IndPenSim_Summary_data_notebook_V3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Jupyter-NoteBook IndPenSim Import and Plot\n",
    "\n",
    "## IndPenSim Data import "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download data and unzip contents to current folder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IndPenSim Data websites \n",
    "Addition details can be found at:<a href='http://www.industrialpenicillinsimulation.com/'> www.industrialpenicillinsimulation.com</a>\n",
    "Data is downloaded from : <a href='https://data.mendeley.com/datasets/pdnjz7zz5x/1'> Mendeley data Website</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Import necessary packages\n",
    "import os\n",
    "from urllib.request import urlretrieve \n",
    "import zipfile\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "import ipywidgets as widgets\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Patience this is downloading over 0.5 GB of data so might take some time depending on internet connection...\n"
     ]
    }
   ],
   "source": [
    "## Downloadinhg zip folder containing data from Mndely data website\n",
    "print('Patience this is downloading over 0.5 GB of data so might take some time depending on internet connection...')\n",
    "indpensim_data_link = 'https://data.mendeley.com//datasets/pdnjz7zz5x//1//files//ec0dfb55-7e3c-4124-8b0c-ca8ae7c50fe7//100_Batches_IndPenSim.zip'\n",
    "# download the url contents in binary format\n",
    "r = requests.get(indpensim_data_link)\n",
    " \n",
    "# open method to open a file on your system and write the contents\n",
    "with open(\"100_batches.zip\", \"wb\") as code:\n",
    "    code.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unzip IndPenSim Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Unzipping data from folders \n",
    "with zipfile.ZipFile(\"100_batches.zip\",\"r\") as zip_ref:\n",
    "    zip_ref.extractall()\n",
    "\n",
    "# Converting batch and Ramna data into Dataframe\n",
    "import pandas as pd\n",
    "data = pd.read_csv('Mendeley_data/100_Batches_IndPenSim_V3.csv') \n",
    "# Converting summary statisic data into Dataframe\n",
    "data_summary = pd.read_csv('Mendeley_data/100_Batches_IndPenSim_Statistics.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Summary"
   ]
  },
  {
   "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>Batch ref</th>\n",
       "      <th>Penicllin_harvested_during_batch(kg)</th>\n",
       "      <th>Penicllin_harvested_end_of_batch (kg)</th>\n",
       "      <th>Penicllin_yield_total (kg)</th>\n",
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       "      <td>2326000.0</td>\n",
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       "      <td>2675300.0</td>\n",
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       "      <td>1071000.0</td>\n",
       "      <td>1886700.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>1147600.0</td>\n",
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       "      <th>8</th>\n",
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       "      <td>4083100.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>878430.0</td>\n",
       "      <td>1103600.0</td>\n",
       "      <td>1982000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Batch ref  Penicllin_harvested_during_batch(kg)  \\\n",
       "0          1                             1066400.0   \n",
       "1          2                              985910.0   \n",
       "2          3                             1416100.0   \n",
       "3          4                              815700.0   \n",
       "4          5                             1128500.0   \n",
       "5          6                             1005700.0   \n",
       "6          7                             1147600.0   \n",
       "7          8                             1201200.0   \n",
       "8          9                             1757800.0   \n",
       "9         10                              878430.0   \n",
       "\n",
       "   Penicllin_harvested_end_of_batch (kg)  Penicllin_yield_total (kg)  \\\n",
       "0                              1720000.0                   2786400.0   \n",
       "1                              1340100.0                   2326000.0   \n",
       "2                              1259200.0                   2675300.0   \n",
       "3                              1071000.0                   1886700.0   \n",
       "4                              2434400.0                   3562900.0   \n",
       "5                              1383100.0                   2388700.0   \n",
       "6                              2307000.0                   3454600.0   \n",
       "7                              2676200.0                   3877400.0   \n",
       "8                              2325300.0                   4083100.0   \n",
       "9                              1103600.0                   1982000.0   \n",
       "\n",
       "   Fault ref(0-NoFault 1-Fault)  \n",
       "0                             0  \n",
       "1                             0  \n",
       "2                             0  \n",
       "3                             0  \n",
       "4                             0  \n",
       "5                             0  \n",
       "6                             0  \n",
       "7                             0  \n",
       "8                             0  \n",
       "9                             0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary of Summary data\n",
    "data_summary.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th>Time (h)</th>\n",
       "      <th>Aeration rate(Fg:L/h)</th>\n",
       "      <th>Agitator RPM(RPM:RPM)</th>\n",
       "      <th>Sugar feed rate(Fs:L/h)</th>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.2</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>1.63800</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>469490.0</td>\n",
       "      <td>476530.0</td>\n",
       "      <td>482900.0</td>\n",
       "      <td>488050.0</td>\n",
       "      <td>491330.0</td>\n",
       "      <td>492540.0</td>\n",
       "      <td>491990.0</td>\n",
       "      <td>489940.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.4</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>18.1260</td>\n",
       "      <td>3.24110</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>515860.0</td>\n",
       "      <td>522970.0</td>\n",
       "      <td>529340.0</td>\n",
       "      <td>534260.0</td>\n",
       "      <td>537480.0</td>\n",
       "      <td>538580.0</td>\n",
       "      <td>537930.0</td>\n",
       "      <td>535880.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2.6</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>28.0370</td>\n",
       "      <td>5.20940</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>471800.0</td>\n",
       "      <td>478630.0</td>\n",
       "      <td>484640.0</td>\n",
       "      <td>489260.0</td>\n",
       "      <td>491920.0</td>\n",
       "      <td>492710.0</td>\n",
       "      <td>491700.0</td>\n",
       "      <td>489820.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2.8</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>31.9080</td>\n",
       "      <td>7.45310</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>488170.0</td>\n",
       "      <td>495150.0</td>\n",
       "      <td>501390.0</td>\n",
       "      <td>506250.0</td>\n",
       "      <td>509220.0</td>\n",
       "      <td>510150.0</td>\n",
       "      <td>509470.0</td>\n",
       "      <td>508260.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.0</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>28.3970</td>\n",
       "      <td>9.85710</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>478310.0</td>\n",
       "      <td>485360.0</td>\n",
       "      <td>491650.0</td>\n",
       "      <td>496580.0</td>\n",
       "      <td>499650.0</td>\n",
       "      <td>500790.0</td>\n",
       "      <td>500070.0</td>\n",
       "      <td>498190.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3.2</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>19.5940</td>\n",
       "      <td>12.32700</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>494180.0</td>\n",
       "      <td>500950.0</td>\n",
       "      <td>507090.0</td>\n",
       "      <td>511850.0</td>\n",
       "      <td>514660.0</td>\n",
       "      <td>515630.0</td>\n",
       "      <td>514840.0</td>\n",
       "      <td>513130.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3.4</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.5880</td>\n",
       "      <td>14.66500</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>502350.0</td>\n",
       "      <td>509310.0</td>\n",
       "      <td>515660.0</td>\n",
       "      <td>520620.0</td>\n",
       "      <td>523600.0</td>\n",
       "      <td>524760.0</td>\n",
       "      <td>524280.0</td>\n",
       "      <td>522570.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3.6</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.2774</td>\n",
       "      <td>17.04900</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>515250.0</td>\n",
       "      <td>522090.0</td>\n",
       "      <td>528370.0</td>\n",
       "      <td>533390.0</td>\n",
       "      <td>536390.0</td>\n",
       "      <td>537200.0</td>\n",
       "      <td>536550.0</td>\n",
       "      <td>534500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3.8</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>9.0006</td>\n",
       "      <td>19.67100</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>488590.0</td>\n",
       "      <td>495600.0</td>\n",
       "      <td>501850.0</td>\n",
       "      <td>506710.0</td>\n",
       "      <td>509680.0</td>\n",
       "      <td>510630.0</td>\n",
       "      <td>509980.0</td>\n",
       "      <td>508440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4.0</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>17.2010</td>\n",
       "      <td>22.80300</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>500790.0</td>\n",
       "      <td>507650.0</td>\n",
       "      <td>513830.0</td>\n",
       "      <td>518650.0</td>\n",
       "      <td>521410.0</td>\n",
       "      <td>521970.0</td>\n",
       "      <td>520920.0</td>\n",
       "      <td>519370.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>4.2</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>26.0410</td>\n",
       "      <td>25.71200</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>489420.0</td>\n",
       "      <td>496440.0</td>\n",
       "      <td>502770.0</td>\n",
       "      <td>507690.0</td>\n",
       "      <td>510700.0</td>\n",
       "      <td>511510.0</td>\n",
       "      <td>510850.0</td>\n",
       "      <td>508810.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4.4</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>30.9790</td>\n",
       "      <td>28.29700</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>538790.0</td>\n",
       "      <td>545720.0</td>\n",
       "      <td>551970.0</td>\n",
       "      <td>556740.0</td>\n",
       "      <td>559710.0</td>\n",
       "      <td>560840.0</td>\n",
       "      <td>560460.0</td>\n",
       "      <td>559240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>4.6</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>29.3820</td>\n",
       "      <td>31.47000</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>484760.0</td>\n",
       "      <td>491500.0</td>\n",
       "      <td>497590.0</td>\n",
       "      <td>502170.0</td>\n",
       "      <td>505000.0</td>\n",
       "      <td>505880.0</td>\n",
       "      <td>505220.0</td>\n",
       "      <td>503680.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4.8</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>22.3890</td>\n",
       "      <td>34.48900</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>511660.0</td>\n",
       "      <td>518660.0</td>\n",
       "      <td>525120.0</td>\n",
       "      <td>530220.0</td>\n",
       "      <td>533500.0</td>\n",
       "      <td>534610.0</td>\n",
       "      <td>533660.0</td>\n",
       "      <td>532110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>5.0</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.0170</td>\n",
       "      <td>38.27200</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>488300.0</td>\n",
       "      <td>494910.0</td>\n",
       "      <td>500870.0</td>\n",
       "      <td>505540.0</td>\n",
       "      <td>508220.0</td>\n",
       "      <td>508940.0</td>\n",
       "      <td>507930.0</td>\n",
       "      <td>506050.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5.2</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>9.5520</td>\n",
       "      <td>42.59500</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>497370.0</td>\n",
       "      <td>504260.0</td>\n",
       "      <td>510530.0</td>\n",
       "      <td>515370.0</td>\n",
       "      <td>518300.0</td>\n",
       "      <td>519280.0</td>\n",
       "      <td>518360.0</td>\n",
       "      <td>516480.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5.4</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11.9440</td>\n",
       "      <td>46.90700</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>492400.0</td>\n",
       "      <td>499390.0</td>\n",
       "      <td>505650.0</td>\n",
       "      <td>510410.0</td>\n",
       "      <td>513240.0</td>\n",
       "      <td>514110.0</td>\n",
       "      <td>513300.0</td>\n",
       "      <td>511420.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5.6</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>19.5920</td>\n",
       "      <td>51.04600</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>496830.0</td>\n",
       "      <td>503790.0</td>\n",
       "      <td>510170.0</td>\n",
       "      <td>515290.0</td>\n",
       "      <td>518450.0</td>\n",
       "      <td>519450.0</td>\n",
       "      <td>518400.0</td>\n",
       "      <td>516350.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5.8</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>28.4160</td>\n",
       "      <td>55.68000</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>538600.0</td>\n",
       "      <td>545570.0</td>\n",
       "      <td>551830.0</td>\n",
       "      <td>556670.0</td>\n",
       "      <td>559670.0</td>\n",
       "      <td>560480.0</td>\n",
       "      <td>559500.0</td>\n",
       "      <td>557780.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>6.0</td>\n",
       "      <td>30</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>33.8550</td>\n",
       "      <td>58.83500</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>...</td>\n",
       "      <td>466270.0</td>\n",
       "      <td>473120.0</td>\n",
       "      <td>479180.0</td>\n",
       "      <td>483660.0</td>\n",
       "      <td>486320.0</td>\n",
       "      <td>487110.0</td>\n",
       "      <td>485930.0</td>\n",
       "      <td>483720.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>113905</th>\n",
       "      <td>224.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.2650</td>\n",
       "      <td>37.76700</td>\n",
       "      <td>0.80781</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>795170.0</td>\n",
       "      <td>802230.0</td>\n",
       "      <td>808660.0</td>\n",
       "      <td>813860.0</td>\n",
       "      <td>817190.0</td>\n",
       "      <td>818630.0</td>\n",
       "      <td>818360.0</td>\n",
       "      <td>816970.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113906</th>\n",
       "      <td>224.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.2743</td>\n",
       "      <td>11.33000</td>\n",
       "      <td>60.91900</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>834420.0</td>\n",
       "      <td>842000.0</td>\n",
       "      <td>848850.0</td>\n",
       "      <td>854280.0</td>\n",
       "      <td>857750.0</td>\n",
       "      <td>859150.0</td>\n",
       "      <td>858610.0</td>\n",
       "      <td>857390.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113907</th>\n",
       "      <td>224.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4.7721</td>\n",
       "      <td>38.68600</td>\n",
       "      <td>6.09190</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>797210.0</td>\n",
       "      <td>804460.0</td>\n",
       "      <td>811000.0</td>\n",
       "      <td>816090.0</td>\n",
       "      <td>819250.0</td>\n",
       "      <td>820470.0</td>\n",
       "      <td>820370.0</td>\n",
       "      <td>819300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113908</th>\n",
       "      <td>224.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.4984</td>\n",
       "      <td>11.60600</td>\n",
       "      <td>96.28600</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>803900.0</td>\n",
       "      <td>811150.0</td>\n",
       "      <td>817790.0</td>\n",
       "      <td>822960.0</td>\n",
       "      <td>826240.0</td>\n",
       "      <td>827490.0</td>\n",
       "      <td>826950.0</td>\n",
       "      <td>825220.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113909</th>\n",
       "      <td>225.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.5100</td>\n",
       "      <td>72.00000</td>\n",
       "      <td>9.62860</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>826520.0</td>\n",
       "      <td>833840.0</td>\n",
       "      <td>840520.0</td>\n",
       "      <td>845870.0</td>\n",
       "      <td>849510.0</td>\n",
       "      <td>851100.0</td>\n",
       "      <td>850700.0</td>\n",
       "      <td>849640.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113910</th>\n",
       "      <td>225.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.8910</td>\n",
       "      <td>45.81000</td>\n",
       "      <td>0.96286</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>828630.0</td>\n",
       "      <td>835910.0</td>\n",
       "      <td>842480.0</td>\n",
       "      <td>847680.0</td>\n",
       "      <td>850990.0</td>\n",
       "      <td>852120.0</td>\n",
       "      <td>851610.0</td>\n",
       "      <td>850050.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113911</th>\n",
       "      <td>225.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>17.8040</td>\n",
       "      <td>13.74300</td>\n",
       "      <td>66.10500</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>821110.0</td>\n",
       "      <td>828240.0</td>\n",
       "      <td>834760.0</td>\n",
       "      <td>839980.0</td>\n",
       "      <td>843410.0</td>\n",
       "      <td>844830.0</td>\n",
       "      <td>844690.0</td>\n",
       "      <td>843460.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113912</th>\n",
       "      <td>225.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>17.6270</td>\n",
       "      <td>45.92000</td>\n",
       "      <td>6.61050</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>809630.0</td>\n",
       "      <td>816970.0</td>\n",
       "      <td>823720.0</td>\n",
       "      <td>829110.0</td>\n",
       "      <td>832680.0</td>\n",
       "      <td>834040.0</td>\n",
       "      <td>833770.0</td>\n",
       "      <td>832370.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113913</th>\n",
       "      <td>225.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.2830</td>\n",
       "      <td>18.94400</td>\n",
       "      <td>0.66105</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>801050.0</td>\n",
       "      <td>808190.0</td>\n",
       "      <td>814730.0</td>\n",
       "      <td>819860.0</td>\n",
       "      <td>823090.0</td>\n",
       "      <td>824260.0</td>\n",
       "      <td>823680.0</td>\n",
       "      <td>822290.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113914</th>\n",
       "      <td>226.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>9.4585</td>\n",
       "      <td>5.68330</td>\n",
       "      <td>49.94000</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>790710.0</td>\n",
       "      <td>798040.0</td>\n",
       "      <td>804650.0</td>\n",
       "      <td>810010.0</td>\n",
       "      <td>813450.0</td>\n",
       "      <td>814780.0</td>\n",
       "      <td>814280.0</td>\n",
       "      <td>812710.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113915</th>\n",
       "      <td>226.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.5024</td>\n",
       "      <td>1.70500</td>\n",
       "      <td>0.00010</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>809710.0</td>\n",
       "      <td>816970.0</td>\n",
       "      <td>823630.0</td>\n",
       "      <td>828890.0</td>\n",
       "      <td>832450.0</td>\n",
       "      <td>834110.0</td>\n",
       "      <td>834040.0</td>\n",
       "      <td>833140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113916</th>\n",
       "      <td>226.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4.2791</td>\n",
       "      <td>0.51150</td>\n",
       "      <td>67.87900</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>823180.0</td>\n",
       "      <td>830370.0</td>\n",
       "      <td>836880.0</td>\n",
       "      <td>841990.0</td>\n",
       "      <td>845310.0</td>\n",
       "      <td>846540.0</td>\n",
       "      <td>846300.0</td>\n",
       "      <td>844570.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113917</th>\n",
       "      <td>226.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.2738</td>\n",
       "      <td>33.20000</td>\n",
       "      <td>6.78790</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>811510.0</td>\n",
       "      <td>818690.0</td>\n",
       "      <td>825130.0</td>\n",
       "      <td>830080.0</td>\n",
       "      <td>833100.0</td>\n",
       "      <td>834170.0</td>\n",
       "      <td>833400.0</td>\n",
       "      <td>831500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113918</th>\n",
       "      <td>226.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.3150</td>\n",
       "      <td>9.96000</td>\n",
       "      <td>106.42000</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>807400.0</td>\n",
       "      <td>814770.0</td>\n",
       "      <td>821560.0</td>\n",
       "      <td>827010.0</td>\n",
       "      <td>830520.0</td>\n",
       "      <td>832000.0</td>\n",
       "      <td>831660.0</td>\n",
       "      <td>830420.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113919</th>\n",
       "      <td>227.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.3400</td>\n",
       "      <td>77.07100</td>\n",
       "      <td>10.64200</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>822560.0</td>\n",
       "      <td>829580.0</td>\n",
       "      <td>835980.0</td>\n",
       "      <td>840930.0</td>\n",
       "      <td>844020.0</td>\n",
       "      <td>845220.0</td>\n",
       "      <td>845080.0</td>\n",
       "      <td>843840.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113920</th>\n",
       "      <td>227.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>16.2320</td>\n",
       "      <td>45.39500</td>\n",
       "      <td>1.06420</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>838120.0</td>\n",
       "      <td>845580.0</td>\n",
       "      <td>852450.0</td>\n",
       "      <td>857970.0</td>\n",
       "      <td>861580.0</td>\n",
       "      <td>863240.0</td>\n",
       "      <td>863170.0</td>\n",
       "      <td>861760.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113921</th>\n",
       "      <td>227.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>15.1180</td>\n",
       "      <td>13.61800</td>\n",
       "      <td>72.46900</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>788650.0</td>\n",
       "      <td>795890.0</td>\n",
       "      <td>802420.0</td>\n",
       "      <td>807510.0</td>\n",
       "      <td>810870.0</td>\n",
       "      <td>812370.0</td>\n",
       "      <td>811920.0</td>\n",
       "      <td>810690.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113922</th>\n",
       "      <td>227.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11.9930</td>\n",
       "      <td>48.95300</td>\n",
       "      <td>7.24690</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>794280.0</td>\n",
       "      <td>801240.0</td>\n",
       "      <td>807540.0</td>\n",
       "      <td>812550.0</td>\n",
       "      <td>815800.0</td>\n",
       "      <td>816900.0</td>\n",
       "      <td>816190.0</td>\n",
       "      <td>814610.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113923</th>\n",
       "      <td>227.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>8.3346</td>\n",
       "      <td>14.68600</td>\n",
       "      <td>119.94000</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>810380.0</td>\n",
       "      <td>817530.0</td>\n",
       "      <td>824110.0</td>\n",
       "      <td>829260.0</td>\n",
       "      <td>832660.0</td>\n",
       "      <td>833730.0</td>\n",
       "      <td>832950.0</td>\n",
       "      <td>831050.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113924</th>\n",
       "      <td>228.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.1901</td>\n",
       "      <td>93.39500</td>\n",
       "      <td>11.99400</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>810820.0</td>\n",
       "      <td>818080.0</td>\n",
       "      <td>824590.0</td>\n",
       "      <td>829640.0</td>\n",
       "      <td>832810.0</td>\n",
       "      <td>833960.0</td>\n",
       "      <td>833390.0</td>\n",
       "      <td>831980.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113925</th>\n",
       "      <td>228.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.2708</td>\n",
       "      <td>61.46100</td>\n",
       "      <td>1.19940</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>821430.0</td>\n",
       "      <td>828750.0</td>\n",
       "      <td>835440.0</td>\n",
       "      <td>840690.0</td>\n",
       "      <td>844100.0</td>\n",
       "      <td>845400.0</td>\n",
       "      <td>844990.0</td>\n",
       "      <td>843420.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113926</th>\n",
       "      <td>228.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>8.5039</td>\n",
       "      <td>18.43800</td>\n",
       "      <td>80.87500</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>798730.0</td>\n",
       "      <td>805960.0</td>\n",
       "      <td>812650.0</td>\n",
       "      <td>818010.0</td>\n",
       "      <td>821400.0</td>\n",
       "      <td>822440.0</td>\n",
       "      <td>821760.0</td>\n",
       "      <td>820350.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113927</th>\n",
       "      <td>228.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11.6800</td>\n",
       "      <td>61.79200</td>\n",
       "      <td>8.08750</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>798640.0</td>\n",
       "      <td>806010.0</td>\n",
       "      <td>812720.0</td>\n",
       "      <td>817950.0</td>\n",
       "      <td>821330.0</td>\n",
       "      <td>822770.0</td>\n",
       "      <td>822520.0</td>\n",
       "      <td>820780.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113928</th>\n",
       "      <td>228.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.2350</td>\n",
       "      <td>32.54100</td>\n",
       "      <td>0.80875</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>795140.0</td>\n",
       "      <td>802440.0</td>\n",
       "      <td>809150.0</td>\n",
       "      <td>814490.0</td>\n",
       "      <td>818050.0</td>\n",
       "      <td>819600.0</td>\n",
       "      <td>819460.0</td>\n",
       "      <td>818220.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113929</th>\n",
       "      <td>229.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.6420</td>\n",
       "      <td>9.76240</td>\n",
       "      <td>59.35900</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>813310.0</td>\n",
       "      <td>820650.0</td>\n",
       "      <td>827360.0</td>\n",
       "      <td>832760.0</td>\n",
       "      <td>836270.0</td>\n",
       "      <td>837740.0</td>\n",
       "      <td>837390.0</td>\n",
       "      <td>835650.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113930</th>\n",
       "      <td>229.2</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>12.9000</td>\n",
       "      <td>33.58600</td>\n",
       "      <td>5.93590</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>816050.0</td>\n",
       "      <td>823390.0</td>\n",
       "      <td>830160.0</td>\n",
       "      <td>835530.0</td>\n",
       "      <td>839140.0</td>\n",
       "      <td>840570.0</td>\n",
       "      <td>840160.0</td>\n",
       "      <td>838580.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113931</th>\n",
       "      <td>229.4</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.0470</td>\n",
       "      <td>10.07600</td>\n",
       "      <td>98.83400</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>773520.0</td>\n",
       "      <td>780840.0</td>\n",
       "      <td>787470.0</td>\n",
       "      <td>792750.0</td>\n",
       "      <td>796220.0</td>\n",
       "      <td>797610.0</td>\n",
       "      <td>797270.0</td>\n",
       "      <td>796020.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113932</th>\n",
       "      <td>229.6</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>7.3609</td>\n",
       "      <td>69.34500</td>\n",
       "      <td>9.88340</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>788240.0</td>\n",
       "      <td>795550.0</td>\n",
       "      <td>802190.0</td>\n",
       "      <td>807420.0</td>\n",
       "      <td>810590.0</td>\n",
       "      <td>811660.0</td>\n",
       "      <td>811210.0</td>\n",
       "      <td>809960.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113933</th>\n",
       "      <td>229.8</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.2794</td>\n",
       "      <td>38.61000</td>\n",
       "      <td>0.98834</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>781180.0</td>\n",
       "      <td>788420.0</td>\n",
       "      <td>794950.0</td>\n",
       "      <td>800140.0</td>\n",
       "      <td>803610.0</td>\n",
       "      <td>804900.0</td>\n",
       "      <td>804490.0</td>\n",
       "      <td>803410.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113934</th>\n",
       "      <td>230.0</td>\n",
       "      <td>65</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>7.3055</td>\n",
       "      <td>11.58300</td>\n",
       "      <td>67.53600</td>\n",
       "      <td>250</td>\n",
       "      <td>0.9</td>\n",
       "      <td>...</td>\n",
       "      <td>778800.0</td>\n",
       "      <td>785950.0</td>\n",
       "      <td>792440.0</td>\n",
       "      <td>797700.0</td>\n",
       "      <td>801130.0</td>\n",
       "      <td>802350.0</td>\n",
       "      <td>801770.0</td>\n",
       "      <td>799850.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>113935 rows × 2239 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Time (h)  Aeration rate(Fg:L/h)  Agitator RPM(RPM:RPM)  \\\n",
       "0            0.2                     30                    100   \n",
       "1            0.4                     30                    100   \n",
       "2            0.6                     30                    100   \n",
       "3            0.8                     30                    100   \n",
       "4            1.0                     30                    100   \n",
       "5            1.2                     30                    100   \n",
       "6            1.4                     30                    100   \n",
       "7            1.6                     30                    100   \n",
       "8            1.8                     30                    100   \n",
       "9            2.0                     30                    100   \n",
       "10           2.2                     30                    100   \n",
       "11           2.4                     30                    100   \n",
       "12           2.6                     30                    100   \n",
       "13           2.8                     30                    100   \n",
       "14           3.0                     30                    100   \n",
       "15           3.2                     30                    100   \n",
       "16           3.4                     30                    100   \n",
       "17           3.6                     30                    100   \n",
       "18           3.8                     30                    100   \n",
       "19           4.0                     30                    100   \n",
       "20           4.2                     30                    100   \n",
       "21           4.4                     30                    100   \n",
       "22           4.6                     30                    100   \n",
       "23           4.8                     30                    100   \n",
       "24           5.0                     30                    100   \n",
       "25           5.2                     30                    100   \n",
       "26           5.4                     30                    100   \n",
       "27           5.6                     30                    100   \n",
       "28           5.8                     30                    100   \n",
       "29           6.0                     30                    100   \n",
       "...          ...                    ...                    ...   \n",
       "113905     224.2                     65                    100   \n",
       "113906     224.4                     65                    100   \n",
       "113907     224.6                     65                    100   \n",
       "113908     224.8                     65                    100   \n",
       "113909     225.0                     65                    100   \n",
       "113910     225.2                     65                    100   \n",
       "113911     225.4                     65                    100   \n",
       "113912     225.6                     65                    100   \n",
       "113913     225.8                     65                    100   \n",
       "113914     226.0                     65                    100   \n",
       "113915     226.2                     65                    100   \n",
       "113916     226.4                     65                    100   \n",
       "113917     226.6                     65                    100   \n",
       "113918     226.8                     65                    100   \n",
       "113919     227.0                     65                    100   \n",
       "113920     227.2                     65                    100   \n",
       "113921     227.4                     65                    100   \n",
       "113922     227.6                     65                    100   \n",
       "113923     227.8                     65                    100   \n",
       "113924     228.0                     65                    100   \n",
       "113925     228.2                     65                    100   \n",
       "113926     228.4                     65                    100   \n",
       "113927     228.6                     65                    100   \n",
       "113928     228.8                     65                    100   \n",
       "113929     229.0                     65                    100   \n",
       "113930     229.2                     65                    100   \n",
       "113931     229.4                     65                    100   \n",
       "113932     229.6                     65                    100   \n",
       "113933     229.8                     65                    100   \n",
       "113934     230.0                     65                    100   \n",
       "\n",
       "        Sugar feed rate(Fs:L/h)  Acid flow rate(Fa:L/h)  \\\n",
       "0                             8                  0.0000   \n",
       "1                             8                  0.0000   \n",
       "2                             8                  0.0000   \n",
       "3                             8                  0.0000   \n",
       "4                             8                  0.5181   \n",
       "5                             8                  1.0387   \n",
       "6                             8                  1.5604   \n",
       "7                             8                  2.0823   \n",
       "8                             8                  0.0000   \n",
       "9                             8                  0.0000   \n",
       "10                            8                  0.0000   \n",
       "11                            8                  0.0000   \n",
       "12                            8                  0.0000   \n",
       "13                            8                  0.0000   \n",
       "14                            8                  0.0000   \n",
       "15                           15                  0.0000   \n",
       "16                           15                  0.0000   \n",
       "17                           15                  0.0000   \n",
       "18                           15                  0.0000   \n",
       "19                           15                  0.0000   \n",
       "20                           15                  0.0000   \n",
       "21                           15                  0.0000   \n",
       "22                           15                  0.0000   \n",
       "23                           15                  0.0000   \n",
       "24                           15                  0.0000   \n",
       "25                           15                  0.0000   \n",
       "26                           15                  0.0000   \n",
       "27                           15                  0.0000   \n",
       "28                           15                  0.0000   \n",
       "29                           15                  0.0000   \n",
       "...                         ...                     ...   \n",
       "113905                       80                  0.0000   \n",
       "113906                       80                  0.0000   \n",
       "113907                       80                  0.0000   \n",
       "113908                       80                  0.0000   \n",
       "113909                       80                  0.0000   \n",
       "113910                       80                  0.0000   \n",
       "113911                       80                  0.0000   \n",
       "113912                       80                  0.0000   \n",
       "113913                       80                  0.0000   \n",
       "113914                       80                  0.0000   \n",
       "113915                       80                  0.0000   \n",
       "113916                       80                  0.0000   \n",
       "113917                       80                  0.0000   \n",
       "113918                       80                  0.0000   \n",
       "113919                       80                  0.0000   \n",
       "113920                       80                  0.0000   \n",
       "113921                       80                  0.0000   \n",
       "113922                       80                  0.0000   \n",
       "113923                       80                  0.0000   \n",
       "113924                       80                  0.0000   \n",
       "113925                       80                  0.0000   \n",
       "113926                       80                  0.0000   \n",
       "113927                       80                  0.0000   \n",
       "113928                       80                  0.0000   \n",
       "113929                       80                  0.0000   \n",
       "113930                       80                  0.0000   \n",
       "113931                       80                  0.0000   \n",
       "113932                       80                  0.0000   \n",
       "113933                       80                  0.0000   \n",
       "113934                       80                  0.0000   \n",
       "\n",
       "        Base flow rate(Fb:L/h)  Heating/cooling water flow rate(Fc:L/h)  \\\n",
       "0                      30.1180                                  9.83350   \n",
       "1                      51.2210                                 18.15500   \n",
       "2                      54.3020                                  9.59820   \n",
       "3                      37.8160                                  4.33950   \n",
       "4                      18.9080                                  1.10450   \n",
       "5                       9.4541                                  0.00010   \n",
       "6                       4.7270                                  0.00010   \n",
       "7                       2.3635                                  0.00010   \n",
       "8                       0.0000                                  0.00010   \n",
       "9                       0.0000                                  0.51077   \n",
       "10                      6.7741                                  1.63800   \n",
       "11                     18.1260                                  3.24110   \n",
       "12                     28.0370                                  5.20940   \n",
       "13                     31.9080                                  7.45310   \n",
       "14                     28.3970                                  9.85710   \n",
       "15                     19.5940                                 12.32700   \n",
       "16                     10.5880                                 14.66500   \n",
       "17                      6.2774                                 17.04900   \n",
       "18                      9.0006                                 19.67100   \n",
       "19                     17.2010                                 22.80300   \n",
       "20                     26.0410                                 25.71200   \n",
       "21                     30.9790                                 28.29700   \n",
       "22                     29.3820                                 31.47000   \n",
       "23                     22.3890                                 34.48900   \n",
       "24                     14.0170                                 38.27200   \n",
       "25                      9.5520                                 42.59500   \n",
       "26                     11.9440                                 46.90700   \n",
       "27                     19.5920                                 51.04600   \n",
       "28                     28.4160                                 55.68000   \n",
       "29                     33.8550                                 58.83500   \n",
       "...                        ...                                      ...   \n",
       "113905                 10.2650                                 37.76700   \n",
       "113906                  6.2743                                 11.33000   \n",
       "113907                  4.7721                                 38.68600   \n",
       "113908                  6.4984                                 11.60600   \n",
       "113909                 10.5100                                 72.00000   \n",
       "113910                 14.8910                                 45.81000   \n",
       "113911                 17.8040                                 13.74300   \n",
       "113912                 17.6270                                 45.92000   \n",
       "113913                 14.2830                                 18.94400   \n",
       "113914                  9.4585                                  5.68330   \n",
       "113915                  5.5024                                  1.70500   \n",
       "113916                  4.2791                                  0.51150   \n",
       "113917                  6.2738                                 33.20000   \n",
       "113918                 10.3150                                  9.96000   \n",
       "113919                 14.3400                                 77.07100   \n",
       "113920                 16.2320                                 45.39500   \n",
       "113921                 15.1180                                 13.61800   \n",
       "113922                 11.9930                                 48.95300   \n",
       "113923                  8.3346                                 14.68600   \n",
       "113924                  6.1901                                 93.39500   \n",
       "113925                  6.2708                                 61.46100   \n",
       "113926                  8.5039                                 18.43800   \n",
       "113927                 11.6800                                 61.79200   \n",
       "113928                 14.2350                                 32.54100   \n",
       "113929                 14.6420                                  9.76240   \n",
       "113930                 12.9000                                 33.58600   \n",
       "113931                 10.0470                                 10.07600   \n",
       "113932                  7.3609                                 69.34500   \n",
       "113933                  6.2794                                 38.61000   \n",
       "113934                  7.3055                                 11.58300   \n",
       "\n",
       "        Heating water flow rate(Fh:L/h)  Water for injection/dilution(Fw:L/h)  \\\n",
       "0                               0.00010                                     0   \n",
       "1                               0.00010                                     0   \n",
       "2                               0.00010                                     0   \n",
       "3                               0.00010                                     0   \n",
       "4                               0.00010                                     0   \n",
       "5                               0.00010                                     0   \n",
       "6                               0.00010                                     0   \n",
       "7                               0.00010                                     0   \n",
       "8                               0.00010                                     0   \n",
       "9                               0.00010                                     0   \n",
       "10                              0.00010                                     0   \n",
       "11                              0.00010                                     0   \n",
       "12                              0.00010                                     0   \n",
       "13                              0.00010                                     0   \n",
       "14                              0.00010                                     0   \n",
       "15                              0.00010                                     0   \n",
       "16                              0.00010                                     0   \n",
       "17                              0.00010                                     0   \n",
       "18                              0.00010                                     0   \n",
       "19                              0.00010                                     0   \n",
       "20                              0.00010                                     0   \n",
       "21                              0.00010                                     0   \n",
       "22                              0.00010                                     0   \n",
       "23                              0.00010                                     0   \n",
       "24                              0.00010                                     0   \n",
       "25                              0.00010                                     0   \n",
       "26                              0.00010                                     0   \n",
       "27                              0.00010                                     0   \n",
       "28                              0.00010                                     0   \n",
       "29                              0.00010                                     0   \n",
       "...                                 ...                                   ...   \n",
       "113905                          0.80781                                   250   \n",
       "113906                         60.91900                                   250   \n",
       "113907                          6.09190                                   250   \n",
       "113908                         96.28600                                   250   \n",
       "113909                          9.62860                                   250   \n",
       "113910                          0.96286                                   250   \n",
       "113911                         66.10500                                   250   \n",
       "113912                          6.61050                                   250   \n",
       "113913                          0.66105                                   250   \n",
       "113914                         49.94000                                   250   \n",
       "113915                          0.00010                                   250   \n",
       "113916                         67.87900                                   250   \n",
       "113917                          6.78790                                   250   \n",
       "113918                        106.42000                                   250   \n",
       "113919                         10.64200                                   250   \n",
       "113920                          1.06420                                   250   \n",
       "113921                         72.46900                                   250   \n",
       "113922                          7.24690                                   250   \n",
       "113923                        119.94000                                   250   \n",
       "113924                         11.99400                                   250   \n",
       "113925                          1.19940                                   250   \n",
       "113926                         80.87500                                   250   \n",
       "113927                          8.08750                                   250   \n",
       "113928                          0.80875                                   250   \n",
       "113929                         59.35900                                   250   \n",
       "113930                          5.93590                                   250   \n",
       "113931                         98.83400                                   250   \n",
       "113932                          9.88340                                   250   \n",
       "113933                          0.98834                                   250   \n",
       "113934                         67.53600                                   250   \n",
       "\n",
       "        Air head pressure(pressure:bar) ...        210       209       208  \\\n",
       "0                                   0.6 ...        0.0       0.0       0.0   \n",
       "1                                   0.6 ...        0.0       0.0       0.0   \n",
       "2                                   0.6 ...        0.0       0.0       0.0   \n",
       "3                                   0.6 ...        0.0       0.0       0.0   \n",
       "4                                   0.6 ...        0.0       0.0       0.0   \n",
       "5                                   0.6 ...        0.0       0.0       0.0   \n",
       "6                                   0.6 ...        0.0       0.0       0.0   \n",
       "7                                   0.6 ...        0.0       0.0       0.0   \n",
       "8                                   0.6 ...        0.0       0.0       0.0   \n",
       "9                                   0.6 ...        0.0       0.0       0.0   \n",
       "10                                  0.6 ...   469490.0  476530.0  482900.0   \n",
       "11                                  0.6 ...   515860.0  522970.0  529340.0   \n",
       "12                                  0.6 ...   471800.0  478630.0  484640.0   \n",
       "13                                  0.6 ...   488170.0  495150.0  501390.0   \n",
       "14                                  0.6 ...   478310.0  485360.0  491650.0   \n",
       "15                                  0.6 ...   494180.0  500950.0  507090.0   \n",
       "16                                  0.6 ...   502350.0  509310.0  515660.0   \n",
       "17                                  0.6 ...   515250.0  522090.0  528370.0   \n",
       "18                                  0.6 ...   488590.0  495600.0  501850.0   \n",
       "19                                  0.6 ...   500790.0  507650.0  513830.0   \n",
       "20                                  0.6 ...   489420.0  496440.0  502770.0   \n",
       "21                                  0.6 ...   538790.0  545720.0  551970.0   \n",
       "22                                  0.6 ...   484760.0  491500.0  497590.0   \n",
       "23                                  0.6 ...   511660.0  518660.0  525120.0   \n",
       "24                                  0.6 ...   488300.0  494910.0  500870.0   \n",
       "25                                  0.6 ...   497370.0  504260.0  510530.0   \n",
       "26                                  0.6 ...   492400.0  499390.0  505650.0   \n",
       "27                                  0.6 ...   496830.0  503790.0  510170.0   \n",
       "28                                  0.6 ...   538600.0  545570.0  551830.0   \n",
       "29                                  0.6 ...   466270.0  473120.0  479180.0   \n",
       "...                                 ... ...        ...       ...       ...   \n",
       "113905                              0.9 ...   795170.0  802230.0  808660.0   \n",
       "113906                              0.9 ...   834420.0  842000.0  848850.0   \n",
       "113907                              0.9 ...   797210.0  804460.0  811000.0   \n",
       "113908                              0.9 ...   803900.0  811150.0  817790.0   \n",
       "113909                              0.9 ...   826520.0  833840.0  840520.0   \n",
       "113910                              0.9 ...   828630.0  835910.0  842480.0   \n",
       "113911                              0.9 ...   821110.0  828240.0  834760.0   \n",
       "113912                              0.9 ...   809630.0  816970.0  823720.0   \n",
       "113913                              0.9 ...   801050.0  808190.0  814730.0   \n",
       "113914                              0.9 ...   790710.0  798040.0  804650.0   \n",
       "113915                              0.9 ...   809710.0  816970.0  823630.0   \n",
       "113916                              0.9 ...   823180.0  830370.0  836880.0   \n",
       "113917                              0.9 ...   811510.0  818690.0  825130.0   \n",
       "113918                              0.9 ...   807400.0  814770.0  821560.0   \n",
       "113919                              0.9 ...   822560.0  829580.0  835980.0   \n",
       "113920                              0.9 ...   838120.0  845580.0  852450.0   \n",
       "113921                              0.9 ...   788650.0  795890.0  802420.0   \n",
       "113922                              0.9 ...   794280.0  801240.0  807540.0   \n",
       "113923                              0.9 ...   810380.0  817530.0  824110.0   \n",
       "113924                              0.9 ...   810820.0  818080.0  824590.0   \n",
       "113925                              0.9 ...   821430.0  828750.0  835440.0   \n",
       "113926                              0.9 ...   798730.0  805960.0  812650.0   \n",
       "113927                              0.9 ...   798640.0  806010.0  812720.0   \n",
       "113928                              0.9 ...   795140.0  802440.0  809150.0   \n",
       "113929                              0.9 ...   813310.0  820650.0  827360.0   \n",
       "113930                              0.9 ...   816050.0  823390.0  830160.0   \n",
       "113931                              0.9 ...   773520.0  780840.0  787470.0   \n",
       "113932                              0.9 ...   788240.0  795550.0  802190.0   \n",
       "113933                              0.9 ...   781180.0  788420.0  794950.0   \n",
       "113934                              0.9 ...   778800.0  785950.0  792440.0   \n",
       "\n",
       "             207       206       205       204       203  202  201  \n",
       "0            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "1            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "2            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "3            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "4            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "5            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "6            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "7            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "8            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "9            0.0       0.0       0.0       0.0       0.0  NaN  NaN  \n",
       "10      488050.0  491330.0  492540.0  491990.0  489940.0  NaN  NaN  \n",
       "11      534260.0  537480.0  538580.0  537930.0  535880.0  NaN  NaN  \n",
       "12      489260.0  491920.0  492710.0  491700.0  489820.0  NaN  NaN  \n",
       "13      506250.0  509220.0  510150.0  509470.0  508260.0  NaN  NaN  \n",
       "14      496580.0  499650.0  500790.0  500070.0  498190.0  NaN  NaN  \n",
       "15      511850.0  514660.0  515630.0  514840.0  513130.0  NaN  NaN  \n",
       "16      520620.0  523600.0  524760.0  524280.0  522570.0  NaN  NaN  \n",
       "17      533390.0  536390.0  537200.0  536550.0  534500.0  NaN  NaN  \n",
       "18      506710.0  509680.0  510630.0  509980.0  508440.0  NaN  NaN  \n",
       "19      518650.0  521410.0  521970.0  520920.0  519370.0  NaN  NaN  \n",
       "20      507690.0  510700.0  511510.0  510850.0  508810.0  NaN  NaN  \n",
       "21      556740.0  559710.0  560840.0  560460.0  559240.0  NaN  NaN  \n",
       "22      502170.0  505000.0  505880.0  505220.0  503680.0  NaN  NaN  \n",
       "23      530220.0  533500.0  534610.0  533660.0  532110.0  NaN  NaN  \n",
       "24      505540.0  508220.0  508940.0  507930.0  506050.0  NaN  NaN  \n",
       "25      515370.0  518300.0  519280.0  518360.0  516480.0  NaN  NaN  \n",
       "26      510410.0  513240.0  514110.0  513300.0  511420.0  NaN  NaN  \n",
       "27      515290.0  518450.0  519450.0  518400.0  516350.0  NaN  NaN  \n",
       "28      556670.0  559670.0  560480.0  559500.0  557780.0  NaN  NaN  \n",
       "29      483660.0  486320.0  487110.0  485930.0  483720.0  NaN  NaN  \n",
       "...          ...       ...       ...       ...       ...  ...  ...  \n",
       "113905  813860.0  817190.0  818630.0  818360.0  816970.0  NaN  NaN  \n",
       "113906  854280.0  857750.0  859150.0  858610.0  857390.0  NaN  NaN  \n",
       "113907  816090.0  819250.0  820470.0  820370.0  819300.0  NaN  NaN  \n",
       "113908  822960.0  826240.0  827490.0  826950.0  825220.0  NaN  NaN  \n",
       "113909  845870.0  849510.0  851100.0  850700.0  849640.0  NaN  NaN  \n",
       "113910  847680.0  850990.0  852120.0  851610.0  850050.0  NaN  NaN  \n",
       "113911  839980.0  843410.0  844830.0  844690.0  843460.0  NaN  NaN  \n",
       "113912  829110.0  832680.0  834040.0  833770.0  832370.0  NaN  NaN  \n",
       "113913  819860.0  823090.0  824260.0  823680.0  822290.0  NaN  NaN  \n",
       "113914  810010.0  813450.0  814780.0  814280.0  812710.0  NaN  NaN  \n",
       "113915  828890.0  832450.0  834110.0  834040.0  833140.0  NaN  NaN  \n",
       "113916  841990.0  845310.0  846540.0  846300.0  844570.0  NaN  NaN  \n",
       "113917  830080.0  833100.0  834170.0  833400.0  831500.0  NaN  NaN  \n",
       "113918  827010.0  830520.0  832000.0  831660.0  830420.0  NaN  NaN  \n",
       "113919  840930.0  844020.0  845220.0  845080.0  843840.0  NaN  NaN  \n",
       "113920  857970.0  861580.0  863240.0  863170.0  861760.0  NaN  NaN  \n",
       "113921  807510.0  810870.0  812370.0  811920.0  810690.0  NaN  NaN  \n",
       "113922  812550.0  815800.0  816900.0  816190.0  814610.0  NaN  NaN  \n",
       "113923  829260.0  832660.0  833730.0  832950.0  831050.0  NaN  NaN  \n",
       "113924  829640.0  832810.0  833960.0  833390.0  831980.0  NaN  NaN  \n",
       "113925  840690.0  844100.0  845400.0  844990.0  843420.0  NaN  NaN  \n",
       "113926  818010.0  821400.0  822440.0  821760.0  820350.0  NaN  NaN  \n",
       "113927  817950.0  821330.0  822770.0  822520.0  820780.0  NaN  NaN  \n",
       "113928  814490.0  818050.0  819600.0  819460.0  818220.0  NaN  NaN  \n",
       "113929  832760.0  836270.0  837740.0  837390.0  835650.0  NaN  NaN  \n",
       "113930  835530.0  839140.0  840570.0  840160.0  838580.0  NaN  NaN  \n",
       "113931  792750.0  796220.0  797610.0  797270.0  796020.0  NaN  NaN  \n",
       "113932  807420.0  810590.0  811660.0  811210.0  809960.0  NaN  NaN  \n",
       "113933  800140.0  803610.0  804900.0  804490.0  803410.0  NaN  NaN  \n",
       "113934  797700.0  801130.0  802350.0  801770.0  799850.0  NaN  NaN  \n",
       "\n",
       "[113935 rows x 2239 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary of Dataframe for raw data\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Data Processing\n",
    "### Split data into spectral and process data\n",
    "Splitting the data into process measurement data and Raman spectroscopy data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Time (h)</th>\n",
       "      <th>Aeration rate(Fg:L/h)</th>\n",
       "      <th>Agitator RPM(RPM:RPM)</th>\n",
       "      <th>Sugar feed rate(Fs:L/h)</th>\n",
       "      <th>Acid flow rate(Fa:L/h)</th>\n",
       "      <th>Base flow rate(Fb:L/h)</th>\n",
       "      <th>Heating/cooling water flow rate(Fc:L/h)</th>\n",
       "      <th>Heating water flow rate(Fh:L/h)</th>\n",
       "      <th>Water for injection/dilution(Fw:L/h)</th>\n",
       "      <th>Air head pressure(pressure:bar)</th>\n",
       "      <th>...</th>\n",
       "      <th>Ammonia shots(NH3_shots:kgs)</th>\n",
       "      <th>Viscosity(Viscosity_offline:centPoise)</th>\n",
       "      <th>Fault reference(Fault_ref:Fault ref)</th>\n",
       "      <th>0 - Recipe driven 1 - Operator controlled(Control_ref:Control ref)</th>\n",
       "      <th>1- No Raman spec</th>\n",
       "      <th>1-Raman spec recorded</th>\n",
       "      <th>Batch reference(Batch_ref:Batch ref)</th>\n",
       "      <th>2-PAT control(PAT_ref:PAT ref)</th>\n",
       "      <th>Batch ID</th>\n",
       "      <th>Fault flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.0</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>113935.0</td>\n",
       "      <td>2062.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>114.750656</td>\n",
       "      <td>65.246360</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.663764</td>\n",
       "      <td>0.073209</td>\n",
       "      <td>61.334389</td>\n",
       "      <td>74.346341</td>\n",
       "      <td>20.763025</td>\n",
       "      <td>154.811954</td>\n",
       "      <td>0.945026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.546454</td>\n",
       "      <td>0.011024</td>\n",
       "      <td>0.301795</td>\n",
       "      <td>1.295783</td>\n",
       "      <td>50.402466</td>\n",
       "      <td>50.402466</td>\n",
       "      <td>0.101154</td>\n",
       "      <td>89307.003616</td>\n",
       "      <td>89402.127915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>66.990504</td>\n",
       "      <td>11.690215</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.680134</td>\n",
       "      <td>0.552788</td>\n",
       "      <td>44.972713</td>\n",
       "      <td>108.022600</td>\n",
       "      <td>50.230266</td>\n",
       "      <td>155.601474</td>\n",
       "      <td>0.134269</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.073778</td>\n",
       "      <td>0.104415</td>\n",
       "      <td>0.459039</td>\n",
       "      <td>0.456396</td>\n",
       "      <td>28.862140</td>\n",
       "      <td>28.862140</td>\n",
       "      <td>0.301534</td>\n",
       "      <td>47765.751082</td>\n",
       "      <td>47852.683115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.075300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>57.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.766000</td>\n",
       "      <td>11.157000</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.812250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47016.500000</td>\n",
       "      <td>47029.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>114.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.407000</td>\n",
       "      <td>34.384000</td>\n",
       "      <td>0.159010</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53.154000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>89699.000000</td>\n",
       "      <td>89772.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>171.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>76.271500</td>\n",
       "      <td>94.904500</td>\n",
       "      <td>11.640500</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.536000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>129390.000000</td>\n",
       "      <td>129570.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>290.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>12.996000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.930000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>194630.000000</td>\n",
       "      <td>195340.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time (h)  Aeration rate(Fg:L/h)  Agitator RPM(RPM:RPM)  \\\n",
       "count  113935.000000          113935.000000               113935.0   \n",
       "mean      114.750656              65.246360                  100.0   \n",
       "std        66.990504              11.690215                    0.0   \n",
       "min         0.200000              20.000000                  100.0   \n",
       "25%        57.000000              60.000000                  100.0   \n",
       "50%       114.000000              65.000000                  100.0   \n",
       "75%       171.000000              75.000000                  100.0   \n",
       "max       290.000000              75.000000                  100.0   \n",
       "\n",
       "       Sugar feed rate(Fs:L/h)  Acid flow rate(Fa:L/h)  \\\n",
       "count            113935.000000           113935.000000   \n",
       "mean                 76.663764                0.073209   \n",
       "std                  25.680134                0.552788   \n",
       "min                   2.000000                0.000000   \n",
       "25%                  72.000000                0.000000   \n",
       "50%                  80.000000                0.000000   \n",
       "75%                  90.000000                0.000000   \n",
       "max                 150.000000               12.996000   \n",
       "\n",
       "       Base flow rate(Fb:L/h)  Heating/cooling water flow rate(Fc:L/h)  \\\n",
       "count           113935.000000                            113935.000000   \n",
       "mean                61.334389                                74.346341   \n",
       "std                 44.972713                               108.022600   \n",
       "min                  0.000000                                 0.000100   \n",
       "25%                 35.766000                                11.157000   \n",
       "50%                 55.407000                                34.384000   \n",
       "75%                 76.271500                                94.904500   \n",
       "max                225.000000                              1500.000000   \n",
       "\n",
       "       Heating water flow rate(Fh:L/h)  Water for injection/dilution(Fw:L/h)  \\\n",
       "count                    113935.000000                         113935.000000   \n",
       "mean                         20.763025                            154.811954   \n",
       "std                          50.230266                            155.601474   \n",
       "min                           0.000100                              0.000000   \n",
       "25%                           0.000100                              0.000000   \n",
       "50%                           0.159010                            100.000000   \n",
       "75%                          11.640500                            250.000000   \n",
       "max                        1500.000000                            500.000000   \n",
       "\n",
       "       Air head pressure(pressure:bar)      ...        \\\n",
       "count                    113935.000000      ...         \n",
       "mean                          0.945026      ...         \n",
       "std                           0.134269      ...         \n",
       "min                           0.600000      ...         \n",
       "25%                           0.900000      ...         \n",
       "50%                           0.900000      ...         \n",
       "75%                           1.100000      ...         \n",
       "max                           1.100000      ...         \n",
       "\n",
       "       Ammonia shots(NH3_shots:kgs)  Viscosity(Viscosity_offline:centPoise)  \\\n",
       "count                      113935.0                             2062.000000   \n",
       "mean                            0.0                               51.546454   \n",
       "std                             0.0                               24.073778   \n",
       "min                             0.0                                4.075300   \n",
       "25%                             0.0                               34.812250   \n",
       "50%                             0.0                               53.154000   \n",
       "75%                             0.0                               73.536000   \n",
       "max                             0.0                              117.930000   \n",
       "\n",
       "       Fault reference(Fault_ref:Fault ref)  \\\n",
       "count                         113935.000000   \n",
       "mean                               0.011024   \n",
       "std                                0.104415   \n",
       "min                                0.000000   \n",
       "25%                                0.000000   \n",
       "50%                                0.000000   \n",
       "75%                                0.000000   \n",
       "max                                1.000000   \n",
       "\n",
       "       0 - Recipe driven 1 - Operator controlled(Control_ref:Control ref)  \\\n",
       "count                                      113935.000000                    \n",
       "mean                                            0.301795                    \n",
       "std                                             0.459039                    \n",
       "min                                             0.000000                    \n",
       "25%                                             0.000000                    \n",
       "50%                                             0.000000                    \n",
       "75%                                             1.000000                    \n",
       "max                                             1.000000                    \n",
       "\n",
       "       1- No Raman spec   1-Raman spec recorded  \\\n",
       "count     113935.000000           113935.000000   \n",
       "mean           1.295783               50.402466   \n",
       "std            0.456396               28.862140   \n",
       "min            1.000000                1.000000   \n",
       "25%            1.000000               26.000000   \n",
       "50%            1.000000               50.000000   \n",
       "75%            2.000000               76.000000   \n",
       "max            2.000000              100.000000   \n",
       "\n",
       "       Batch reference(Batch_ref:Batch ref)  2-PAT control(PAT_ref:PAT ref)  \\\n",
       "count                         113935.000000                   113935.000000   \n",
       "mean                              50.402466                        0.101154   \n",
       "std                               28.862140                        0.301534   \n",
       "min                                1.000000                        0.000000   \n",
       "25%                               26.000000                        0.000000   \n",
       "50%                               50.000000                        0.000000   \n",
       "75%                               76.000000                        0.000000   \n",
       "max                              100.000000                        1.000000   \n",
       "\n",
       "            Batch ID     Fault flag  \n",
       "count  113935.000000  113935.000000  \n",
       "mean    89307.003616   89402.127915  \n",
       "std     47765.751082   47852.683115  \n",
       "min         0.000000       0.000000  \n",
       "25%     47016.500000   47029.500000  \n",
       "50%     89699.000000   89772.000000  \n",
       "75%    129390.000000  129570.000000  \n",
       "max    194630.000000  195340.000000  \n",
       "\n",
       "[8 rows x 39 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variable_raman_data = np.split(data, [data.columns.get_loc(\"2400\")], axis=1)\n",
    "variable_data = variable_raman_data[0]\n",
    "variable_data.describe()\n",
    "### Reable Batch ID's correctly\n",
    "variable_data = variable_data.rename(columns={'2-PAT control(PAT_ref:PAT ref)': 'Batch reference(Batch_ref:Batch ref)','Batch reference(Batch_ref:Batch ref)':'2-PAT control(PAT_ref:PAT ref)'})\n",
    "raman_spectra = variable_raman_data[1]\n",
    "batch_ref_df = variable_data[['Batch reference(Batch_ref:Batch ref)']]\n",
    "raman_spectra_batch_id = pd.concat([batch_ref_df, raman_spectra], axis=1)\n",
    "variable_data.shape\n",
    "variable_data.head(3)\n",
    "variable_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "variable_list = variable_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Time (h)</th>\n",
       "      <th>Aeration rate(Fg:L/h)</th>\n",
       "      <th>Agitator RPM(RPM:RPM)</th>\n",
       "      <th>Sugar feed rate(Fs:L/h)</th>\n",
       "      <th>Acid flow rate(Fa:L/h)</th>\n",
       "      <th>Base flow rate(Fb:L/h)</th>\n",
       "      <th>Heating/cooling water flow rate(Fc:L/h)</th>\n",
       "      <th>Heating water flow rate(Fh:L/h)</th>\n",
       "      <th>Water for injection/dilution(Fw:L/h)</th>\n",
       "      <th>Air head pressure(pressure:bar)</th>\n",
       "      <th>...</th>\n",
       "      <th>Ammonia shots(NH3_shots:kgs)</th>\n",
       "      <th>Viscosity(Viscosity_offline:centPoise)</th>\n",
       "      <th>Fault reference(Fault_ref:Fault ref)</th>\n",
       "      <th>0 - Recipe driven 1 - Operator controlled(Control_ref:Control ref)</th>\n",
       "      <th>1- No Raman spec</th>\n",
       "      <th>1-Raman spec recorded</th>\n",
       "      <th>Batch reference(Batch_ref:Batch ref)</th>\n",
       "      <th>2-PAT control(PAT_ref:PAT ref)</th>\n",
       "      <th>Batch ID</th>\n",
       "      <th>Fault flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.0</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>113935.0</td>\n",
       "      <td>2062.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "      <td>113935.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>114.750656</td>\n",
       "      <td>65.246360</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.663764</td>\n",
       "      <td>0.073209</td>\n",
       "      <td>61.334389</td>\n",
       "      <td>74.346341</td>\n",
       "      <td>20.763025</td>\n",
       "      <td>154.811954</td>\n",
       "      <td>0.945026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.546454</td>\n",
       "      <td>0.011024</td>\n",
       "      <td>0.301795</td>\n",
       "      <td>1.295783</td>\n",
       "      <td>50.402466</td>\n",
       "      <td>50.402466</td>\n",
       "      <td>0.101154</td>\n",
       "      <td>89307.003616</td>\n",
       "      <td>89402.127915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>66.990504</td>\n",
       "      <td>11.690215</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.680134</td>\n",
       "      <td>0.552788</td>\n",
       "      <td>44.972713</td>\n",
       "      <td>108.022600</td>\n",
       "      <td>50.230266</td>\n",
       "      <td>155.601474</td>\n",
       "      <td>0.134269</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.073778</td>\n",
       "      <td>0.104415</td>\n",
       "      <td>0.459039</td>\n",
       "      <td>0.456396</td>\n",
       "      <td>28.862140</td>\n",
       "      <td>28.862140</td>\n",
       "      <td>0.301534</td>\n",
       "      <td>47765.751082</td>\n",
       "      <td>47852.683115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.075300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>57.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.766000</td>\n",
       "      <td>11.157000</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.812250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47016.500000</td>\n",
       "      <td>47029.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>114.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.407000</td>\n",
       "      <td>34.384000</td>\n",
       "      <td>0.159010</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53.154000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>89699.000000</td>\n",
       "      <td>89772.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>171.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>76.271500</td>\n",
       "      <td>94.904500</td>\n",
       "      <td>11.640500</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.536000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>129390.000000</td>\n",
       "      <td>129570.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>290.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>12.996000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.930000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>194630.000000</td>\n",
       "      <td>195340.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time (h)  Aeration rate(Fg:L/h)  Agitator RPM(RPM:RPM)  \\\n",
       "count  113935.000000          113935.000000               113935.0   \n",
       "mean      114.750656              65.246360                  100.0   \n",
       "std        66.990504              11.690215                    0.0   \n",
       "min         0.200000              20.000000                  100.0   \n",
       "25%        57.000000              60.000000                  100.0   \n",
       "50%       114.000000              65.000000                  100.0   \n",
       "75%       171.000000              75.000000                  100.0   \n",
       "max       290.000000              75.000000                  100.0   \n",
       "\n",
       "       Sugar feed rate(Fs:L/h)  Acid flow rate(Fa:L/h)  \\\n",
       "count            113935.000000           113935.000000   \n",
       "mean                 76.663764                0.073209   \n",
       "std                  25.680134                0.552788   \n",
       "min                   2.000000                0.000000   \n",
       "25%                  72.000000                0.000000   \n",
       "50%                  80.000000                0.000000   \n",
       "75%                  90.000000                0.000000   \n",
       "max                 150.000000               12.996000   \n",
       "\n",
       "       Base flow rate(Fb:L/h)  Heating/cooling water flow rate(Fc:L/h)  \\\n",
       "count           113935.000000                            113935.000000   \n",
       "mean                61.334389                                74.346341   \n",
       "std                 44.972713                               108.022600   \n",
       "min                  0.000000                                 0.000100   \n",
       "25%                 35.766000                                11.157000   \n",
       "50%                 55.407000                                34.384000   \n",
       "75%                 76.271500                                94.904500   \n",
       "max                225.000000                              1500.000000   \n",
       "\n",
       "       Heating water flow rate(Fh:L/h)  Water for injection/dilution(Fw:L/h)  \\\n",
       "count                    113935.000000                         113935.000000   \n",
       "mean                         20.763025                            154.811954   \n",
       "std                          50.230266                            155.601474   \n",
       "min                           0.000100                              0.000000   \n",
       "25%                           0.000100                              0.000000   \n",
       "50%                           0.159010                            100.000000   \n",
       "75%                          11.640500                            250.000000   \n",
       "max                        1500.000000                            500.000000   \n",
       "\n",
       "       Air head pressure(pressure:bar)      ...        \\\n",
       "count                    113935.000000      ...         \n",
       "mean                          0.945026      ...         \n",
       "std                           0.134269      ...         \n",
       "min                           0.600000      ...         \n",
       "25%                           0.900000      ...         \n",
       "50%                           0.900000      ...         \n",
       "75%                           1.100000      ...         \n",
       "max                           1.100000      ...         \n",
       "\n",
       "       Ammonia shots(NH3_shots:kgs)  Viscosity(Viscosity_offline:centPoise)  \\\n",
       "count                      113935.0                             2062.000000   \n",
       "mean                            0.0                               51.546454   \n",
       "std                             0.0                               24.073778   \n",
       "min                             0.0                                4.075300   \n",
       "25%                             0.0                               34.812250   \n",
       "50%                             0.0                               53.154000   \n",
       "75%                             0.0                               73.536000   \n",
       "max                             0.0                              117.930000   \n",
       "\n",
       "       Fault reference(Fault_ref:Fault ref)  \\\n",
       "count                         113935.000000   \n",
       "mean                               0.011024   \n",
       "std                                0.104415   \n",
       "min                                0.000000   \n",
       "25%                                0.000000   \n",
       "50%                                0.000000   \n",
       "75%                                0.000000   \n",
       "max                                1.000000   \n",
       "\n",
       "       0 - Recipe driven 1 - Operator controlled(Control_ref:Control ref)  \\\n",
       "count                                      113935.000000                    \n",
       "mean                                            0.301795                    \n",
       "std                                             0.459039                    \n",
       "min                                             0.000000                    \n",
       "25%                                             0.000000                    \n",
       "50%                                             0.000000                    \n",
       "75%                                             1.000000                    \n",
       "max                                             1.000000                    \n",
       "\n",
       "       1- No Raman spec   1-Raman spec recorded  \\\n",
       "count     113935.000000           113935.000000   \n",
       "mean           1.295783               50.402466   \n",
       "std            0.456396               28.862140   \n",
       "min            1.000000                1.000000   \n",
       "25%            1.000000               26.000000   \n",
       "50%            1.000000               50.000000   \n",
       "75%            2.000000               76.000000   \n",
       "max            2.000000              100.000000   \n",
       "\n",
       "       Batch reference(Batch_ref:Batch ref)  2-PAT control(PAT_ref:PAT ref)  \\\n",
       "count                         113935.000000                   113935.000000   \n",
       "mean                              50.402466                        0.101154   \n",
       "std                               28.862140                        0.301534   \n",
       "min                                1.000000                        0.000000   \n",
       "25%                               26.000000                        0.000000   \n",
       "50%                               50.000000                        0.000000   \n",
       "75%                               76.000000                        0.000000   \n",
       "max                              100.000000                        1.000000   \n",
       "\n",
       "            Batch ID     Fault flag  \n",
       "count  113935.000000  113935.000000  \n",
       "mean    89307.003616   89402.127915  \n",
       "std     47765.751082   47852.683115  \n",
       "min         0.000000       0.000000  \n",
       "25%     47016.500000   47029.500000  \n",
       "50%     89699.000000   89772.000000  \n",
       "75%    129390.000000  129570.000000  \n",
       "max    194630.000000  195340.000000  \n",
       "\n",
       "[8 rows x 39 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variable_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Variable data plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "54fe623d625a40019e52ce3656f2bbb1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(index=13, options=('Time (h)', 'Aeration rate(Fg:L/h)', 'Agitator RPM(RPM:RPM)', 'Sugar feed rate(Fs:…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    " \n",
    "\n",
    "variable_plot_selection = widgets.Dropdown(options=variable_list, value = 'Penicillin concentration(P:g/L)')\n",
    "variable_plot_selection\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Penicillin concentration(P:g/L)')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,6))\n",
    "bp = variable_data.groupby('Batch reference(Batch_ref:Batch ref)').plot(x = 'Time (h)', y = variable_plot_selection.value,   ax=ax, legend = False, )\n",
    "ax.set_title('Summary of Campaigns')\n",
    "ax.set_xlabel('Time')\n",
    "ax.set_ylabel(variable_plot_selection.value)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Raman Data plot \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "raman_data = variable_data.groupby('Batch reference(Batch_ref:Batch ref)').get_group(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Intensity = raman_spectra.iloc[100:1208, 100:1500]\n",
    "x_wave = raman_spectra.index[100:1500]\n",
    "Temp = Intensity.transpose()\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(x_wave,Temp)\n",
    "plt.ylabel('Intensity units')\n",
    "plt.xlabel('Wavelengths (cm^(-1))')\n",
    "plt\n",
    "plt.show()"
   ]
  }
 ],
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  "hide_input": true,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
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  "toc": {
   "base_numbering": 1,
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   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
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}