APP_river_level_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "APP165 = pd.read_csv('APP0165.csv', delimiter = ',')\n",
    "river = pd.read_csv('river_level.csv', delimiter = ',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>level</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:10:00 PM</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:20:00 PM</td>\n",
       "      <td>0.7163</td>\n",
       "      <td>12.151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:30:00 PM</td>\n",
       "      <td>0.7237</td>\n",
       "      <td>12.134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:40:00 PM</td>\n",
       "      <td>0.7303</td>\n",
       "      <td>12.126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:50:00 PM</td>\n",
       "      <td>0.7365</td>\n",
       "      <td>12.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:00:00 PM</td>\n",
       "      <td>0.7422</td>\n",
       "      <td>12.041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:10:00 PM</td>\n",
       "      <td>0.7480</td>\n",
       "      <td>11.962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:20:00 PM</td>\n",
       "      <td>0.7537</td>\n",
       "      <td>11.974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:30:00 PM</td>\n",
       "      <td>0.7578</td>\n",
       "      <td>12.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:40:00 PM</td>\n",
       "      <td>0.7596</td>\n",
       "      <td>12.142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:50:00 PM</td>\n",
       "      <td>0.7589</td>\n",
       "      <td>12.158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:00:00 PM</td>\n",
       "      <td>0.7558</td>\n",
       "      <td>12.093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:10:00 PM</td>\n",
       "      <td>0.7529</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:20:00 PM</td>\n",
       "      <td>0.7467</td>\n",
       "      <td>12.160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:30:00 PM</td>\n",
       "      <td>0.7396</td>\n",
       "      <td>12.169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:40:00 PM</td>\n",
       "      <td>0.7321</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:50:00 PM</td>\n",
       "      <td>0.7220</td>\n",
       "      <td>12.124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:00:00 PM</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>12.053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:10:00 PM</td>\n",
       "      <td>0.7001</td>\n",
       "      <td>12.218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:20:00 PM</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>12.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:30:00 PM</td>\n",
       "      <td>0.6717</td>\n",
       "      <td>12.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:40:00 PM</td>\n",
       "      <td>0.6559</td>\n",
       "      <td>12.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:50:00 PM</td>\n",
       "      <td>0.6397</td>\n",
       "      <td>12.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:00:00 PM</td>\n",
       "      <td>0.6222</td>\n",
       "      <td>12.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:10:00 PM</td>\n",
       "      <td>0.6031</td>\n",
       "      <td>12.229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:20:00 PM</td>\n",
       "      <td>0.5836</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:30:00 PM</td>\n",
       "      <td>0.5643</td>\n",
       "      <td>12.140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:40:00 PM</td>\n",
       "      <td>0.5444</td>\n",
       "      <td>12.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:50:00 PM</td>\n",
       "      <td>0.5234</td>\n",
       "      <td>12.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>07:00:00 PM</td>\n",
       "      <td>0.5029</td>\n",
       "      <td>12.252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110980</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:00:00 AM</td>\n",
       "      <td>0.6587</td>\n",
       "      <td>12.306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110981</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:10:00 AM</td>\n",
       "      <td>0.6447</td>\n",
       "      <td>12.307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110982</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:20:00 AM</td>\n",
       "      <td>0.6301</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110983</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:30:00 AM</td>\n",
       "      <td>0.6135</td>\n",
       "      <td>12.477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110984</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:40:00 AM</td>\n",
       "      <td>0.5958</td>\n",
       "      <td>12.479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110985</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:50:00 AM</td>\n",
       "      <td>0.5786</td>\n",
       "      <td>12.508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110986</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:00:00 AM</td>\n",
       "      <td>0.5581</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110987</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:10:00 AM</td>\n",
       "      <td>0.5384</td>\n",
       "      <td>12.506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110988</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:20:00 AM</td>\n",
       "      <td>0.5194</td>\n",
       "      <td>12.502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110989</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:30:00 AM</td>\n",
       "      <td>0.4996</td>\n",
       "      <td>12.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110990</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:40:00 AM</td>\n",
       "      <td>0.4794</td>\n",
       "      <td>12.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110991</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:50:00 AM</td>\n",
       "      <td>0.4583</td>\n",
       "      <td>12.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110992</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:00:00 AM</td>\n",
       "      <td>0.4382</td>\n",
       "      <td>12.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110993</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:10:00 AM</td>\n",
       "      <td>0.4198</td>\n",
       "      <td>12.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110994</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:20:00 AM</td>\n",
       "      <td>0.4003</td>\n",
       "      <td>12.457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110995</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:30:00 AM</td>\n",
       "      <td>0.3827</td>\n",
       "      <td>12.460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110996</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:40:00 AM</td>\n",
       "      <td>0.3670</td>\n",
       "      <td>12.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110997</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:50:00 AM</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110998</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:00:00 AM</td>\n",
       "      <td>0.3467</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110999</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:10:00 AM</td>\n",
       "      <td>0.3384</td>\n",
       "      <td>12.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111000</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:20:00 AM</td>\n",
       "      <td>0.3367</td>\n",
       "      <td>12.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111001</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:30:00 AM</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>12.411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111002</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:40:00 AM</td>\n",
       "      <td>0.3402</td>\n",
       "      <td>12.422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111003</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:50:00 AM</td>\n",
       "      <td>0.3445</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111004</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:00:00 PM</td>\n",
       "      <td>0.3497</td>\n",
       "      <td>12.481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111005</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:10:00 PM</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111006</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:20:00 PM</td>\n",
       "      <td>0.3616</td>\n",
       "      <td>12.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111007</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:30:00 PM</td>\n",
       "      <td>0.3664</td>\n",
       "      <td>12.351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111008</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:40:00 PM</td>\n",
       "      <td>0.3729</td>\n",
       "      <td>12.318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111009</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:50:00 PM</td>\n",
       "      <td>0.3813</td>\n",
       "      <td>12.328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>111010 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              date         time   level    temp\n",
       "0       19/09/2016  02:10:00 PM  0.7100  12.185\n",
       "1       19/09/2016  02:20:00 PM  0.7163  12.151\n",
       "2       19/09/2016  02:30:00 PM  0.7237  12.134\n",
       "3       19/09/2016  02:40:00 PM  0.7303  12.126\n",
       "4       19/09/2016  02:50:00 PM  0.7365  12.107\n",
       "5       19/09/2016  03:00:00 PM  0.7422  12.041\n",
       "6       19/09/2016  03:10:00 PM  0.7480  11.962\n",
       "7       19/09/2016  03:20:00 PM  0.7537  11.974\n",
       "8       19/09/2016  03:30:00 PM  0.7578  12.012\n",
       "9       19/09/2016  03:40:00 PM  0.7596  12.142\n",
       "10      19/09/2016  03:50:00 PM  0.7589  12.158\n",
       "11      19/09/2016  04:00:00 PM  0.7558  12.093\n",
       "12      19/09/2016  04:10:00 PM  0.7529  12.062\n",
       "13      19/09/2016  04:20:00 PM  0.7467  12.160\n",
       "14      19/09/2016  04:30:00 PM  0.7396  12.169\n",
       "15      19/09/2016  04:40:00 PM  0.7321  12.062\n",
       "16      19/09/2016  04:50:00 PM  0.7220  12.124\n",
       "17      19/09/2016  05:00:00 PM  0.7119  12.053\n",
       "18      19/09/2016  05:10:00 PM  0.7001  12.218\n",
       "19      19/09/2016  05:20:00 PM  0.6869  12.043\n",
       "20      19/09/2016  05:30:00 PM  0.6717  12.138\n",
       "21      19/09/2016  05:40:00 PM  0.6559  12.096\n",
       "22      19/09/2016  05:50:00 PM  0.6397  12.254\n",
       "23      19/09/2016  06:00:00 PM  0.6222  12.090\n",
       "24      19/09/2016  06:10:00 PM  0.6031  12.229\n",
       "25      19/09/2016  06:20:00 PM  0.5836  12.185\n",
       "26      19/09/2016  06:30:00 PM  0.5643  12.140\n",
       "27      19/09/2016  06:40:00 PM  0.5444  12.100\n",
       "28      19/09/2016  06:50:00 PM  0.5234  12.270\n",
       "29      19/09/2016  07:00:00 PM  0.5029  12.252\n",
       "...            ...          ...     ...     ...\n",
       "110980  30/10/2018  08:00:00 AM  0.6587  12.306\n",
       "110981  30/10/2018  08:10:00 AM  0.6447  12.307\n",
       "110982  30/10/2018  08:20:00 AM  0.6301  12.464\n",
       "110983  30/10/2018  08:30:00 AM  0.6135  12.477\n",
       "110984  30/10/2018  08:40:00 AM  0.5958  12.479\n",
       "110985  30/10/2018  08:50:00 AM  0.5786  12.508\n",
       "110986  30/10/2018  09:00:00 AM  0.5581  12.523\n",
       "110987  30/10/2018  09:10:00 AM  0.5384  12.506\n",
       "110988  30/10/2018  09:20:00 AM  0.5194  12.502\n",
       "110989  30/10/2018  09:30:00 AM  0.4996  12.466\n",
       "110990  30/10/2018  09:40:00 AM  0.4794  12.487\n",
       "110991  30/10/2018  09:50:00 AM  0.4583  12.475\n",
       "110992  30/10/2018  10:00:00 AM  0.4382  12.458\n",
       "110993  30/10/2018  10:10:00 AM  0.4198  12.439\n",
       "110994  30/10/2018  10:20:00 AM  0.4003  12.457\n",
       "110995  30/10/2018  10:30:00 AM  0.3827  12.460\n",
       "110996  30/10/2018  10:40:00 AM  0.3670  12.480\n",
       "110997  30/10/2018  10:50:00 AM  0.3557  12.499\n",
       "110998  30/10/2018  11:00:00 AM  0.3467  12.523\n",
       "110999  30/10/2018  11:10:00 AM  0.3384  12.495\n",
       "111000  30/10/2018  11:20:00 AM  0.3367  12.483\n",
       "111001  30/10/2018  11:30:00 AM  0.3382  12.411\n",
       "111002  30/10/2018  11:40:00 AM  0.3402  12.422\n",
       "111003  30/10/2018  11:50:00 AM  0.3445  12.464\n",
       "111004  30/10/2018  12:00:00 PM  0.3497  12.481\n",
       "111005  30/10/2018  12:10:00 PM  0.3557  12.471\n",
       "111006  30/10/2018  12:20:00 PM  0.3616  12.387\n",
       "111007  30/10/2018  12:30:00 PM  0.3664  12.351\n",
       "111008  30/10/2018  12:40:00 PM  0.3729  12.318\n",
       "111009  30/10/2018  12:50:00 PM  0.3813  12.328\n",
       "\n",
       "[111010 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "APP165"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/01/2016 00:15:00</td>\n",
       "      <td>0.639</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/01/2016 00:30:00</td>\n",
       "      <td>0.591</td>\n",
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       "      <td>0.542</td>\n",
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       "      <td>1/01/2016 01:00:00</td>\n",
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       "      <th>5</th>\n",
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       "      <td>0.385</td>\n",
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       "      <td>1/01/2016 01:45:00</td>\n",
       "      <td>0.334</td>\n",
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       "      <th>7</th>\n",
       "      <td>1/01/2016 02:00:00</td>\n",
       "      <td>0.283</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/01/2016 02:15:00</td>\n",
       "      <td>0.234</td>\n",
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       "      <th>9</th>\n",
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       "      <th>10</th>\n",
       "      <td>1/01/2016 02:45:00</td>\n",
       "      <td>0.142</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1/01/2016 03:00:00</td>\n",
       "      <td>0.102</td>\n",
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       "      <th>12</th>\n",
       "      <td>1/01/2016 03:15:00</td>\n",
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       "      <td>0.027</td>\n",
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       "      <td>1/01/2016 04:00:00</td>\n",
       "      <td>-0.039</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1/01/2016 04:15:00</td>\n",
       "      <td>-0.068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1/01/2016 04:30:00</td>\n",
       "      <td>-0.094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1/01/2016 04:45:00</td>\n",
       "      <td>-0.116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1/01/2016 05:00:00</td>\n",
       "      <td>-0.135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1/01/2016 05:15:00</td>\n",
       "      <td>-0.153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1/01/2016 05:30:00</td>\n",
       "      <td>-0.169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1/01/2016 05:45:00</td>\n",
       "      <td>-0.184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1/01/2016 06:00:00</td>\n",
       "      <td>-0.197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1/01/2016 06:15:00</td>\n",
       "      <td>-0.208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1/01/2016 06:30:00</td>\n",
       "      <td>-0.206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1/01/2016 06:45:00</td>\n",
       "      <td>-0.184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1/01/2016 07:00:00</td>\n",
       "      <td>-0.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1/01/2016 07:15:00</td>\n",
       "      <td>-0.102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1/01/2016 07:30:00</td>\n",
       "      <td>-0.045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126627</th>\n",
       "      <td>12/08/2019 01:00:00</td>\n",
       "      <td>0.616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126628</th>\n",
       "      <td>12/08/2019 01:15:00</td>\n",
       "      <td>0.688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126629</th>\n",
       "      <td>12/08/2019 01:30:00</td>\n",
       "      <td>0.765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126630</th>\n",
       "      <td>12/08/2019 01:45:00</td>\n",
       "      <td>0.836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126631</th>\n",
       "      <td>12/08/2019 02:00:00</td>\n",
       "      <td>0.908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126632</th>\n",
       "      <td>12/08/2019 02:15:00</td>\n",
       "      <td>0.959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126633</th>\n",
       "      <td>12/08/2019 02:30:00</td>\n",
       "      <td>1.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126634</th>\n",
       "      <td>12/08/2019 02:45:00</td>\n",
       "      <td>1.047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126635</th>\n",
       "      <td>12/08/2019 03:00:00</td>\n",
       "      <td>1.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126636</th>\n",
       "      <td>12/08/2019 03:15:00</td>\n",
       "      <td>1.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126637</th>\n",
       "      <td>12/08/2019 03:30:00</td>\n",
       "      <td>1.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126638</th>\n",
       "      <td>12/08/2019 03:45:00</td>\n",
       "      <td>1.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126639</th>\n",
       "      <td>12/08/2019 04:00:00</td>\n",
       "      <td>0.944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126640</th>\n",
       "      <td>12/08/2019 04:15:00</td>\n",
       "      <td>0.888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>12/08/2019 04:30:00</td>\n",
       "      <td>0.821</td>\n",
       "    </tr>\n",
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       "      <th>126642</th>\n",
       "      <td>12/08/2019 04:45:00</td>\n",
       "      <td>0.771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126643</th>\n",
       "      <td>12/08/2019 05:00:00</td>\n",
       "      <td>0.717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126644</th>\n",
       "      <td>12/08/2019 05:15:00</td>\n",
       "      <td>0.655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126645</th>\n",
       "      <td>12/08/2019 05:30:00</td>\n",
       "      <td>0.607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126646</th>\n",
       "      <td>12/08/2019 05:45:00</td>\n",
       "      <td>0.546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126647</th>\n",
       "      <td>12/08/2019 06:00:00</td>\n",
       "      <td>0.496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126648</th>\n",
       "      <td>12/08/2019 06:15:00</td>\n",
       "      <td>0.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126649</th>\n",
       "      <td>12/08/2019 06:30:00</td>\n",
       "      <td>0.386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126650</th>\n",
       "      <td>12/08/2019 06:45:00</td>\n",
       "      <td>0.334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126651</th>\n",
       "      <td>12/08/2019 07:00:00</td>\n",
       "      <td>0.280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126652</th>\n",
       "      <td>12/08/2019 07:15:00</td>\n",
       "      <td>0.235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126653</th>\n",
       "      <td>12/08/2019 07:30:00</td>\n",
       "      <td>0.191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126654</th>\n",
       "      <td>12/08/2019 07:45:00</td>\n",
       "      <td>0.143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126655</th>\n",
       "      <td>12/08/2019 08:00:00</td>\n",
       "      <td>0.101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126656</th>\n",
       "      <td>12/08/2019 08:15:00</td>\n",
       "      <td>0.077</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126657 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  date_time  level\n",
       "0        1/01/2016 00:15:00  0.639\n",
       "1        1/01/2016 00:30:00  0.591\n",
       "2        1/01/2016 00:45:00  0.542\n",
       "3        1/01/2016 01:00:00  0.491\n",
       "4        1/01/2016 01:15:00  0.438\n",
       "5        1/01/2016 01:30:00  0.385\n",
       "6        1/01/2016 01:45:00  0.334\n",
       "7        1/01/2016 02:00:00  0.283\n",
       "8        1/01/2016 02:15:00  0.234\n",
       "9        1/01/2016 02:30:00  0.186\n",
       "10       1/01/2016 02:45:00  0.142\n",
       "11       1/01/2016 03:00:00  0.102\n",
       "12       1/01/2016 03:15:00  0.063\n",
       "13       1/01/2016 03:30:00  0.027\n",
       "14       1/01/2016 03:45:00 -0.007\n",
       "15       1/01/2016 04:00:00 -0.039\n",
       "16       1/01/2016 04:15:00 -0.068\n",
       "17       1/01/2016 04:30:00 -0.094\n",
       "18       1/01/2016 04:45:00 -0.116\n",
       "19       1/01/2016 05:00:00 -0.135\n",
       "20       1/01/2016 05:15:00 -0.153\n",
       "21       1/01/2016 05:30:00 -0.169\n",
       "22       1/01/2016 05:45:00 -0.184\n",
       "23       1/01/2016 06:00:00 -0.197\n",
       "24       1/01/2016 06:15:00 -0.208\n",
       "25       1/01/2016 06:30:00 -0.206\n",
       "26       1/01/2016 06:45:00 -0.184\n",
       "27       1/01/2016 07:00:00 -0.149\n",
       "28       1/01/2016 07:15:00 -0.102\n",
       "29       1/01/2016 07:30:00 -0.045\n",
       "...                     ...    ...\n",
       "126627  12/08/2019 01:00:00  0.616\n",
       "126628  12/08/2019 01:15:00  0.688\n",
       "126629  12/08/2019 01:30:00  0.765\n",
       "126630  12/08/2019 01:45:00  0.836\n",
       "126631  12/08/2019 02:00:00  0.908\n",
       "126632  12/08/2019 02:15:00  0.959\n",
       "126633  12/08/2019 02:30:00  1.011\n",
       "126634  12/08/2019 02:45:00  1.047\n",
       "126635  12/08/2019 03:00:00  1.062\n",
       "126636  12/08/2019 03:15:00  1.073\n",
       "126637  12/08/2019 03:30:00  1.049\n",
       "126638  12/08/2019 03:45:00  1.008\n",
       "126639  12/08/2019 04:00:00  0.944\n",
       "126640  12/08/2019 04:15:00  0.888\n",
       "126641  12/08/2019 04:30:00  0.821\n",
       "126642  12/08/2019 04:45:00  0.771\n",
       "126643  12/08/2019 05:00:00  0.717\n",
       "126644  12/08/2019 05:15:00  0.655\n",
       "126645  12/08/2019 05:30:00  0.607\n",
       "126646  12/08/2019 05:45:00  0.546\n",
       "126647  12/08/2019 06:00:00  0.496\n",
       "126648  12/08/2019 06:15:00  0.439\n",
       "126649  12/08/2019 06:30:00  0.386\n",
       "126650  12/08/2019 06:45:00  0.334\n",
       "126651  12/08/2019 07:00:00  0.280\n",
       "126652  12/08/2019 07:15:00  0.235\n",
       "126653  12/08/2019 07:30:00  0.191\n",
       "126654  12/08/2019 07:45:00  0.143\n",
       "126655  12/08/2019 08:00:00  0.101\n",
       "126656  12/08/2019 08:15:00  0.077\n",
       "\n",
       "[126657 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "river"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "cannot insert date_time, already exists",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-27-928034809f8a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Combine date and time columns\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mAPP165\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'date_time'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mAPP165\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'date'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m' '\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mAPP165\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'time'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36minsert\u001b[1;34m(self, loc, column, value, allow_duplicates)\u001b[0m\n\u001b[0;32m   2519\u001b[0m         \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sanitize_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbroadcast\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2520\u001b[0m         self._data.insert(loc, column, value,\n\u001b[1;32m-> 2521\u001b[1;33m                           allow_duplicates=allow_duplicates)\n\u001b[0m\u001b[0;32m   2522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2523\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0massign\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\internals.py\u001b[0m in \u001b[0;36minsert\u001b[1;34m(self, loc, item, value, allow_duplicates)\u001b[0m\n\u001b[0;32m   3808\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mallow_duplicates\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mitem\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3809\u001b[0m             \u001b[1;31m# Should this be a different kind of error??\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3810\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'cannot insert {}, already exists'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3811\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3812\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: cannot insert date_time, already exists"
     ]
    }
   ],
   "source": [
    "# Combine date and time columns\n",
    "APP165.insert(2, 'date_time', APP165['date'] + ' ' + APP165['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>date_time</th>\n",
       "      <th>level</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:10:00 PM</td>\n",
       "      <td>19/09/2016 02:10:00 PM</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:20:00 PM</td>\n",
       "      <td>19/09/2016 02:20:00 PM</td>\n",
       "      <td>0.7163</td>\n",
       "      <td>12.151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:30:00 PM</td>\n",
       "      <td>19/09/2016 02:30:00 PM</td>\n",
       "      <td>0.7237</td>\n",
       "      <td>12.134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:40:00 PM</td>\n",
       "      <td>19/09/2016 02:40:00 PM</td>\n",
       "      <td>0.7303</td>\n",
       "      <td>12.126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:50:00 PM</td>\n",
       "      <td>19/09/2016 02:50:00 PM</td>\n",
       "      <td>0.7365</td>\n",
       "      <td>12.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:00:00 PM</td>\n",
       "      <td>19/09/2016 03:00:00 PM</td>\n",
       "      <td>0.7422</td>\n",
       "      <td>12.041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:10:00 PM</td>\n",
       "      <td>19/09/2016 03:10:00 PM</td>\n",
       "      <td>0.7480</td>\n",
       "      <td>11.962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:20:00 PM</td>\n",
       "      <td>19/09/2016 03:20:00 PM</td>\n",
       "      <td>0.7537</td>\n",
       "      <td>11.974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:30:00 PM</td>\n",
       "      <td>19/09/2016 03:30:00 PM</td>\n",
       "      <td>0.7578</td>\n",
       "      <td>12.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:40:00 PM</td>\n",
       "      <td>19/09/2016 03:40:00 PM</td>\n",
       "      <td>0.7596</td>\n",
       "      <td>12.142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:50:00 PM</td>\n",
       "      <td>19/09/2016 03:50:00 PM</td>\n",
       "      <td>0.7589</td>\n",
       "      <td>12.158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:00:00 PM</td>\n",
       "      <td>19/09/2016 04:00:00 PM</td>\n",
       "      <td>0.7558</td>\n",
       "      <td>12.093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:10:00 PM</td>\n",
       "      <td>19/09/2016 04:10:00 PM</td>\n",
       "      <td>0.7529</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:20:00 PM</td>\n",
       "      <td>19/09/2016 04:20:00 PM</td>\n",
       "      <td>0.7467</td>\n",
       "      <td>12.160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:30:00 PM</td>\n",
       "      <td>19/09/2016 04:30:00 PM</td>\n",
       "      <td>0.7396</td>\n",
       "      <td>12.169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:40:00 PM</td>\n",
       "      <td>19/09/2016 04:40:00 PM</td>\n",
       "      <td>0.7321</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:50:00 PM</td>\n",
       "      <td>19/09/2016 04:50:00 PM</td>\n",
       "      <td>0.7220</td>\n",
       "      <td>12.124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:00:00 PM</td>\n",
       "      <td>19/09/2016 05:00:00 PM</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>12.053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:10:00 PM</td>\n",
       "      <td>19/09/2016 05:10:00 PM</td>\n",
       "      <td>0.7001</td>\n",
       "      <td>12.218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:20:00 PM</td>\n",
       "      <td>19/09/2016 05:20:00 PM</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>12.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:30:00 PM</td>\n",
       "      <td>19/09/2016 05:30:00 PM</td>\n",
       "      <td>0.6717</td>\n",
       "      <td>12.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:40:00 PM</td>\n",
       "      <td>19/09/2016 05:40:00 PM</td>\n",
       "      <td>0.6559</td>\n",
       "      <td>12.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:50:00 PM</td>\n",
       "      <td>19/09/2016 05:50:00 PM</td>\n",
       "      <td>0.6397</td>\n",
       "      <td>12.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:00:00 PM</td>\n",
       "      <td>19/09/2016 06:00:00 PM</td>\n",
       "      <td>0.6222</td>\n",
       "      <td>12.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:10:00 PM</td>\n",
       "      <td>19/09/2016 06:10:00 PM</td>\n",
       "      <td>0.6031</td>\n",
       "      <td>12.229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:20:00 PM</td>\n",
       "      <td>19/09/2016 06:20:00 PM</td>\n",
       "      <td>0.5836</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:30:00 PM</td>\n",
       "      <td>19/09/2016 06:30:00 PM</td>\n",
       "      <td>0.5643</td>\n",
       "      <td>12.140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:40:00 PM</td>\n",
       "      <td>19/09/2016 06:40:00 PM</td>\n",
       "      <td>0.5444</td>\n",
       "      <td>12.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:50:00 PM</td>\n",
       "      <td>19/09/2016 06:50:00 PM</td>\n",
       "      <td>0.5234</td>\n",
       "      <td>12.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>07:00:00 PM</td>\n",
       "      <td>19/09/2016 07:00:00 PM</td>\n",
       "      <td>0.5029</td>\n",
       "      <td>12.252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110980</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:00:00 AM</td>\n",
       "      <td>30/10/2018 08:00:00 AM</td>\n",
       "      <td>0.6587</td>\n",
       "      <td>12.306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110981</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:10:00 AM</td>\n",
       "      <td>30/10/2018 08:10:00 AM</td>\n",
       "      <td>0.6447</td>\n",
       "      <td>12.307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110982</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:20:00 AM</td>\n",
       "      <td>30/10/2018 08:20:00 AM</td>\n",
       "      <td>0.6301</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110983</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:30:00 AM</td>\n",
       "      <td>30/10/2018 08:30:00 AM</td>\n",
       "      <td>0.6135</td>\n",
       "      <td>12.477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110984</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:40:00 AM</td>\n",
       "      <td>30/10/2018 08:40:00 AM</td>\n",
       "      <td>0.5958</td>\n",
       "      <td>12.479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110985</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:50:00 AM</td>\n",
       "      <td>30/10/2018 08:50:00 AM</td>\n",
       "      <td>0.5786</td>\n",
       "      <td>12.508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110986</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:00:00 AM</td>\n",
       "      <td>30/10/2018 09:00:00 AM</td>\n",
       "      <td>0.5581</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110987</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:10:00 AM</td>\n",
       "      <td>30/10/2018 09:10:00 AM</td>\n",
       "      <td>0.5384</td>\n",
       "      <td>12.506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110988</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:20:00 AM</td>\n",
       "      <td>30/10/2018 09:20:00 AM</td>\n",
       "      <td>0.5194</td>\n",
       "      <td>12.502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110989</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:30:00 AM</td>\n",
       "      <td>30/10/2018 09:30:00 AM</td>\n",
       "      <td>0.4996</td>\n",
       "      <td>12.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110990</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:40:00 AM</td>\n",
       "      <td>30/10/2018 09:40:00 AM</td>\n",
       "      <td>0.4794</td>\n",
       "      <td>12.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110991</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:50:00 AM</td>\n",
       "      <td>30/10/2018 09:50:00 AM</td>\n",
       "      <td>0.4583</td>\n",
       "      <td>12.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110992</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:00:00 AM</td>\n",
       "      <td>30/10/2018 10:00:00 AM</td>\n",
       "      <td>0.4382</td>\n",
       "      <td>12.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110993</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:10:00 AM</td>\n",
       "      <td>30/10/2018 10:10:00 AM</td>\n",
       "      <td>0.4198</td>\n",
       "      <td>12.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110994</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:20:00 AM</td>\n",
       "      <td>30/10/2018 10:20:00 AM</td>\n",
       "      <td>0.4003</td>\n",
       "      <td>12.457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110995</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:30:00 AM</td>\n",
       "      <td>30/10/2018 10:30:00 AM</td>\n",
       "      <td>0.3827</td>\n",
       "      <td>12.460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110996</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:40:00 AM</td>\n",
       "      <td>30/10/2018 10:40:00 AM</td>\n",
       "      <td>0.3670</td>\n",
       "      <td>12.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110997</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:50:00 AM</td>\n",
       "      <td>30/10/2018 10:50:00 AM</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110998</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:00:00 AM</td>\n",
       "      <td>30/10/2018 11:00:00 AM</td>\n",
       "      <td>0.3467</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110999</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:10:00 AM</td>\n",
       "      <td>30/10/2018 11:10:00 AM</td>\n",
       "      <td>0.3384</td>\n",
       "      <td>12.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111000</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:20:00 AM</td>\n",
       "      <td>30/10/2018 11:20:00 AM</td>\n",
       "      <td>0.3367</td>\n",
       "      <td>12.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111001</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:30:00 AM</td>\n",
       "      <td>30/10/2018 11:30:00 AM</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>12.411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111002</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:40:00 AM</td>\n",
       "      <td>30/10/2018 11:40:00 AM</td>\n",
       "      <td>0.3402</td>\n",
       "      <td>12.422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111003</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:50:00 AM</td>\n",
       "      <td>30/10/2018 11:50:00 AM</td>\n",
       "      <td>0.3445</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111004</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:00:00 PM</td>\n",
       "      <td>30/10/2018 12:00:00 PM</td>\n",
       "      <td>0.3497</td>\n",
       "      <td>12.481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111005</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:10:00 PM</td>\n",
       "      <td>30/10/2018 12:10:00 PM</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111006</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:20:00 PM</td>\n",
       "      <td>30/10/2018 12:20:00 PM</td>\n",
       "      <td>0.3616</td>\n",
       "      <td>12.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111007</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:30:00 PM</td>\n",
       "      <td>30/10/2018 12:30:00 PM</td>\n",
       "      <td>0.3664</td>\n",
       "      <td>12.351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111008</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:40:00 PM</td>\n",
       "      <td>30/10/2018 12:40:00 PM</td>\n",
       "      <td>0.3729</td>\n",
       "      <td>12.318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111009</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:50:00 PM</td>\n",
       "      <td>30/10/2018 12:50:00 PM</td>\n",
       "      <td>0.3813</td>\n",
       "      <td>12.328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>111010 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              date         time               date_time   level    temp\n",
       "0       19/09/2016  02:10:00 PM  19/09/2016 02:10:00 PM  0.7100  12.185\n",
       "1       19/09/2016  02:20:00 PM  19/09/2016 02:20:00 PM  0.7163  12.151\n",
       "2       19/09/2016  02:30:00 PM  19/09/2016 02:30:00 PM  0.7237  12.134\n",
       "3       19/09/2016  02:40:00 PM  19/09/2016 02:40:00 PM  0.7303  12.126\n",
       "4       19/09/2016  02:50:00 PM  19/09/2016 02:50:00 PM  0.7365  12.107\n",
       "5       19/09/2016  03:00:00 PM  19/09/2016 03:00:00 PM  0.7422  12.041\n",
       "6       19/09/2016  03:10:00 PM  19/09/2016 03:10:00 PM  0.7480  11.962\n",
       "7       19/09/2016  03:20:00 PM  19/09/2016 03:20:00 PM  0.7537  11.974\n",
       "8       19/09/2016  03:30:00 PM  19/09/2016 03:30:00 PM  0.7578  12.012\n",
       "9       19/09/2016  03:40:00 PM  19/09/2016 03:40:00 PM  0.7596  12.142\n",
       "10      19/09/2016  03:50:00 PM  19/09/2016 03:50:00 PM  0.7589  12.158\n",
       "11      19/09/2016  04:00:00 PM  19/09/2016 04:00:00 PM  0.7558  12.093\n",
       "12      19/09/2016  04:10:00 PM  19/09/2016 04:10:00 PM  0.7529  12.062\n",
       "13      19/09/2016  04:20:00 PM  19/09/2016 04:20:00 PM  0.7467  12.160\n",
       "14      19/09/2016  04:30:00 PM  19/09/2016 04:30:00 PM  0.7396  12.169\n",
       "15      19/09/2016  04:40:00 PM  19/09/2016 04:40:00 PM  0.7321  12.062\n",
       "16      19/09/2016  04:50:00 PM  19/09/2016 04:50:00 PM  0.7220  12.124\n",
       "17      19/09/2016  05:00:00 PM  19/09/2016 05:00:00 PM  0.7119  12.053\n",
       "18      19/09/2016  05:10:00 PM  19/09/2016 05:10:00 PM  0.7001  12.218\n",
       "19      19/09/2016  05:20:00 PM  19/09/2016 05:20:00 PM  0.6869  12.043\n",
       "20      19/09/2016  05:30:00 PM  19/09/2016 05:30:00 PM  0.6717  12.138\n",
       "21      19/09/2016  05:40:00 PM  19/09/2016 05:40:00 PM  0.6559  12.096\n",
       "22      19/09/2016  05:50:00 PM  19/09/2016 05:50:00 PM  0.6397  12.254\n",
       "23      19/09/2016  06:00:00 PM  19/09/2016 06:00:00 PM  0.6222  12.090\n",
       "24      19/09/2016  06:10:00 PM  19/09/2016 06:10:00 PM  0.6031  12.229\n",
       "25      19/09/2016  06:20:00 PM  19/09/2016 06:20:00 PM  0.5836  12.185\n",
       "26      19/09/2016  06:30:00 PM  19/09/2016 06:30:00 PM  0.5643  12.140\n",
       "27      19/09/2016  06:40:00 PM  19/09/2016 06:40:00 PM  0.5444  12.100\n",
       "28      19/09/2016  06:50:00 PM  19/09/2016 06:50:00 PM  0.5234  12.270\n",
       "29      19/09/2016  07:00:00 PM  19/09/2016 07:00:00 PM  0.5029  12.252\n",
       "...            ...          ...                     ...     ...     ...\n",
       "110980  30/10/2018  08:00:00 AM  30/10/2018 08:00:00 AM  0.6587  12.306\n",
       "110981  30/10/2018  08:10:00 AM  30/10/2018 08:10:00 AM  0.6447  12.307\n",
       "110982  30/10/2018  08:20:00 AM  30/10/2018 08:20:00 AM  0.6301  12.464\n",
       "110983  30/10/2018  08:30:00 AM  30/10/2018 08:30:00 AM  0.6135  12.477\n",
       "110984  30/10/2018  08:40:00 AM  30/10/2018 08:40:00 AM  0.5958  12.479\n",
       "110985  30/10/2018  08:50:00 AM  30/10/2018 08:50:00 AM  0.5786  12.508\n",
       "110986  30/10/2018  09:00:00 AM  30/10/2018 09:00:00 AM  0.5581  12.523\n",
       "110987  30/10/2018  09:10:00 AM  30/10/2018 09:10:00 AM  0.5384  12.506\n",
       "110988  30/10/2018  09:20:00 AM  30/10/2018 09:20:00 AM  0.5194  12.502\n",
       "110989  30/10/2018  09:30:00 AM  30/10/2018 09:30:00 AM  0.4996  12.466\n",
       "110990  30/10/2018  09:40:00 AM  30/10/2018 09:40:00 AM  0.4794  12.487\n",
       "110991  30/10/2018  09:50:00 AM  30/10/2018 09:50:00 AM  0.4583  12.475\n",
       "110992  30/10/2018  10:00:00 AM  30/10/2018 10:00:00 AM  0.4382  12.458\n",
       "110993  30/10/2018  10:10:00 AM  30/10/2018 10:10:00 AM  0.4198  12.439\n",
       "110994  30/10/2018  10:20:00 AM  30/10/2018 10:20:00 AM  0.4003  12.457\n",
       "110995  30/10/2018  10:30:00 AM  30/10/2018 10:30:00 AM  0.3827  12.460\n",
       "110996  30/10/2018  10:40:00 AM  30/10/2018 10:40:00 AM  0.3670  12.480\n",
       "110997  30/10/2018  10:50:00 AM  30/10/2018 10:50:00 AM  0.3557  12.499\n",
       "110998  30/10/2018  11:00:00 AM  30/10/2018 11:00:00 AM  0.3467  12.523\n",
       "110999  30/10/2018  11:10:00 AM  30/10/2018 11:10:00 AM  0.3384  12.495\n",
       "111000  30/10/2018  11:20:00 AM  30/10/2018 11:20:00 AM  0.3367  12.483\n",
       "111001  30/10/2018  11:30:00 AM  30/10/2018 11:30:00 AM  0.3382  12.411\n",
       "111002  30/10/2018  11:40:00 AM  30/10/2018 11:40:00 AM  0.3402  12.422\n",
       "111003  30/10/2018  11:50:00 AM  30/10/2018 11:50:00 AM  0.3445  12.464\n",
       "111004  30/10/2018  12:00:00 PM  30/10/2018 12:00:00 PM  0.3497  12.481\n",
       "111005  30/10/2018  12:10:00 PM  30/10/2018 12:10:00 PM  0.3557  12.471\n",
       "111006  30/10/2018  12:20:00 PM  30/10/2018 12:20:00 PM  0.3616  12.387\n",
       "111007  30/10/2018  12:30:00 PM  30/10/2018 12:30:00 PM  0.3664  12.351\n",
       "111008  30/10/2018  12:40:00 PM  30/10/2018 12:40:00 PM  0.3729  12.318\n",
       "111009  30/10/2018  12:50:00 PM  30/10/2018 12:50:00 PM  0.3813  12.328\n",
       "\n",
       "[111010 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "APP165"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Make Python recognize date_time column as datetime object\n",
    "APP165['date_time']=pd.to_datetime(APP165['date_time'], format = '%d/%m/%Y %I:%M:%S %p')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>date_time</th>\n",
       "      <th>level</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:10:00 PM</td>\n",
       "      <td>2016-09-19 02:10:00</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:20:00 PM</td>\n",
       "      <td>2016-09-19 02:20:00</td>\n",
       "      <td>0.7163</td>\n",
       "      <td>12.151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:30:00 PM</td>\n",
       "      <td>2016-09-19 02:30:00</td>\n",
       "      <td>0.7237</td>\n",
       "      <td>12.134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:40:00 PM</td>\n",
       "      <td>2016-09-19 02:40:00</td>\n",
       "      <td>0.7303</td>\n",
       "      <td>12.126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>02:50:00 PM</td>\n",
       "      <td>2016-09-19 02:50:00</td>\n",
       "      <td>0.7365</td>\n",
       "      <td>12.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:00:00 PM</td>\n",
       "      <td>2016-09-19 03:00:00</td>\n",
       "      <td>0.7422</td>\n",
       "      <td>12.041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:10:00 PM</td>\n",
       "      <td>2016-09-19 03:10:00</td>\n",
       "      <td>0.7480</td>\n",
       "      <td>11.962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:20:00 PM</td>\n",
       "      <td>2016-09-19 03:20:00</td>\n",
       "      <td>0.7537</td>\n",
       "      <td>11.974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:30:00 PM</td>\n",
       "      <td>2016-09-19 03:30:00</td>\n",
       "      <td>0.7578</td>\n",
       "      <td>12.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:40:00 PM</td>\n",
       "      <td>2016-09-19 03:40:00</td>\n",
       "      <td>0.7596</td>\n",
       "      <td>12.142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>03:50:00 PM</td>\n",
       "      <td>2016-09-19 03:50:00</td>\n",
       "      <td>0.7589</td>\n",
       "      <td>12.158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:00:00 PM</td>\n",
       "      <td>2016-09-19 04:00:00</td>\n",
       "      <td>0.7558</td>\n",
       "      <td>12.093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:10:00 PM</td>\n",
       "      <td>2016-09-19 04:10:00</td>\n",
       "      <td>0.7529</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:20:00 PM</td>\n",
       "      <td>2016-09-19 04:20:00</td>\n",
       "      <td>0.7467</td>\n",
       "      <td>12.160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:30:00 PM</td>\n",
       "      <td>2016-09-19 04:30:00</td>\n",
       "      <td>0.7396</td>\n",
       "      <td>12.169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:40:00 PM</td>\n",
       "      <td>2016-09-19 04:40:00</td>\n",
       "      <td>0.7321</td>\n",
       "      <td>12.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>04:50:00 PM</td>\n",
       "      <td>2016-09-19 04:50:00</td>\n",
       "      <td>0.7220</td>\n",
       "      <td>12.124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:00:00 PM</td>\n",
       "      <td>2016-09-19 05:00:00</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>12.053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:10:00 PM</td>\n",
       "      <td>2016-09-19 05:10:00</td>\n",
       "      <td>0.7001</td>\n",
       "      <td>12.218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:20:00 PM</td>\n",
       "      <td>2016-09-19 05:20:00</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>12.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:30:00 PM</td>\n",
       "      <td>2016-09-19 05:30:00</td>\n",
       "      <td>0.6717</td>\n",
       "      <td>12.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:40:00 PM</td>\n",
       "      <td>2016-09-19 05:40:00</td>\n",
       "      <td>0.6559</td>\n",
       "      <td>12.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>05:50:00 PM</td>\n",
       "      <td>2016-09-19 05:50:00</td>\n",
       "      <td>0.6397</td>\n",
       "      <td>12.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:00:00 PM</td>\n",
       "      <td>2016-09-19 06:00:00</td>\n",
       "      <td>0.6222</td>\n",
       "      <td>12.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:10:00 PM</td>\n",
       "      <td>2016-09-19 06:10:00</td>\n",
       "      <td>0.6031</td>\n",
       "      <td>12.229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:20:00 PM</td>\n",
       "      <td>2016-09-19 06:20:00</td>\n",
       "      <td>0.5836</td>\n",
       "      <td>12.185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:30:00 PM</td>\n",
       "      <td>2016-09-19 06:30:00</td>\n",
       "      <td>0.5643</td>\n",
       "      <td>12.140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:40:00 PM</td>\n",
       "      <td>2016-09-19 06:40:00</td>\n",
       "      <td>0.5444</td>\n",
       "      <td>12.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>06:50:00 PM</td>\n",
       "      <td>2016-09-19 06:50:00</td>\n",
       "      <td>0.5234</td>\n",
       "      <td>12.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>19/09/2016</td>\n",
       "      <td>07:00:00 PM</td>\n",
       "      <td>2016-09-19 07:00:00</td>\n",
       "      <td>0.5029</td>\n",
       "      <td>12.252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110980</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:00:00 AM</td>\n",
       "      <td>2018-10-30 08:00:00</td>\n",
       "      <td>0.6587</td>\n",
       "      <td>12.306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110981</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:10:00 AM</td>\n",
       "      <td>2018-10-30 08:10:00</td>\n",
       "      <td>0.6447</td>\n",
       "      <td>12.307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110982</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:20:00 AM</td>\n",
       "      <td>2018-10-30 08:20:00</td>\n",
       "      <td>0.6301</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110983</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:30:00 AM</td>\n",
       "      <td>2018-10-30 08:30:00</td>\n",
       "      <td>0.6135</td>\n",
       "      <td>12.477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110984</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:40:00 AM</td>\n",
       "      <td>2018-10-30 08:40:00</td>\n",
       "      <td>0.5958</td>\n",
       "      <td>12.479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110985</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>08:50:00 AM</td>\n",
       "      <td>2018-10-30 08:50:00</td>\n",
       "      <td>0.5786</td>\n",
       "      <td>12.508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110986</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:00:00 AM</td>\n",
       "      <td>2018-10-30 09:00:00</td>\n",
       "      <td>0.5581</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110987</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:10:00 AM</td>\n",
       "      <td>2018-10-30 09:10:00</td>\n",
       "      <td>0.5384</td>\n",
       "      <td>12.506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110988</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:20:00 AM</td>\n",
       "      <td>2018-10-30 09:20:00</td>\n",
       "      <td>0.5194</td>\n",
       "      <td>12.502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110989</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:30:00 AM</td>\n",
       "      <td>2018-10-30 09:30:00</td>\n",
       "      <td>0.4996</td>\n",
       "      <td>12.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110990</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:40:00 AM</td>\n",
       "      <td>2018-10-30 09:40:00</td>\n",
       "      <td>0.4794</td>\n",
       "      <td>12.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110991</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>09:50:00 AM</td>\n",
       "      <td>2018-10-30 09:50:00</td>\n",
       "      <td>0.4583</td>\n",
       "      <td>12.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110992</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:00:00 AM</td>\n",
       "      <td>2018-10-30 10:00:00</td>\n",
       "      <td>0.4382</td>\n",
       "      <td>12.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110993</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:10:00 AM</td>\n",
       "      <td>2018-10-30 10:10:00</td>\n",
       "      <td>0.4198</td>\n",
       "      <td>12.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110994</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:20:00 AM</td>\n",
       "      <td>2018-10-30 10:20:00</td>\n",
       "      <td>0.4003</td>\n",
       "      <td>12.457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110995</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:30:00 AM</td>\n",
       "      <td>2018-10-30 10:30:00</td>\n",
       "      <td>0.3827</td>\n",
       "      <td>12.460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110996</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:40:00 AM</td>\n",
       "      <td>2018-10-30 10:40:00</td>\n",
       "      <td>0.3670</td>\n",
       "      <td>12.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110997</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>10:50:00 AM</td>\n",
       "      <td>2018-10-30 10:50:00</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110998</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:00:00 AM</td>\n",
       "      <td>2018-10-30 11:00:00</td>\n",
       "      <td>0.3467</td>\n",
       "      <td>12.523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110999</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:10:00 AM</td>\n",
       "      <td>2018-10-30 11:10:00</td>\n",
       "      <td>0.3384</td>\n",
       "      <td>12.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111000</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:20:00 AM</td>\n",
       "      <td>2018-10-30 11:20:00</td>\n",
       "      <td>0.3367</td>\n",
       "      <td>12.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111001</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:30:00 AM</td>\n",
       "      <td>2018-10-30 11:30:00</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>12.411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111002</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:40:00 AM</td>\n",
       "      <td>2018-10-30 11:40:00</td>\n",
       "      <td>0.3402</td>\n",
       "      <td>12.422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111003</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>11:50:00 AM</td>\n",
       "      <td>2018-10-30 11:50:00</td>\n",
       "      <td>0.3445</td>\n",
       "      <td>12.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111004</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:00:00 PM</td>\n",
       "      <td>2018-10-30 12:00:00</td>\n",
       "      <td>0.3497</td>\n",
       "      <td>12.481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111005</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:10:00 PM</td>\n",
       "      <td>2018-10-30 12:10:00</td>\n",
       "      <td>0.3557</td>\n",
       "      <td>12.471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111006</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:20:00 PM</td>\n",
       "      <td>2018-10-30 12:20:00</td>\n",
       "      <td>0.3616</td>\n",
       "      <td>12.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111007</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:30:00 PM</td>\n",
       "      <td>2018-10-30 12:30:00</td>\n",
       "      <td>0.3664</td>\n",
       "      <td>12.351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111008</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:40:00 PM</td>\n",
       "      <td>2018-10-30 12:40:00</td>\n",
       "      <td>0.3729</td>\n",
       "      <td>12.318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111009</th>\n",
       "      <td>30/10/2018</td>\n",
       "      <td>12:50:00 PM</td>\n",
       "      <td>2018-10-30 12:50:00</td>\n",
       "      <td>0.3813</td>\n",
       "      <td>12.328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>111010 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              date         time           date_time   level    temp\n",
       "0       19/09/2016  02:10:00 PM 2016-09-19 02:10:00  0.7100  12.185\n",
       "1       19/09/2016  02:20:00 PM 2016-09-19 02:20:00  0.7163  12.151\n",
       "2       19/09/2016  02:30:00 PM 2016-09-19 02:30:00  0.7237  12.134\n",
       "3       19/09/2016  02:40:00 PM 2016-09-19 02:40:00  0.7303  12.126\n",
       "4       19/09/2016  02:50:00 PM 2016-09-19 02:50:00  0.7365  12.107\n",
       "5       19/09/2016  03:00:00 PM 2016-09-19 03:00:00  0.7422  12.041\n",
       "6       19/09/2016  03:10:00 PM 2016-09-19 03:10:00  0.7480  11.962\n",
       "7       19/09/2016  03:20:00 PM 2016-09-19 03:20:00  0.7537  11.974\n",
       "8       19/09/2016  03:30:00 PM 2016-09-19 03:30:00  0.7578  12.012\n",
       "9       19/09/2016  03:40:00 PM 2016-09-19 03:40:00  0.7596  12.142\n",
       "10      19/09/2016  03:50:00 PM 2016-09-19 03:50:00  0.7589  12.158\n",
       "11      19/09/2016  04:00:00 PM 2016-09-19 04:00:00  0.7558  12.093\n",
       "12      19/09/2016  04:10:00 PM 2016-09-19 04:10:00  0.7529  12.062\n",
       "13      19/09/2016  04:20:00 PM 2016-09-19 04:20:00  0.7467  12.160\n",
       "14      19/09/2016  04:30:00 PM 2016-09-19 04:30:00  0.7396  12.169\n",
       "15      19/09/2016  04:40:00 PM 2016-09-19 04:40:00  0.7321  12.062\n",
       "16      19/09/2016  04:50:00 PM 2016-09-19 04:50:00  0.7220  12.124\n",
       "17      19/09/2016  05:00:00 PM 2016-09-19 05:00:00  0.7119  12.053\n",
       "18      19/09/2016  05:10:00 PM 2016-09-19 05:10:00  0.7001  12.218\n",
       "19      19/09/2016  05:20:00 PM 2016-09-19 05:20:00  0.6869  12.043\n",
       "20      19/09/2016  05:30:00 PM 2016-09-19 05:30:00  0.6717  12.138\n",
       "21      19/09/2016  05:40:00 PM 2016-09-19 05:40:00  0.6559  12.096\n",
       "22      19/09/2016  05:50:00 PM 2016-09-19 05:50:00  0.6397  12.254\n",
       "23      19/09/2016  06:00:00 PM 2016-09-19 06:00:00  0.6222  12.090\n",
       "24      19/09/2016  06:10:00 PM 2016-09-19 06:10:00  0.6031  12.229\n",
       "25      19/09/2016  06:20:00 PM 2016-09-19 06:20:00  0.5836  12.185\n",
       "26      19/09/2016  06:30:00 PM 2016-09-19 06:30:00  0.5643  12.140\n",
       "27      19/09/2016  06:40:00 PM 2016-09-19 06:40:00  0.5444  12.100\n",
       "28      19/09/2016  06:50:00 PM 2016-09-19 06:50:00  0.5234  12.270\n",
       "29      19/09/2016  07:00:00 PM 2016-09-19 07:00:00  0.5029  12.252\n",
       "...            ...          ...                 ...     ...     ...\n",
       "110980  30/10/2018  08:00:00 AM 2018-10-30 08:00:00  0.6587  12.306\n",
       "110981  30/10/2018  08:10:00 AM 2018-10-30 08:10:00  0.6447  12.307\n",
       "110982  30/10/2018  08:20:00 AM 2018-10-30 08:20:00  0.6301  12.464\n",
       "110983  30/10/2018  08:30:00 AM 2018-10-30 08:30:00  0.6135  12.477\n",
       "110984  30/10/2018  08:40:00 AM 2018-10-30 08:40:00  0.5958  12.479\n",
       "110985  30/10/2018  08:50:00 AM 2018-10-30 08:50:00  0.5786  12.508\n",
       "110986  30/10/2018  09:00:00 AM 2018-10-30 09:00:00  0.5581  12.523\n",
       "110987  30/10/2018  09:10:00 AM 2018-10-30 09:10:00  0.5384  12.506\n",
       "110988  30/10/2018  09:20:00 AM 2018-10-30 09:20:00  0.5194  12.502\n",
       "110989  30/10/2018  09:30:00 AM 2018-10-30 09:30:00  0.4996  12.466\n",
       "110990  30/10/2018  09:40:00 AM 2018-10-30 09:40:00  0.4794  12.487\n",
       "110991  30/10/2018  09:50:00 AM 2018-10-30 09:50:00  0.4583  12.475\n",
       "110992  30/10/2018  10:00:00 AM 2018-10-30 10:00:00  0.4382  12.458\n",
       "110993  30/10/2018  10:10:00 AM 2018-10-30 10:10:00  0.4198  12.439\n",
       "110994  30/10/2018  10:20:00 AM 2018-10-30 10:20:00  0.4003  12.457\n",
       "110995  30/10/2018  10:30:00 AM 2018-10-30 10:30:00  0.3827  12.460\n",
       "110996  30/10/2018  10:40:00 AM 2018-10-30 10:40:00  0.3670  12.480\n",
       "110997  30/10/2018  10:50:00 AM 2018-10-30 10:50:00  0.3557  12.499\n",
       "110998  30/10/2018  11:00:00 AM 2018-10-30 11:00:00  0.3467  12.523\n",
       "110999  30/10/2018  11:10:00 AM 2018-10-30 11:10:00  0.3384  12.495\n",
       "111000  30/10/2018  11:20:00 AM 2018-10-30 11:20:00  0.3367  12.483\n",
       "111001  30/10/2018  11:30:00 AM 2018-10-30 11:30:00  0.3382  12.411\n",
       "111002  30/10/2018  11:40:00 AM 2018-10-30 11:40:00  0.3402  12.422\n",
       "111003  30/10/2018  11:50:00 AM 2018-10-30 11:50:00  0.3445  12.464\n",
       "111004  30/10/2018  12:00:00 PM 2018-10-30 12:00:00  0.3497  12.481\n",
       "111005  30/10/2018  12:10:00 PM 2018-10-30 12:10:00  0.3557  12.471\n",
       "111006  30/10/2018  12:20:00 PM 2018-10-30 12:20:00  0.3616  12.387\n",
       "111007  30/10/2018  12:30:00 PM 2018-10-30 12:30:00  0.3664  12.351\n",
       "111008  30/10/2018  12:40:00 PM 2018-10-30 12:40:00  0.3729  12.318\n",
       "111009  30/10/2018  12:50:00 PM 2018-10-30 12:50:00  0.3813  12.328\n",
       "\n",
       "[111010 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "APP165"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>date_time</th>\n",
       "      <th>level</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3229</th>\n",
       "      <td>12/10/2016</td>\n",
       "      <td>12:20:00 AM</td>\n",
       "      <td>2016-10-12 12:20:00</td>\n",
       "      <td>0.6589</td>\n",
       "      <td>12.242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71987</th>\n",
       "      <td>1/02/2018</td>\n",
       "      <td>01:00:45 PM</td>\n",
       "      <td>2018-02-01 01:00:45</td>\n",
       "      <td>0.5442</td>\n",
       "      <td>13.520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16984</th>\n",
       "      <td>15/01/2017</td>\n",
       "      <td>12:50:00 PM</td>\n",
       "      <td>2017-01-15 12:50:00</td>\n",
       "      <td>0.5075</td>\n",
       "      <td>13.029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87600</th>\n",
       "      <td>20/05/2018</td>\n",
       "      <td>11:20:00 PM</td>\n",
       "      <td>2018-05-20 11:20:00</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>14.234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92011</th>\n",
       "      <td>20/06/2018</td>\n",
       "      <td>02:30:00 PM</td>\n",
       "      <td>2018-06-20 02:30:00</td>\n",
       "      <td>0.4712</td>\n",
       "      <td>13.646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date         time           date_time   level    temp\n",
       "3229   12/10/2016  12:20:00 AM 2016-10-12 12:20:00  0.6589  12.242\n",
       "71987   1/02/2018  01:00:45 PM 2018-02-01 01:00:45  0.5442  13.520\n",
       "16984  15/01/2017  12:50:00 PM 2017-01-15 12:50:00  0.5075  13.029\n",
       "87600  20/05/2018  11:20:00 PM 2018-05-20 11:20:00  0.2820  14.234\n",
       "92011  20/06/2018  02:30:00 PM 2018-06-20 02:30:00  0.4712  13.646"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "APP165.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2017-12-31 04:10:45')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# randomly check if date_time AM/PM is recognized correctly\n",
    "random = APP165.iloc[67398]['date_time']\n",
    "random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31/12/2017 04:10:45 AM\n"
     ]
    }
   ],
   "source": [
    "print(random.strftime(\"%d/%m/%Y %I:%M:%S %p\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Result: incorrect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Make Python recognize date_time column as datetime object\n",
    "\n",
    "APP165['date_time']=pd.to_datetime(APP165['date_time'], format = '%d/%m/%Y %I:%M:%S %p')"
   ]
  }
 ],
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