "          (\"scaler\", pre.StandardScaler()),\n",
    "          (\"reg\", lin.SGDRegressor())\n",
    "])\n",
    "\n",
    "mod.cross_val_score(pipe, X_train, y_train.ravel(), scoring=\"neg_root_mean_squared_error\", cv=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "56e15691",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=3,\n",
       "             estimator=Pipeline(steps=[('scaler', StandardScaler()),\n",
       "                                       ('reg', SGDRegressor(random_state=42))]),\n",
       "             param_grid={'reg__alpha': [0.0001, 0.0002, 0.0003],\n",
       "                         'reg__eta0': [0.1, 0.2, 0.3], 'reg__penalty': ['l1']},\n",
       "             scoring='neg_root_mean_squared_error')"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe = pip.Pipeline([\n",
    "          (\"scaler\", pre.StandardScaler()),\n",
    "          (\"reg\", lin.SGDRegressor(random_state=42))\n",
    "])\n",
    "\n",
    "params = {\n",
    "    \"reg__penalty\": [\"l1\"],\n",
    "    \"reg__alpha\": [0.0001, 0.0002, 0.0003],\n",
    "    \"reg__eta0\": [0.1, 0.2, 0.3]\n",
    "}\n",
    "\n",
    "grid = mod.GridSearchCV(pipe, params, scoring=\"neg_root_mean_squared_error\", cv=3)\n",
    "grid.fit(X_train, y_train.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "26bb1efb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_reg__alpha</th>\n",
       "      <th>param_reg__eta0</th>\n",
       "      <th>param_reg__penalty</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.025002</td>\n",
       "      <td>0.005386</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>4.791264e-04</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.1</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0001, 'reg__eta0': 0.1, 'reg_...</td>\n",
       "      <td>-0.020412</td>\n",
       "      <td>-0.011934</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>-0.017135</td>\n",
       "      <td>0.003719</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.019331</td>\n",
       "      <td>0.003299</td>\n",
       "      <td>0.002001</td>\n",
       "      <td>3.893359e-07</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.2</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0001, 'reg__eta0': 0.2, 'reg_...</td>\n",
       "      <td>-0.035436</td>\n",
       "      <td>-0.024942</td>\n",
       "      <td>-0.027250</td>\n",
       "      <td>-0.029209</td>\n",
       "      <td>0.004503</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.263365</td>\n",
       "      <td>0.022306</td>\n",
       "      <td>0.001662</td>\n",
       "      <td>4.764767e-04</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.3</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0001, 'reg__eta0': 0.3, 'reg_...</td>\n",
       "      <td>-0.089393</td>\n",
       "      <td>-0.083136</td>\n",
       "      <td>-0.093578</td>\n",
       "      <td>-0.088702</td>\n",
       "      <td>0.004291</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.017315</td>\n",
       "      <td>0.000932</td>\n",
       "      <td>0.002001</td>\n",
       "      <td>1.381091e-06</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.1</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0002, 'reg__eta0': 0.1, 'reg_...</td>\n",
       "      <td>-0.017686</td>\n",
       "      <td>-0.009569</td>\n",
       "      <td>-0.017125</td>\n",
       "      <td>-0.014793</td>\n",
       "      <td>0.003701</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.020010</td>\n",
       "      <td>0.001407</td>\n",
       "      <td>0.001668</td>\n",
       "      <td>4.725549e-04</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.2</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0002, 'reg__eta0': 0.2, 'reg_...</td>\n",
       "      <td>-0.031440</td>\n",
       "      <td>-0.021246</td>\n",
       "      <td>-0.023699</td>\n",
       "      <td>-0.025462</td>\n",
       "      <td>0.004344</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.263691</td>\n",
       "      <td>0.026805</td>\n",
       "      <td>0.001975</td>\n",
       "      <td>1.721720e-05</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.3</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0002, 'reg__eta0': 0.3, 'reg_...</td>\n",
       "      <td>-0.090381</td>\n",
       "      <td>-0.077473</td>\n",
       "      <td>-0.087812</td>\n",
       "      <td>-0.085222</td>\n",
       "      <td>0.005579</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.019665</td>\n",
       "      <td>0.000945</td>\n",
       "      <td>0.002001</td>\n",
       "      <td>8.920806e-07</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.1</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0003, 'reg__eta0': 0.1, 'reg_...</td>\n",
       "      <td>-0.014801</td>\n",
       "      <td>-0.007201</td>\n",
       "      <td>-0.015193</td>\n",
       "      <td>-0.012398</td>\n",
       "      <td>0.003679</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.020988</td>\n",
       "      <td>0.000831</td>\n",
       "      <td>0.002011</td>\n",
       "      <td>1.402015e-05</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.2</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0003, 'reg__eta0': 0.2, 'reg_...</td>\n",
       "      <td>-0.027585</td>\n",
       "      <td>-0.017613</td>\n",
       "      <td>-0.020164</td>\n",
       "      <td>-0.021787</td>\n",
       "      <td>0.004229</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.273046</td>\n",
       "      <td>0.019292</td>\n",
       "      <td>0.001984</td>\n",
       "      <td>2.139961e-05</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.3</td>\n",
       "      <td>l1</td>\n",
       "      <td>{'reg__alpha': 0.0003, 'reg__eta0': 0.3, 'reg_...</td>\n",
       "      <td>-0.084356</td>\n",
       "      <td>-0.077818</td>\n",
       "      <td>-0.081708</td>\n",
       "      <td>-0.081294</td>\n",
       "      <td>0.002685</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "0       0.025002      0.005386         0.001667    4.791264e-04   \n",
       "1       0.019331      0.003299         0.002001    3.893359e-07   \n",
       "2       0.263365      0.022306         0.001662    4.764767e-04   \n",
       "3       0.017315      0.000932         0.002001    1.381091e-06   \n",
       "4       0.020010      0.001407         0.001668    4.725549e-04   \n",
       "5       0.263691      0.026805         0.001975    1.721720e-05   \n",
       "6       0.019665      0.000945         0.002001    8.920806e-07   \n",
       "7       0.020988      0.000831         0.002011    1.402015e-05   \n",
       "8       0.273046      0.019292         0.001984    2.139961e-05   \n",
       "\n",
       "  param_reg__alpha param_reg__eta0 param_reg__penalty  \\\n",
       "0           0.0001             0.1                 l1   \n",
       "1           0.0001             0.2                 l1   \n",
       "2           0.0001             0.3                 l1   \n",
       "3           0.0002             0.1                 l1   \n",
       "4           0.0002             0.2                 l1   \n",
       "5           0.0002             0.3                 l1   \n",
       "6           0.0003             0.1                 l1   \n",
       "7           0.0003             0.2                 l1   \n",
       "8           0.0003             0.3                 l1   \n",
       "\n",
       "                                              params  split0_test_score  \\\n",
       "0  {'reg__alpha': 0.0001, 'reg__eta0': 0.1, 'reg_...          -0.020412   \n",
       "1  {'reg__alpha': 0.0001, 'reg__eta0': 0.2, 'reg_...          -0.035436   \n",
       "2  {'reg__alpha': 0.0001, 'reg__eta0': 0.3, 'reg_...          -0.089393   \n",
       "3  {'reg__alpha': 0.0002, 'reg__eta0': 0.1, 'reg_...          -0.017686   \n",
       "4  {'reg__alpha': 0.0002, 'reg__eta0': 0.2, 'reg_...          -0.031440   \n",
       "5  {'reg__alpha': 0.0002, 'reg__eta0': 0.3, 'reg_...          -0.090381   \n",
       "6  {'reg__alpha': 0.0003, 'reg__eta0': 0.1, 'reg_...          -0.014801   \n",
       "7  {'reg__alpha': 0.0003, 'reg__eta0': 0.2, 'reg_...          -0.027585   \n",
       "8  {'reg__alpha': 0.0003, 'reg__eta0': 0.3, 'reg_...          -0.084356   \n",
       "\n",
       "   split1_test_score  split2_test_score  mean_test_score  std_test_score  \\\n",
       "0          -0.011934          -0.019059        -0.017135        0.003719   \n",
       "1          -0.024942          -0.027250        -0.029209        0.004503   \n",
       "2          -0.083136          -0.093578        -0.088702        0.004291   \n",
       "3          -0.009569          -0.017125        -0.014793        0.003701   \n",
       "4          -0.021246          -0.023699        -0.025462        0.004344   \n",
       "5          -0.077473          -0.087812        -0.085222        0.005579   \n",
       "6          -0.007201          -0.015193        -0.012398        0.003679   \n",
       "7          -0.017613          -0.020164        -0.021787        0.004229   \n",
       "8          -0.077818          -0.081708        -0.081294        0.002685   \n",
       "\n",
       "   rank_test_score  \n",
       "0                3  \n",
       "1                6  \n",
       "2                9  \n",
       "3                2  \n",
       "4                5  \n",
       "5                8  \n",
       "6                1  \n",
       "7                4  \n",
       "8                7  "
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(grid.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "b67c5965",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('scaler', StandardScaler()),\n",
       "                ('reg',\n",
       "                 SGDRegressor(alpha=0.0003, eta0=0.1, penalty='l1',\n",
       "                              random_state=42))])"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "4cddc168",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.012398359309079116"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "480334e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.03367296520125561"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = grid.best_estimator_.predict(X_test)\n",
    "met.mean_squared_error(y_test, y_pred, squared=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67f10d37",
   "metadata": {},
   "source": [
    "Learning Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "4e88b1fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plotLearningCurveRegression(est, X_train, y_train, X_test, y_test, y_lower=0, y_upper=1):\n",
    "  x_values = []\n",
    "  y_values_train = []\n",
    "  y_values_test = []\n",
    "\n",
    "  for j in np.linspace(25, len(X_train), 20):\n",
    "    i = int(j)\n",
    "    x_values.append(i)\n",
    "\n",
    "    X_train_sample = X_train[:i]\n",
    "    y_train_sample = y_train[:i]\n",
    "\n",
    "    # compose the model with current train data\n",
    "    est.fit(X_train_sample, y_train_sample)\n",
    "\n",
    "    # calcualte train score\n",
    "    y_pred_train = est.predict(X_train_sample)\n",
    "    train_score =  met.mean_squared_error(y_train_sample, y_pred_train, squared=False)\n",
    "    y_values_train.append(train_score)\n",
    "\n",
    "    # calculate test score\n",
    "    y_pred_test = est.predict(X_test)\n",
    "    test_score = met.mean_squared_error(y_test, y_pred_test, squared=False)\n",
    "    y_values_test.append(test_score)\n",
    "  \n",
    "  plt.plot(x_values, y_values_train, label=\"train\")\n",
    "  plt.plot(x_values, y_values_test, label=\"test\")\n",
    "  plt.xlabel(\"Train Size\")\n",
    "  plt.ylabel(\"RMSE Score\")\n",
    "  plt.legend()\n",
    "  plt.grid(True)\n",
    "  plt.ylim(y_lower, y_upper)\n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "f0e9beda",
   "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": [
    "pipe = pip.Pipeline([\n",
    "            (\"scaler\", pre.StandardScaler()),\n",
    "            (\"regressor\", lin.SGDRegressor(random_state=42))\n",
    "])\n",
    "\n",
    "plotLearningCurveRegression(pipe, X_train, y_train.ravel(), X_test, y_test.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "77725acc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SSEKERL\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\_stochastic_gradient.py:1503: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "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": [
    "pipe = pip.Pipeline([\n",
    "            (\"poly\", pre.PolynomialFeatures(degree=2)),\n",
    "            (\"scaler\", pre.StandardScaler()),\n",
    "            (\"regressor\", lin.SGDRegressor(random_state=42))\n",
    "])\n",
    "\n",
    "plotLearningCurveRegression(pipe, X_train, y_train.ravel(), X_test, y_test.ravel(), y_lower=0, y_upper=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "c1290cdd",
   "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": [
    "pipe = pip.Pipeline([\n",
    "          (\"scaler\", pre.StandardScaler()),\n",
    "          (\"reg\", lin.SGDRegressor(random_state=42))\n",
    "])\n",
    "\n",
    "params = {\n",
    "    \"reg__penalty\": [\"l1\"],\n",
    "    \"reg__alpha\": [0.0001, 0.0002, 0.0003],\n",
    "    \"reg__eta0\": [0.1, 0.2, 0.3]\n",
    "}\n",
    "\n",
    "grid = mod.GridSearchCV(pipe, params, scoring=\"neg_root_mean_squared_error\", cv=3)\n",
    "grid.fit(X_train, y_train.ravel())\n",
    "\n",
    "plotLearningCurveRegression(pipe, X_train, y_train.ravel(), X_test, y_test.ravel(), y_lower=0, y_upper=1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}