Join_Tables.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_selection import VarianceThreshold\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "import seaborn as sns\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score as acc\n",
    "from mlxtend.feature_selection import SequentialFeatureSelector as sfs\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_inlet=pd.read_csv('new_data_inlet.csv')\n",
    "data_outlet=pd.read_csv('new_data_outlet.csv')\n",
    "effluent_data=pd.read_csv('CleanData_V2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'record_date', 'avg_outflow'], dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_outlet.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_inlet['record_date']= pd.to_datetime(data_inlet['record_date']).dt.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_outlet['record_date']= pd.to_datetime(data_outlet['record_date']).dt.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_data=pd.concat([data_outlet,data_inlet], axis=1, join='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_data2=pd.concat([joined_data,effluent_data], axis=1, join='inner')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Unnamed: 0</th>\n",
       "      <th>record_date</th>\n",
       "      <th>avg_outflow</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>record_date</th>\n",
       "      <th>avg_inflow</th>\n",
       "      <th>feeder1_kwh</th>\n",
       "      <th>feeder2_kwh</th>\n",
       "      <th>Ammonia_mg_L_1</th>\n",
       "      <th>BOD_mg_L_1</th>\n",
       "      <th>...</th>\n",
       "      <th>H</th>\n",
       "      <th>PP</th>\n",
       "      <th>VV</th>\n",
       "      <th>V</th>\n",
       "      <th>VM</th>\n",
       "      <th>VG</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>record_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2009-01-01</td>\n",
       "      <td>2.941282</td>\n",
       "      <td>0</td>\n",
       "      <td>2009-01-01</td>\n",
       "      <td>2.588918</td>\n",
       "      <td>105695</td>\n",
       "      <td>70161</td>\n",
       "      <td>27.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>1.52</td>\n",
       "      <td>10.0</td>\n",
       "      <td>26.9</td>\n",
       "      <td>53.5</td>\n",
       "      <td>79.5</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>01-01-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2009-02-01</td>\n",
       "      <td>2.935526</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-02-01</td>\n",
       "      <td>2.961178</td>\n",
       "      <td>111836</td>\n",
       "      <td>69788</td>\n",
       "      <td>25.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.4</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>02-01-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2009-03-01</td>\n",
       "      <td>2.928222</td>\n",
       "      <td>2</td>\n",
       "      <td>2009-03-01</td>\n",
       "      <td>3.225309</td>\n",
       "      <td>140088</td>\n",
       "      <td>61928</td>\n",
       "      <td>42.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10.0</td>\n",
       "      <td>31.9</td>\n",
       "      <td>61.1</td>\n",
       "      <td>77.8</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>05-01-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2009-04-01</td>\n",
       "      <td>2.927961</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-04-01</td>\n",
       "      <td>3.354091</td>\n",
       "      <td>140121</td>\n",
       "      <td>67426</td>\n",
       "      <td>36.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>38.9</td>\n",
       "      <td>53.5</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>06-01-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2009-05-01</td>\n",
       "      <td>2.917222</td>\n",
       "      <td>4</td>\n",
       "      <td>2009-05-01</td>\n",
       "      <td>3.794004</td>\n",
       "      <td>135260</td>\n",
       "      <td>67564</td>\n",
       "      <td>46.0</td>\n",
       "      <td>508.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.6</td>\n",
       "      <td>35.2</td>\n",
       "      <td>53.5</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>07-01-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1377</th>\n",
       "      <td>1377</td>\n",
       "      <td>2012-11-10</td>\n",
       "      <td>5.068004</td>\n",
       "      <td>1377</td>\n",
       "      <td>2012-09-10</td>\n",
       "      <td>4.716265</td>\n",
       "      <td>167475</td>\n",
       "      <td>138463</td>\n",
       "      <td>28.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.4</td>\n",
       "      <td>22.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>20-05-2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1378</th>\n",
       "      <td>1378</td>\n",
       "      <td>2012-12-10</td>\n",
       "      <td>5.882439</td>\n",
       "      <td>1378</td>\n",
       "      <td>2012-10-10</td>\n",
       "      <td>5.510004</td>\n",
       "      <td>160476</td>\n",
       "      <td>132970</td>\n",
       "      <td>40.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.5</td>\n",
       "      <td>25.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>24-05-2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1379</th>\n",
       "      <td>1379</td>\n",
       "      <td>2012-10-13</td>\n",
       "      <td>4.638265</td>\n",
       "      <td>1379</td>\n",
       "      <td>2012-11-10</td>\n",
       "      <td>4.810787</td>\n",
       "      <td>174179</td>\n",
       "      <td>133789</td>\n",
       "      <td>47.0</td>\n",
       "      <td>260.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18.1</td>\n",
       "      <td>25.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>25-05-2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1380</th>\n",
       "      <td>1380</td>\n",
       "      <td>2012-10-14</td>\n",
       "      <td>5.372526</td>\n",
       "      <td>1380</td>\n",
       "      <td>2012-12-10</td>\n",
       "      <td>4.929222</td>\n",
       "      <td>166213</td>\n",
       "      <td>150462</td>\n",
       "      <td>46.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>35.2</td>\n",
       "      <td>51.9</td>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>26</td>\n",
       "      <td>26-05-2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1381</th>\n",
       "      <td>1381</td>\n",
       "      <td>2012-10-15</td>\n",
       "      <td>4.072309</td>\n",
       "      <td>1381</td>\n",
       "      <td>2012-10-13</td>\n",
       "      <td>5.193874</td>\n",
       "      <td>173246</td>\n",
       "      <td>145022</td>\n",
       "      <td>31.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>44.6</td>\n",
       "      <td>66.5</td>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>27-05-2019</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1382 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  record_date  avg_outflow  Unnamed: 0  record_date  \\\n",
       "0              0   2009-01-01     2.941282           0   2009-01-01   \n",
       "1              1   2009-02-01     2.935526           1   2009-02-01   \n",
       "2              2   2009-03-01     2.928222           2   2009-03-01   \n",
       "3              3   2009-04-01     2.927961           3   2009-04-01   \n",
       "4              4   2009-05-01     2.917222           4   2009-05-01   \n",
       "...          ...          ...          ...         ...          ...   \n",
       "1377        1377   2012-11-10     5.068004        1377   2012-09-10   \n",
       "1378        1378   2012-12-10     5.882439        1378   2012-10-10   \n",
       "1379        1379   2012-10-13     4.638265        1379   2012-11-10   \n",
       "1380        1380   2012-10-14     5.372526        1380   2012-12-10   \n",
       "1381        1381   2012-10-15     4.072309        1381   2012-10-13   \n",
       "\n",
       "      avg_inflow  feeder1_kwh  feeder2_kwh  Ammonia_mg_L_1  BOD_mg_L_1  ...  \\\n",
       "0       2.588918       105695        70161            27.0       365.0  ...   \n",
       "1       2.961178       111836        69788            25.0       370.0  ...   \n",
       "2       3.225309       140088        61928            42.0       418.0  ...   \n",
       "3       3.354091       140121        67426            36.0       430.0  ...   \n",
       "4       3.794004       135260        67564            46.0       508.0  ...   \n",
       "...          ...          ...          ...             ...         ...  ...   \n",
       "1377    4.716265       167475       138463            28.0       310.0  ...   \n",
       "1378    5.510004       160476       132970            40.0       250.0  ...   \n",
       "1379    4.810787       174179       133789            47.0       260.0  ...   \n",
       "1380    4.929222       166213       150462            46.0       300.0  ...   \n",
       "1381    5.193874       173246       145022            31.0       270.0  ...   \n",
       "\n",
       "       H    PP    VV     V    VM    VG  year  month  day  record_date  \n",
       "0     56  1.52  10.0  26.9  53.5  79.5  2014      1    1   01-01-2014  \n",
       "1     63  0.00  10.0  14.4  27.8   0.0  2014      1    2   02-01-2014  \n",
       "2     47  0.25  10.0  31.9  61.1  77.8  2014      1    5   05-01-2014  \n",
       "3     49  0.00  10.0  27.0  38.9  53.5  2014      1    6   06-01-2014  \n",
       "4     65  0.00  10.0  20.6  35.2  53.5  2014      1    7   07-01-2014  \n",
       "...   ..   ...   ...   ...   ...   ...   ...    ...  ...          ...  \n",
       "1377  56  0.00  10.0  14.4  22.2   0.0  2019      6   20   20-05-2019  \n",
       "1378  71  0.00   0.0  13.5  25.9   0.0  2019      6   24   24-05-2019  \n",
       "1379  65  0.00  10.0  18.1  25.9   0.0  2019      6   25   25-05-2019  \n",
       "1380  65  0.00  10.0  21.9  35.2  51.9  2019      6   26   26-05-2019  \n",
       "1381  63  0.00  10.0  28.0  44.6  66.5  2019      6   27   27-05-2019  \n",
       "\n",
       "[1382 rows x 26 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_data2.to_csv('joined_tables.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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