Visualising Bangalore Air Pollution using Brunel

Visualising Bangalore Air Pollution using Brunel.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing Bangalore Air Pollution with Brunel\n",
    "\n",
    "\n",
    "Data is availabe on GitHub at https://github.com/thejeshgn/cpcb_bangalore/ which is scraped from the pollution control board site. We will try and do some analysis using that data and Brunel.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Data\n",
    "We will read the csv directly from github using the requests and create the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>NO</th>\n",
       "      <th>station</th>\n",
       "      <th>key</th>\n",
       "      <th>year</th>\n",
       "      <th>date</th>\n",
       "      <th>from_time</th>\n",
       "      <th>RH</th>\n",
       "      <th>SO2</th>\n",
       "      <th>CO</th>\n",
       "      <th>...</th>\n",
       "      <th>TOLU</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>SR</th>\n",
       "      <th>AT</th>\n",
       "      <th>PM10</th>\n",
       "      <th>PRES</th>\n",
       "      <th>ETHYL</th>\n",
       "      <th>NMHC</th>\n",
       "      <th>THC</th>\n",
       "      <th>PXYLEN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>34844</th>\n",
       "      <td>34845</td>\n",
       "      <td>42.1</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_19_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>19:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.67</td>\n",
       "      <td>...</td>\n",
       "      <td>44.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34845</th>\n",
       "      <td>34846</td>\n",
       "      <td>11.0</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_20_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>20:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.45</td>\n",
       "      <td>...</td>\n",
       "      <td>44.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34846</th>\n",
       "      <td>34847</td>\n",
       "      <td>22.0</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_21_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>21:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.84</td>\n",
       "      <td>...</td>\n",
       "      <td>41.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34847</th>\n",
       "      <td>34848</td>\n",
       "      <td>7.2</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_22_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>22:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.34</td>\n",
       "      <td>...</td>\n",
       "      <td>41.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34848</th>\n",
       "      <td>34849</td>\n",
       "      <td>11.6</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_23_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>23:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>39.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id    NO    station                         key  year        date  \\\n",
       "34844  34845  42.1  JAYANAGAR  JAYANAGAR_17_03_2018_19_00  2018  17/03/2018   \n",
       "34845  34846  11.0  JAYANAGAR  JAYANAGAR_17_03_2018_20_00  2018  17/03/2018   \n",
       "34846  34847  22.0  JAYANAGAR  JAYANAGAR_17_03_2018_21_00  2018  17/03/2018   \n",
       "34847  34848   7.2  JAYANAGAR  JAYANAGAR_17_03_2018_22_00  2018  17/03/2018   \n",
       "34848  34849  11.6  JAYANAGAR  JAYANAGAR_17_03_2018_23_00  2018  17/03/2018   \n",
       "\n",
       "      from_time  RH   SO2    CO   ...    TOLU  TEMP  SR  AT  PM10  PRES  \\\n",
       "34844     19:00 NaN  12.9  4.67   ...    44.9   NaN NaN NaN   114   NaN   \n",
       "34845     20:00 NaN   5.8  5.45   ...    44.6   NaN NaN NaN   132   NaN   \n",
       "34846     21:00 NaN   NaN  5.84   ...    41.8   NaN NaN NaN    41   NaN   \n",
       "34847     22:00 NaN   NaN  5.34   ...    41.1   NaN NaN NaN    60   NaN   \n",
       "34848     23:00 NaN   NaN   NaN   ...    39.4   NaN NaN NaN    35   NaN   \n",
       "\n",
       "       ETHYL  NMHC  THC  PXYLEN  \n",
       "34844    NaN   NaN  NaN     5.5  \n",
       "34845    NaN   NaN  NaN     3.9  \n",
       "34846    NaN   NaN  NaN     4.5  \n",
       "34847    NaN   NaN  NaN     2.0  \n",
       "34848    NaN   NaN  NaN     2.5  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from io import StringIO\n",
    "import requests\n",
    "import pandas as pd\n",
    "\n",
    "def get_file(url):\n",
    "    resp2 = requests.get(url=url)\n",
    "    return StringIO(resp2.text)\n",
    "\n",
    "df = pd.read_csv(get_file('https://github.com/thejeshgn/cpcb_bangalore/raw/master/data/final/data.csv'))\n",
    "\n",
    "df.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>NO</th>\n",
       "      <th>station</th>\n",
       "      <th>key</th>\n",
       "      <th>year</th>\n",
       "      <th>date</th>\n",
       "      <th>from_time</th>\n",
       "      <th>RH</th>\n",
       "      <th>SO2</th>\n",
       "      <th>CO</th>\n",
       "      <th>...</th>\n",
       "      <th>TOLU</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>SR</th>\n",
       "      <th>AT</th>\n",
       "      <th>PM10</th>\n",
       "      <th>PRES</th>\n",
       "      <th>ETHYL</th>\n",
       "      <th>NMHC</th>\n",
       "      <th>THC</th>\n",
       "      <th>PXYLEN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>34844</th>\n",
       "      <td>34845</td>\n",
       "      <td>42.1</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_19_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>19:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.67</td>\n",
       "      <td>...</td>\n",
       "      <td>44.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34845</th>\n",
       "      <td>34846</td>\n",
       "      <td>11.0</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_20_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>20:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.45</td>\n",
       "      <td>...</td>\n",
       "      <td>44.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34846</th>\n",
       "      <td>34847</td>\n",
       "      <td>22.0</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_21_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>21:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.84</td>\n",
       "      <td>...</td>\n",
       "      <td>41.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34847</th>\n",
       "      <td>34848</td>\n",
       "      <td>7.2</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_22_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>22:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.34</td>\n",
       "      <td>...</td>\n",
       "      <td>41.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34848</th>\n",
       "      <td>34849</td>\n",
       "      <td>11.6</td>\n",
       "      <td>JAYANAGAR</td>\n",
       "      <td>JAYANAGAR_17_03_2018_23_00</td>\n",
       "      <td>2018</td>\n",
       "      <td>17/03/2018</td>\n",
       "      <td>23:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>39.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id    NO    station                         key  year        date  \\\n",
       "34844  34845  42.1  JAYANAGAR  JAYANAGAR_17_03_2018_19_00  2018  17/03/2018   \n",
       "34845  34846  11.0  JAYANAGAR  JAYANAGAR_17_03_2018_20_00  2018  17/03/2018   \n",
       "34846  34847  22.0  JAYANAGAR  JAYANAGAR_17_03_2018_21_00  2018  17/03/2018   \n",
       "34847  34848   7.2  JAYANAGAR  JAYANAGAR_17_03_2018_22_00  2018  17/03/2018   \n",
       "34848  34849  11.6  JAYANAGAR  JAYANAGAR_17_03_2018_23_00  2018  17/03/2018   \n",
       "\n",
       "      from_time  RH   SO2    CO   ...    TOLU  TEMP  SR  AT  PM10  PRES  \\\n",
       "34844     19:00 NaN  12.9  4.67   ...    44.9   NaN NaN NaN   114   NaN   \n",
       "34845     20:00 NaN   5.8  5.45   ...    44.6   NaN NaN NaN   132   NaN   \n",
       "34846     21:00 NaN   NaN  5.84   ...    41.8   NaN NaN NaN    41   NaN   \n",
       "34847     22:00 NaN   NaN  5.34   ...    41.1   NaN NaN NaN    60   NaN   \n",
       "34848     23:00 NaN   NaN   NaN   ...    39.4   NaN NaN NaN    35   NaN   \n",
       "\n",
       "       ETHYL  NMHC  THC  PXYLEN  \n",
       "34844    NaN   NaN  NaN     5.5  \n",
       "34845    NaN   NaN  NaN     3.9  \n",
       "34846    NaN   NaN  NaN     4.5  \n",
       "34847    NaN   NaN  NaN     2.0  \n",
       "34848    NaN   NaN  NaN     2.5  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clean\n",
    "We will remove the columns that we dont need. We need station, date, time and PM25 amd PM10 values. Rest can be removed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['id', 'station', 'year', 'date', 'from_time', 'PM25', 'PM10']"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "list(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop([ 'NO','key','RH', 'SO2', 'CO', 'O3', 'NOX', 'WS', 'WD', 'NO2', 'CH4', 'NH3', 'BENZ', 'TOLU', 'TEMP', 'SR', 'AT', 'PRES', 'ETHYL', 'NMHC', 'THC'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>station</th>\n",
       "      <th>year</th>\n",
       "      <th>date</th>\n",
       "      <th>from_time</th>\n",
       "      <th>PM25</th>\n",
       "      <th>PM10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BTM</td>\n",
       "      <td>2017</td>\n",
       "      <td>01/05/2017</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>20.51</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>BTM</td>\n",
       "      <td>2017</td>\n",
       "      <td>01/05/2017</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>17.22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>BTM</td>\n",
       "      <td>2017</td>\n",
       "      <td>01/05/2017</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>22.06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BTM</td>\n",
       "      <td>2017</td>\n",
       "      <td>01/05/2017</td>\n",
       "      <td>20:00:00</td>\n",
       "      <td>26.85</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>BTM</td>\n",
       "      <td>2017</td>\n",
       "      <td>02/05/2017</td>\n",
       "      <td>00:00:00</td>\n",
       "      <td>16.70</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id station  year        date from_time   PM25  PM10\n",
       "0   1     BTM  2017  01/05/2017  08:00:00  20.51   NaN\n",
       "1   2     BTM  2017  01/05/2017  12:00:00  17.22   NaN\n",
       "2   3     BTM  2017  01/05/2017  16:00:00  22.06   NaN\n",
       "3   4     BTM  2017  01/05/2017  20:00:00  26.85   NaN\n",
       "4   5     BTM  2017  02/05/2017  00:00:00  16.70   NaN"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25914, 7)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check format\n",
    "See if the data formats are okay. For example parse the date into date object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['PM25'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['PM10'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('<M8[ns]')"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['date'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['date'] =  pd.to_datetime(df['date'], format='%d/%m/%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('<M8[ns]')"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['date'].dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install Brunel\n",
    "INstall the brunel package and import it into the project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: brunel==2.3 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (2.3)\n",
      "Requirement already satisfied: pandas in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from brunel==2.3) (0.17.1)\n",
      "Requirement already satisfied: jupyter-pip in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from brunel==2.3) (0.3.1)\n",
      "Requirement already satisfied: JPype1 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from brunel==2.3) (0.6.1)\n",
      "Requirement already satisfied: ipython in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from brunel==2.3) (5.5.0)\n",
      "Requirement already satisfied: jinja2 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from brunel==2.3) (2.10)\n",
      "Requirement already satisfied: python-dateutil in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pandas->brunel==2.3) (2.4.2)\n",
      "Requirement already satisfied: pytz>=2011k in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pandas->brunel==2.3) (2018.4)\n",
      "Requirement already satisfied: numpy>=1.7.0 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pandas->brunel==2.3) (1.13.1)\n",
      "Requirement already satisfied: decorator in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (4.0.6)\n",
      "Requirement already satisfied: prompt-toolkit<2.0.0,>=1.0.4 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (1.0.14)\n",
      "Requirement already satisfied: setuptools>=18.5 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (40.2.0)\n",
      "Requirement already satisfied: backports.shutil-get-terminal-size; python_version == \"2.7\" in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (1.0.0)\n",
      "Requirement already satisfied: pexpect; sys_platform != \"win32\" in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (4.0.1)\n",
      "Requirement already satisfied: pathlib2; python_version == \"2.7\" or python_version == \"3.3\" in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (2.2.1)\n",
      "Requirement already satisfied: pygments in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (2.0.2)\n",
      "Requirement already satisfied: traitlets>=4.2 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (4.3.2)\n",
      "Requirement already satisfied: simplegeneric>0.8 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (0.8.1)\n",
      "Requirement already satisfied: pickleshare in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from ipython->brunel==2.3) (0.5)\n",
      "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from jinja2->brunel==2.3) (0.23)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from python-dateutil->pandas->brunel==2.3) (1.10.0)\n",
      "Requirement already satisfied: wcwidth in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from prompt-toolkit<2.0.0,>=1.0.4->ipython->brunel==2.3) (0.1.7)\n",
      "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pexpect; sys_platform != \"win32\"->ipython->brunel==2.3) (0.5)\n",
      "Requirement already satisfied: scandir; python_version < \"3.5\" in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pathlib2; python_version == \"2.7\" or python_version == \"3.3\"->ipython->brunel==2.3) (1.5)\n",
      "Requirement already satisfied: ipython-genutils in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from traitlets>=4.2->ipython->brunel==2.3) (0.1.0)\n",
      "Requirement already satisfied: enum34; python_version == \"2.7\" in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from traitlets>=4.2->ipython->brunel==2.3) (1.1.5)\n",
      "Requirement already satisfied: path.py in /usr/local/src/bluemix_jupyter_bundle.v103/notebook/lib/python2.7/site-packages (from pickleshare->ipython->brunel==2.3) (8.1.2)\n",
      "\u001b[31mtensorflow 1.2.1 has requirement bleach==1.5.0, but you'll have bleach 2.0.0 which is incompatible.\u001b[0m\n",
      "\u001b[31mtensorflow 1.2.1 has requirement html5lib==0.9999999, but you'll have html5lib 0.999999999 which is incompatible.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install brunel==2.3\n",
    "import brunel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's do some visuals\n",
    "\n",
    "Scatter plot of pm10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!--\n",
       "  ~ Copyright (c) 2015 IBM Corporation and others.\n",
       "  ~\n",
       "  ~ Licensed under the Apache License, Version 2.0 (the \"License\");\n",
       "  ~ You may not use this file except in compliance with the License.\n",
       "  ~ You may obtain a copy of the License at\n",
       "  ~\n",
       "  ~     http://www.apache.org/licenses/LICENSE-2.0\n",
       "  ~\n",
       "  ~ Unless required by applicable law or agreed to in writing, software\n",
       "  ~ distributed under the License is distributed on an \"AS IS\" BASIS,\n",
       "  ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
       "  ~ See the License for the specific language governing permissions and\n",
       "  ~ limitations under the License.\n",
       "  -->\n",
       "\n",
       "\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"/data/jupyter2/c80c0cad-084b-4d7e-94f1-c328c646e2b0/nbextensions/brunel_ext/brunel.2.3.css\">\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"/data/jupyter2/c80c0cad-084b-4d7e-94f1-c328c646e2b0/nbextensions/brunel_ext/sumoselect.css\">\n",
       "\n",
       "<style>\n",
       "    \n",
       "</style>\n",
       "\n",
       "<div id=\"controlsid42716c96-e204-11e8-8ddb-002590fb6664\" class=\"brunel\"/>\n",
       "<svg id=\"visid42716746-e204-11e8-8ddb-002590fb6664\" width=\"1200\" height=\"400\"></svg>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/*\n",
       " * Copyright (c) 2015 IBM Corporation and others.\n",
       " *\n",
       " * Licensed under the Apache License, Version 2.0 (the \"License\");\n",
       " * You may not use this file except in compliance with the License.\n",
       " * You may obtain a copy of the License at\n",
       " *\n",
       " *     http://www.apache.org/licenses/LICENSE-2.0\n",
       " *\n",
       " * Unless required by applicable law or agreed to in writing, software\n",
       " * distributed under the License is distributed on an \"AS IS\" BASIS,\n",
       " * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
       " * See the License for the specific language governing permissions and\n",
       " * limitations under the License.\n",
       " */\n",
       "\n",
       "require.config({\n",
       "    waitSeconds: 60,\n",
       "    paths: {\n",
       "        'd3': '//cdnjs.cloudflare.com/ajax/libs/d3/4.2.1/d3.min',\n",
       "        'topojson': '//cdnjs.cloudflare.com/ajax/libs/topojson/1.6.20/topojson.min',\n",
       "        'brunel' : '/data/jupyter2/c80c0cad-084b-4d7e-94f1-c328c646e2b0/nbextensions/brunel_ext/brunel.2.3.min',\n",
       "        'brunelControls' : '/data/jupyter2/c80c0cad-084b-4d7e-94f1-c328c646e2b0/nbextensions/brunel_ext/brunel.controls.2.3.min'\n",
       "    },\n",
       "    shim: {\n",
       "       'brunel' : {\n",
       "            exports: 'BrunelD3',\n",
       "            deps: ['d3', 'topojson'],\n",
       "            init: function() {\n",
       "               return {\n",
       "                 BrunelD3 : BrunelD3,\n",
       "                 BrunelData : BrunelData\n",
       "              }\n",
       "            }\n",
       "        },\n",
       "       'brunelControls' : {\n",
       "            exports: 'BrunelEventHandlers',\n",
       "            init: function() {\n",
       "               return {\n",
       "                 BrunelEventHandlers: BrunelEventHandlers,\n",
       "                 BrunelJQueryControlFactory: BrunelJQueryControlFactory\n",
       "              }\n",
       "            }\n",
       "        }\n",
       "\n",
       "    }\n",
       "\n",
       "});\n",
       "\n",
       "require([\"d3\"], function(d3) {\n",
       "    require([\"brunel\", \"brunelControls\"], function(brunel, brunelControls) {\n",
       "        function  BrunelVis(visId) {\n",
       "  \"use strict\";                                                                       // strict mode\n",
       "  var datasets = [],                                      // array of datasets for the original data\n",
       "      pre = function(d, i) { return d },                         // default pre-process does nothing\n",
       "      post = function(d, i) { return d },                       // default post-process does nothing\n",
       "      transitionTime = 200,                                        // transition time for animations\n",
       "      charts = [],                                                       // the charts in the system\n",
       "      vis = d3.select('#' + visId).attr('class', 'brunel');                     // the SVG container\n",
       "\n",
       "  BrunelD3.addDefinitions(vis);                                   // ensure standard symbols present\n",
       "\n",
       "  // Define chart #1 in the visualization //////////////////////////////////////////////////////////\n",
       "\n",
       "  charts[0] = function(parentNode, filterRows) {\n",
       "    var geom = BrunelD3.geometry(parentNode || vis.node(), 0, 0, 1, 1, 5, 49, 37, 93),\n",
       "      elements = [];                                              // array of elements in this chart\n",
       "\n",
       "    // Define groups for the chart parts ///////////////////////////////////////////////////////////\n",
       "\n",
       "    var chart =  vis.append('g').attr('class', 'chart1')\n",
       "      .attr('transform','translate(' + geom.chart_left + ',' + geom.chart_top + ')');\n",
       "    var overlay = chart.append('g').attr('class', 'element').attr('class', 'overlay');\n",
       "    var zoom = d3.zoom().scaleExtent([1/3,3]);\n",
       "    var zoomNode = overlay.append('rect').attr('class', 'overlay')\n",
       "      .attr('x', geom.inner_left).attr('y', geom.inner_top)\n",
       "      .attr('width', geom.inner_rawWidth).attr('height', geom.inner_rawHeight)\n",
       "      .style('cursor', 'move').call(zoom)\n",
       "      .node();\n",
       "    zoomNode.__zoom = d3.zoomIdentity;\n",
       "    chart.append('rect').attr('class', 'background').attr('width', geom.chart_right-geom.chart_left).attr('height', geom.chart_bottom-geom.chart_top);\n",
       "    var interior = chart.append('g').attr('class', 'interior zoomNone')\n",
       "      .attr('transform','translate(' + geom.inner_left + ',' + geom.inner_top + ')')\n",
       "      .attr('clip-path', 'url(#clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_inner)');\n",
       "    interior.append('rect').attr('class', 'inner').attr('width', geom.inner_width).attr('height', geom.inner_height);\n",
       "    var gridGroup = interior.append('g').attr('class', 'grid');\n",
       "    var axes = chart.append('g').attr('class', 'axis')\n",
       "      .attr('transform','translate(' + geom.inner_left + ',' + geom.inner_top + ')');\n",
       "    var legends = chart.append('g').attr('class', 'legend')\n",
       "      .attr('transform','translate(' + (geom.chart_right-geom.chart_left - 3) + ',' + 0 + ')');\n",
       "    vis.append('clipPath').attr('id', 'clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_inner').append('rect')\n",
       "      .attr('x', 0).attr('y', 0)\n",
       "      .attr('width', geom.inner_rawWidth+1).attr('height', geom.inner_rawHeight+1);\n",
       "\n",
       "    // Scales //////////////////////////////////////////////////////////////////////////////////////\n",
       "\n",
       "    var scale_x = d3.scaleTime().domain([new Date('2015-10-01'), new Date('2018-07-01')])\n",
       "      .range([0, geom.inner_width]);\n",
       "    var scale_inner = d3.scaleLinear().domain([0,1])\n",
       "      .range([-0.5, 0.5]);\n",
       "    var scale_y = d3.scaleLog().domain([0.1, 10000.001])\n",
       "      .range([geom.inner_height, 0]);\n",
       "    var base_scales = [scale_x, scale_y];                           // untransformed original scales\n",
       "\n",
       "    // Axes ////////////////////////////////////////////////////////////////////////////////////////\n",
       "\n",
       "    axes.append('g').attr('class', 'x axis')\n",
       "      .attr('transform','translate(0,' + geom.inner_rawHeight + ')')\n",
       "      .attr('clip-path', 'url(#clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_haxis)');\n",
       "    vis.append('clipPath').attr('id', 'clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_haxis').append('polyline')\n",
       "      .attr('points', '-1,-1000, -1,-1 -5,5, -1000,5, -100,1000, 10000,1000 10000,-1000');\n",
       "    axes.select('g.axis.x').append('text').attr('class', 'title').text('Date').style('text-anchor', 'middle')\n",
       "      .attr('x',geom.inner_rawWidth/2)\n",
       "      .attr('y', geom.inner_bottom - 2.0).attr('dy','-0.27em');\n",
       "    axes.append('g').attr('class', 'y axis')\n",
       "      .attr('clip-path', 'url(#clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_vaxis)');\n",
       "    vis.append('clipPath').attr('id', 'clip_visid42716746-e204-11e8-8ddb-002590fb6664_chart1_vaxis').append('polyline')\n",
       "      .attr('points', '-1000,-10000, 10000,-10000, 10000,' + (geom.inner_rawHeight+1) + ', -1,' + (geom.inner_rawHeight+1) + ', -1,' + (geom.inner_rawHeight+5) + ', -1000,' + (geom.inner_rawHeight+5) );\n",
       "    axes.select('g.axis.y').append('text').attr('class', 'title').text('PM10').style('text-anchor', 'middle')\n",
       "      .attr('x',-geom.inner_rawHeight/2)\n",
       "      .attr('y', 4-geom.inner_left).attr('dy', '0.7em').attr('transform', 'rotate(270)');\n",
       "\n",
       "    var axis_bottom = d3.axisBottom(scale_x).ticks(Math.min(10, Math.round(geom.inner_width / 99.0)));\n",
       "    var axis_left = d3.axisLeft(scale_y).ticks(Math.min(10, Math.round(geom.inner_width / 20)), ',');\n",
       "\n",
       "    function buildAxes(time) {\n",
       "      var axis_x = axes.select('g.axis.x');\n",
       "      BrunelD3.transition(axis_x, time).call(axis_bottom.scale(scale_x));\n",
       "      var axis_y = axes.select('g.axis.y');\n",
       "      BrunelD3.transition(axis_y, time).call(axis_left.scale(scale_y));\n",
       "    }\n",
       "    zoom.on('zoom', function(t, time) {\n",
       "        t = t ||BrunelD3.restrictZoom(d3.event.transform, geom, this);\n",
       "        scale_x = t.rescaleX(base_scales[0]);\n",
       "        scale_y = t.rescaleY(base_scales[1]);\n",
       "        zoomNode.__zoom = t;\n",
       "        interior.attr('class', 'interior ' + BrunelD3.zoomLabel(t.k));;\n",
       "        build(time || -1);\n",
       "    });\n",
       "\n",
       "    // Define element #1 ///////////////////////////////////////////////////////////////////////////\n",
       "\n",
       "    elements[0] = function() {\n",
       "      var original, processed,                           // data sets passed in and then transformed\n",
       "        element, data,                                 // brunel element information and brunel data\n",
       "        selection, merged;                                      // d3 selection and merged selection\n",
       "      var elementGroup = interior.append('g').attr('class', 'element1'),\n",
       "        main = elementGroup.append('g').attr('class', 'main'),\n",
       "        labels = BrunelD3.undoTransform(elementGroup.append('g').attr('class', 'labels').attr('aria-hidden', 'true'), elementGroup);\n",
       "\n",
       "      function makeData() {\n",
       "        original = datasets[0];\n",
       "        if (filterRows) original = original.retainRows(filterRows);\n",
       "        processed = pre(original, 0)\n",
       "          .filter('PM10 valid');\n",
       "        processed = post(processed, 0);\n",
       "        var f0 = processed.field('date'),\n",
       "          f1 = processed.field('PM10'),\n",
       "          f2 = processed.field('station'),\n",
       "          f3 = processed.field('#row'),\n",
       "          f4 = processed.field('#selection');\n",
       "        var keyFunc = function(d) { return f3.value(d) };\n",
       "        data = {\n",
       "          date:         function(d) { return f0.value(d.row) },\n",
       "          PM10:         function(d) { return f1.value(d.row) },\n",
       "          station:      function(d) { return f2.value(d.row) },\n",
       "          $row:         function(d) { return f3.value(d.row) },\n",
       "          $selection:   function(d) { return f4.value(d.row) },\n",
       "          date_f:       function(d) { return f0.valueFormatted(d.row) },\n",
       "          PM10_f:       function(d) { return f1.valueFormatted(d.row) },\n",
       "          station_f:    function(d) { return f2.valueFormatted(d.row) },\n",
       "          $row_f:       function(d) { return f3.valueFormatted(d.row) },\n",
       "          $selection_f: function(d) { return f4.valueFormatted(d.row) },\n",
       "          _split:       function(d) { return f2.value(d.row) },\n",
       "          _key:         keyFunc,\n",
       "          _rows:        BrunelD3.makeRowsWithKeys(keyFunc, processed.rowCount())\n",
       "        };\n",
       "      }\n",
       "      // Aesthetic Functions\n",
       "      var scale_color = d3.scaleOrdinal()\n",
       "        .domain(['CRS', 'HEBBAL', 'JAYANAGAR', 'KAVIKA', 'NIHMANS', 'SGHALLI', 'SILKBOARD'])\n",
       "        .range([ '#00538A', '#C10020', '#F4C800', '#007D34', '#803E75', '#FF6800', \n",
       "          '#817066', '#FFB300', '#F6768E', '#93AA00', '#53377A', '#FF8E00', '#B32851', \n",
       "          '#CEA262', '#FF7A5C', '#7F180D', '#593315', '#F13A13', '#232C16']);\n",
       "      var color = function(d) { return scale_color(data.station(d)) };\n",
       "      legends._legend = legends._legend || { title: ['Station'], \n",
       "        ticks: scale_color.domain()};\n",
       "      legends._legend.color = scale_color;\n",
       "\n",
       "      // Build element from data ///////////////////////////////////////////////////////////////////\n",
       "\n",
       "      function build(transitionMillis) {\n",
       "        element = elements[0];\n",
       "        var w = geom.default_point_size;\n",
       "        var x = function(d) { return scale_x(data.date(d))};\n",
       "        var h = geom.default_point_size;\n",
       "        var y = function(d) { return scale_y(data.PM10(d))};\n",
       "\n",
       "        // Define selection entry operations\n",
       "        function initialState(selection) {\n",
       "          selection\n",
       "            .attr('class', 'element point filled')\n",
       "            .style('pointer-events', 'none')\n",
       "        }\n",
       "\n",
       "        // Define selection update operations on merged data\n",
       "        function updateState(selection) {\n",
       "          selection\n",
       "            .attr('cx',function(d) { return scale_x(data.date(d))})\n",
       "            .attr('cy',function(d) { return scale_y(data.PM10(d))})\n",
       "            .attr('r',geom.default_point_size / 2)\n",
       "            .filter(BrunelD3.hasData)                     // following only performed for data items\n",
       "            .style('fill', color);\n",
       "        }\n",
       "\n",
       "        // Define labeling for the selection\n",
       "        function label(selection, transitionMillis) {\n",
       "        }\n",
       "        // Create selections, set the initial state and transition updates\n",
       "        selection = main.selectAll('.element').data(data._rows, function(d) { return d.key });\n",
       "        var added = selection.enter().append('circle');\n",
       "        merged = selection.merge(added);\n",
       "        initialState(added);\n",
       "        selection.filter(BrunelD3.hasData)\n",
       "          .classed('selected', BrunelD3.isSelected(data))\n",
       "          .filter(BrunelD3.isSelected(data)).raise();\n",
       "        updateState(BrunelD3.transition(merged, transitionMillis));\n",
       "\n",
       "        BrunelD3.transition(selection.exit(), transitionMillis/3)\n",
       "          .style('opacity', 0.5).each( function() {\n",
       "            this.remove(); BrunelD3.removeLabels(this); \n",
       "        });\n",
       "      }\n",
       "\n",
       "      return {\n",
       "        data:           function() { return processed },\n",
       "        original:       function() { return original },\n",
       "        internal:       function() { return data },\n",
       "        selection:      function() { return merged },\n",
       "        makeData:       makeData,\n",
       "        build:          build,\n",
       "        chart:          function() { return charts[0] },\n",
       "        group:          function() { return elementGroup },\n",
       "        fields: {\n",
       "          x:            ['date'],\n",
       "          y:            ['PM10'],\n",
       "          key:          ['#row'],\n",
       "          color:        ['station']\n",
       "        }\n",
       "      };\n",
       "    }();\n",
       "\n",
       "    function build(time, noData) {\n",
       "      var first = elements[0].data() == null;\n",
       "      if (first) time = 0;                                           // no transition for first call\n",
       "      buildAxes(time);\n",
       "      if ((first || time > -1) && !noData) {\n",
       "        elements[0].makeData();\n",
       "        BrunelD3.addLegend(legends, legends._legend);\n",
       "      }\n",
       "      elements[0].build(time);\n",
       "    }\n",
       "\n",
       "    // Expose the following components of the chart\n",
       "    return {\n",
       "      elements : elements,\n",
       "      interior : interior,\n",
       "      scales: {x:scale_x, y:scale_y},\n",
       "      zoom: function(params, time) {\n",
       "          if (params) zoom.on('zoom').call(zoomNode, params, time);\n",
       "          return d3.zoomTransform(zoomNode);\n",
       "      },\n",
       "      build : build\n",
       "    };\n",
       "    }();\n",
       "\n",
       "  function setData(rowData, i) { datasets[i||0] = BrunelD3.makeData(rowData) }\n",
       "  function updateAll(time) { charts.forEach(function(x) {x.build(time || 0)}) }\n",
       "  function buildAll() {\n",
       "    for (var i=0;i<arguments.length;i++) setData(arguments[i], i);\n",
       "    updateAll(transitionTime);\n",
       "  }\n",
       "\n",
       "  return {\n",
       "    dataPreProcess:     function(f) { if (f) pre = f; return pre },\n",
       "    dataPostProcess:    function(f) { if (f) post = f; return post },\n",
       "    data:               function(d,i) { if (d) setData(d,i); return datasets[i||0] },\n",
       "    visId:              visId,\n",
       "    build:              buildAll,\n",
       "    rebuild:            updateAll,\n",
       "    charts:             charts\n",
       "  }\n",
       "}\n",
       "\n",
       "// Data Tables /////////////////////////////////////////////////////////////////////////////////////\n",
       "\n",
       "var table1 = {\n",
       "   summarized: false,\n",
       "   names: ['date', 'PM10', 'station'], \n",
       "   options: ['date-YearMonthDay', 'numeric', 'string'], \n",
       "   rows: [['2017-05-01', null, 'BTM'], ['2017-05-01', null, 'BTM'], ['2017-05-01', null, 'BTM'],\n",
       "  ['2017-05-01', null, 'BTM'], ['2017-05-02', null, 'BTM'], ['2017-05-02', null, 'BTM'],\n",
       "  ['2017-05-02', null, 'BTM'], ['2017-05-02', null, 'BTM'], ['2017-05-02', null, 'BTM'],\n",
       "  ['2017-05-02', null, 'BTM'], ['2017-05-03', null, 'BTM'], ['2017-05-03', null, 'BTM'],\n",
       "  ['2017-05-05', null, 'BTM'], ['2017-05-05', null, 'BTM'], ['2017-05-08', null, 'BTM'],\n",
       "  ['2017-05-08', null, 'BTM'], ['2017-05-11', null, 'BTM'], ['2017-05-11', null, 'BTM'],\n",
       "  ['2017-05-11', null, 'BTM'], ['2017-05-11', null, 'BTM'], ['2017-05-12', null, 'BTM'],\n",
       "  ['2017-05-12', null, 'BTM'], ['2017-05-12', null, 'BTM'], ['2017-05-12', null, 'BTM'],\n",
       "  ['2017-05-13', null, 'BTM'], ['2017-05-13', null, 'BTM'], ['2017-05-13', null, 'BTM'],\n",
       "  ['2017-05-13', null, 'BTM'], ['2017-05-13', null, 'BTM'], ['2017-05-14', null, 'BTM'],\n",
       "  ['2017-05-14', null, 'BTM'], ['2017-05-14', null, 'BTM'], ['2017-05-14', null, 'BTM'],\n",
       "  ['2017-05-14', null, 'BTM'], ['2017-05-14', null, 'BTM'], ['2017-05-15', null, 'BTM'],\n",
       "  ['2017-05-15', null, 'BTM'], ['2017-05-15', null, 'BTM'], ['2017-05-15', null, 'BTM'],\n",
       "  ['2017-05-15', null, 'BTM'], ['2017-05-15', null, 'BTM'], ['2017-05-16', null, 'BTM'],\n",
       "  ['2017-05-16', null, 'BTM'], ['2017-05-16', null, 'BTM'], ['2017-05-16', null, 'BTM'],\n",
       "  ['2017-05-16', null, 'BTM'], ['2017-05-16', null, 'BTM'], ['2017-05-17', null, 'BTM'],\n",
       "  ['2017-05-17', null, 'BTM'], ['2017-05-17', null, 'BTM'], ['2017-05-17', null, 'BTM'],\n",
       "  ['2017-05-17', null, 'BTM'], ['2017-05-17', null, 'BTM'], ['2017-05-18', null, 'BTM'],\n",
       "  ['2017-05-18', null, 'BTM'], ['2017-05-18', null, 'BTM'], ['2017-05-18', null, 'BTM'],\n",
       "  ['2017-05-18', null, 'BTM'], ['2017-05-18', null, 'BTM'], ['2017-05-19', null, 'BTM'],\n",
       "  ['2017-05-19', null, 'BTM'], ['2017-05-19', null, 'BTM'], ['2017-05-19', null, 'BTM'],\n",
       "  ['2017-05-19', null, 'BTM'], ['2017-05-19', null, 'BTM'], ['2017-05-20', null, 'BTM'],\n",
       "  ['2017-05-20', null, 'BTM'], ['2017-05-20', null, 'BTM'], ['2017-05-20', null, 'BTM'],\n",
       "  ['2017-05-20', null, 'BTM'], ['2017-05-20', null, 'BTM'], ['2017-05-21', null, 'BTM'],\n",
       "  ['2017-05-21', null, 'BTM'], ['2017-05-21', null, 'BTM'], ['2017-05-21', null, 'BTM'],\n",
       "  ['2017-05-21', null, 'BTM'], ['2017-05-21', null, 'BTM'], ['2017-05-22', null, 'BTM'],\n",
       "  ['2017-05-22', null, 'BTM'], ['2017-05-22', null, 'BTM'], ['2017-05-22', null, 'BTM'],\n",
       "  ['2017-05-22', null, 'BTM'], ['2017-05-22', null, 'BTM'], ['2017-05-23', null, 'BTM'],\n",
       "  ['2017-05-23', null, 'BTM'], ['2017-05-23', null, 'BTM'], ['2017-05-23', null, 'BTM'],\n",
       "  ['2017-05-23', null, 'BTM'], ['2017-05-23', null, 'BTM'], ['2017-05-24', null, 'BTM'],\n",
       "  ['2017-05-24', null, 'BTM'], ['2017-05-24', null, 'BTM'], ['2017-05-24', null, 'BTM'],\n",
       "  ['2017-05-24', null, 'BTM'], ['2017-05-24', null, 'BTM'], ['2017-05-25', null, 'BTM'],\n",
       "  ['2017-05-25', null, 'BTM'], ['2017-05-25', null, 'BTM'], ['2017-05-25', null, 'BTM'],\n",
       "  ['2017-05-25', null, 'BTM'], ['2017-05-25', null, 'BTM'], ['2017-05-26', null, 'BTM'],\n",
       "  ['2017-05-26', null, 'BTM'], ['2017-05-26', null, 'BTM'], ['2017-05-26', null, 'BTM'],\n",
       "  ['2017-05-27', null, 'BTM'], ['2017-05-27', null, 'BTM'], ['2017-05-28', null, 'BTM'],\n",
       "  ['2017-05-28', null, 'BTM'], ['2017-05-28', null, 'BTM'], ['2017-05-28', null, 'BTM'],\n",
       "  ['2017-05-29', null, 'BTM'], ['2017-05-29', null, 'BTM'], ['2017-05-29', null, 'BTM'],\n",
       "  ['2017-05-29', null, 'BTM'], ['2017-05-29', null, 'BTM'], ['2017-05-29', null, 'BTM'],\n",
       "  ['2017-05-30', null, 'BTM'], ['2017-05-30', null, 'BTM'], ['2017-05-30', null, 'BTM'],\n",
       "  ['2017-05-30', null, 'BTM'], ['2017-05-30', null, 'BTM'], ['2017-05-30', null, 'BTM'],\n",
       "  ['2017-05-31', null, 'BTM'], ['2017-05-31', null, 'BTM'], ['2017-05-31', null, 'BTM'],\n",
       "  ['2017-05-31', null, 'BTM'], ['2017-05-31', null, 'BTM'], ['2017-05-31', null, 'BTM'],\n",
       "  ['2017-06-01', null, 'BTM'], ['2017-06-01', null, 'BTM'], ['2017-06-01', null, 'BTM'],\n",
       "  ['2017-06-01', null, 'BTM'], ['2017-06-01', null, 'BTM'], ['2017-06-01', null, 'BTM'],\n",
       "  ['2017-06-02', null, 'BTM'], ['2017-06-02', null, 'BTM'], ['2017-06-02', null, 'BTM'],\n",
       "  ['2017-06-02', null, 'BTM'], ['2017-06-02', null, 'BTM'], ['2017-06-02', null, 'BTM'],\n",
       "  ['2017-06-03', null, 'BTM'], ['2017-06-03', null, 'BTM'], ['2017-06-03', null, 'BTM'],\n",
       "  ['2017-06-03', null, 'BTM'], ['2017-06-03', null, 'BTM'], ['2017-06-03', null, 'BTM'],\n",
       "  ['2017-06-04', null, 'BTM'], ['2017-06-04', null, 'BTM'], ['2017-06-04', null, 'BTM'],\n",
       "  ['2017-06-04', null, 'BTM'], ['2017-06-04', null, 'BTM'], ['2017-06-04', null, 'BTM'],\n",
       "  ['2017-06-05', null, 'BTM'], ['2017-06-05', null, 'BTM'], ['2017-06-05', null, 'BTM'],\n",
       "  ['2017-06-05', null, 'BTM'], ['2017-06-05', null, 'BTM'], ['2017-06-05', null, 'BTM'],\n",
       "  ['2017-06-06', null, 'BTM'], ['2017-06-06', null, 'BTM'], ['2017-06-06', null, 'BTM'],\n",
       "  ['2017-06-06', null, 'BTM'], ['2017-06-06', null, 'BTM'], ['2017-06-06', null, 'BTM'],\n",
       "  ['2017-06-07', null, 'BTM'], ['2017-06-07', null, 'BTM'], ['2017-06-07', null, 'BTM'],\n",
       "  ['2017-06-07', null, 'BTM'], ['2017-06-08', null, 'BTM'], ['2017-06-08', null, 'BTM'],\n",
       "  ['2017-06-08', null, 'BTM'], ['2017-06-08', null, 'BTM'], ['2017-06-08', null, 'BTM'],\n",
       "  ['2017-06-09', null, 'BTM'], ['2017-06-09', null, 'BTM'], ['2017-06-09', null, 'BTM'],\n",
       "  ['2017-06-09', null, 'BTM'], ['2017-06-09', null, 'BTM'], ['2017-06-09', null, 'BTM'],\n",
       "  ['2017-06-10', null, 'BTM'], ['2017-06-10', null, 'BTM'], ['2017-06-10', null, 'BTM'],\n",
       "  ['2017-06-10', null, 'BTM'], ['2017-06-10', null, 'BTM'], ['2017-06-10', null, 'BTM'],\n",
       "  ['2017-06-11', null, 'BTM'], ['2017-06-11', null, 'BTM'], ['2017-06-11', null, 'BTM'],\n",
       "  ['2017-06-11', null, 'BTM'], ['2017-06-11', null, 'BTM'], ['2017-06-11', null, 'BTM'],\n",
       "  ['2017-06-12', null, 'BTM'], ['2017-06-12', null, 'BTM'], ['2017-06-12', null, 'BTM'],\n",
       "  ['2017-06-12', null, 'BTM'], ['2017-06-12', null, 'BTM'], ['2017-06-12', null, 'BTM'],\n",
       "  ['2017-06-13', null, 'BTM'], ['2017-06-13', null, 'BTM'], ['2017-06-13', null, 'BTM'],\n",
       "  ['2017-06-13', null, 'BTM'], ['2017-06-13', null, 'BTM'], ['2017-06-13', null, 'BTM'],\n",
       "  ['2017-06-14', null, 'BTM'], ['2017-06-14', null, 'BTM'], ['2017-06-14', null, 'BTM'],\n",
       "  ['2017-06-14', null, 'BTM'], ['2017-06-14', null, 'BTM'], ['2017-06-14', null, 'BTM'],\n",
       "  ['2017-06-15', null, 'BTM'], ['2017-06-15', null, 'BTM'], ['2017-06-15', null, 'BTM'],\n",
       "  ['2017-06-15', null, 'BTM'], ['2017-06-15', null, 'BTM'], ['2017-06-15', null, 'BTM'],\n",
       "  ['2017-06-16', null, 'BTM'], ['2017-06-16', null, 'BTM'], ['2017-06-16', null, 'BTM'],\n",
       "  ['2017-06-16', null, 'BTM'], ['2017-06-16', null, 'BTM'], ['2017-06-16', null, 'BTM'],\n",
       "  ['2017-06-17', null, 'BTM'], ['2017-06-17', null, 'BTM'], ['2017-06-17', null, 'BTM'],\n",
       "  ['2017-06-17', null, 'BTM'], ['2017-06-17', null, 'BTM'], ['2017-06-17', null, 'BTM'],\n",
       "  ['2017-06-18', null, 'BTM'], ['2017-06-18', null, 'BTM'], ['2017-06-18', null, 'BTM'],\n",
       "  ['2017-06-18', null, 'BTM'], ['2017-06-18', null, 'BTM'], ['2017-06-18', null, 'BTM'],\n",
       "  ['2017-06-19', null, 'BTM'], ['2017-06-19', null, 'BTM'], ['2017-06-19', null, 'BTM'],\n",
       "  ['2017-06-19', null, 'BTM'], ['2017-06-19', null, 'BTM'], ['2017-06-19', null, 'BTM'],\n",
       "  ['2017-06-20', null, 'BTM'], ['2017-06-20', null, 'BTM'], ['2017-06-20', null, 'BTM'],\n",
       "  ['2017-06-21', null, 'BTM'], ['2017-06-21', null, 'BTM'], ['2017-06-21', null, 'BTM'],\n",
       "  ['2017-06-21', null, 'BTM'], ['2017-06-21', null, 'BTM'], ['2017-06-22', null, 'BTM'],\n",
       "  ['2017-06-22', null, 'BTM'], ['2017-06-22', null, 'BTM'], ['2017-06-22', null, 'BTM'],\n",
       "  ['2017-06-22', null, 'BTM'], ['2017-06-22', null, 'BTM'], ['2017-06-23', null, 'BTM'],\n",
       "  ['2017-06-23', null, 'BTM'], ['2017-06-23', null, 'BTM'], ['2017-06-23', null, 'BTM'],\n",
       "  ['2017-06-23', null, 'BTM'], ['2017-06-23', null, 'BTM'], ['2017-06-24', null, 'BTM'],\n",
       "  ['2017-06-24', null, 'BTM'], ['2017-06-24', null, 'BTM'], ['2017-06-24', null, 'BTM'],\n",
       "  ['2017-06-24', null, 'BTM'], ['2017-06-24', null, 'BTM'], ['2017-06-25', null, 'BTM'],\n",
       "  ['2017-06-25', null, 'BTM'], ['2017-06-25', null, 'BTM'], ['2017-06-25', null, 'BTM'],\n",
       "  ['2017-06-25', null, 'BTM'], ['2017-06-25', null, 'BTM'], ['2017-06-26', null, 'BTM'],\n",
       "  ['2017-06-26', null, 'BTM'], ['2017-06-26', null, 'BTM'], ['2017-06-26', null, 'BTM'],\n",
       "  ['2017-06-26', null, 'BTM'], ['2017-06-26', null, 'BTM'], ['2017-06-27', null, 'BTM'],\n",
       "  ['2017-06-27', null, 'BTM'], ['2017-06-27', null, 'BTM'], ['2017-06-27', null, 'BTM'],\n",
       "  ['2017-06-27', null, 'BTM'], ['2017-06-27', null, 'BTM'], ['2017-06-28', null, 'BTM'],\n",
       "  ['2017-06-28', null, 'BTM'], ['2017-06-28', null, 'BTM'], ['2017-06-29', null, 'BTM'],\n",
       "  ['2017-06-29', null, 'BTM'], ['2017-06-29', null, 'BTM'], ['2017-06-29', null, 'BTM'],\n",
       "  ['2017-06-29', null, 'BTM'], ['2017-06-30', null, 'BTM'], ['2017-06-30', null, 'BTM'],\n",
       "  ['2017-06-30', null, 'BTM'], ['2017-06-30', null, 'BTM'], ['2017-06-30', null, 'BTM'],\n",
       "  ['2017-06-30', null, 'BTM'], ['2017-07-01', null, 'BTM'], ['2017-07-01', null, 'BTM'],\n",
       "  ['2017-07-01', null, 'BTM'], ['2017-07-01', null, 'BTM'], ['2017-07-01', null, 'BTM'],\n",
       "  ['2017-07-01', null, 'BTM'], ['2017-07-02', null, 'BTM'], ['2017-07-02', null, 'BTM'],\n",
       "  ['2017-07-02', null, 'BTM'], ['2017-07-02', null, 'BTM'], ['2017-07-02', null, 'BTM'],\n",
       "  ['2017-07-02', null, 'BTM'], ['2017-07-03', null, 'BTM'], ['2017-07-03', null, 'BTM'],\n",
       "  ['2017-07-03', null, 'BTM'], ['2017-07-03', null, 'BTM'], ['2017-07-03', null, 'BTM'],\n",
       "  ['2017-07-03', null, 'BTM'], ['2017-07-04', null, 'BTM'], ['2017-07-04', null, 'BTM'],\n",
       "  ['2017-07-04', null, 'BTM'], ['2017-07-04', null, 'BTM'], ['2017-07-04', null, 'BTM'],\n",
       "  ['2017-07-04', null, 'BTM'], ['2017-07-05', null, 'BTM'], ['2017-07-05', null, 'BTM'],\n",
       "  ['2017-07-05', null, 'BTM'], ['2017-07-05', null, 'BTM'], ['2017-07-05', null, 'BTM'],\n",
       "  ['2017-07-05', null, 'BTM'], ['2017-07-06', null, 'BTM'], ['2017-07-06', null, 'BTM'],\n",
       "  ['2017-07-06', null, 'BTM'], ['2017-07-06', null, 'BTM'], ['2017-07-06', null, 'BTM'],\n",
       "  ['2017-07-06', null, 'BTM'], ['2017-07-07', null, 'BTM'], ['2017-07-07', null, 'BTM'],\n",
       "  ['2017-07-07', null, 'BTM'], ['2017-07-07', null, 'BTM'], ['2017-07-07', null, 'BTM'],\n",
       "  ['2017-07-07', null, 'BTM'], ['2017-07-08', null, 'BTM'], ['2017-07-08', null, 'BTM'],\n",
       "  ['2017-07-08', null, 'BTM'], ['2017-07-08', null, 'BTM'], ['2017-07-08', null, 'BTM'],\n",
       "  ['2017-07-08', null, 'BTM'], ['2017-07-09', null, 'BTM'], ['2017-07-09', null, 'BTM'],\n",
       "  ['2017-07-09', null, 'BTM'], ['2017-07-09', null, 'BTM'], ['2017-07-09', null, 'BTM'],\n",
       "  ['2017-07-09', null, 'BTM'], ['2017-07-10', null, 'BTM'], ['2017-07-10', null, 'BTM'],\n",
       "  ['2017-07-10', null, 'BTM'], ['2017-07-10', null, 'BTM'], ['2017-07-11', null, 'BTM'],\n",
       "  ['2017-07-11', null, 'BTM'], ['2017-07-11', null, 'BTM'], ['2017-07-11', null, 'BTM'],\n",
       "  ['2017-07-12', null, 'BTM'], ['2017-07-12', null, 'BTM'], ['2017-07-12', null, 'BTM'],\n",
       "  ['2017-07-12', null, 'BTM'], ['2017-07-12', null, 'BTM'], ['2017-07-12', null, 'BTM'],\n",
       "  ['2017-07-13', null, 'BTM'], ['2017-07-13', null, 'BTM'], ['2017-07-13', null, 'BTM'],\n",
       "  ['2017-07-13', null, 'BTM'], ['2017-07-13', null, 'BTM'], ['2017-07-14', null, 'BTM'],\n",
       "  ['2017-07-14', null, 'BTM'], ['2017-07-14', null, 'BTM'], ['2017-07-14', null, 'BTM'],\n",
       "  ['2017-07-14', null, 'BTM'], ['2017-07-14', null, 'BTM'], ['2017-07-15', null, 'BTM'],\n",
       "  ['2017-07-15', null, 'BTM'], ['2017-07-15', null, 'BTM'], ['2017-07-15', null, 'BTM'],\n",
       "  ['2017-07-15', null, 'BTM'], ['2017-07-15', null, 'BTM'], ['2017-07-16', null, 'BTM'],\n",
       "  ['2017-07-16', null, 'BTM'], ['2017-07-16', null, 'BTM'], ['2017-07-16', null, 'BTM'],\n",
       "  ['2017-07-16', null, 'BTM'], ['2017-07-16', null, 'BTM'], ['2017-07-17', null, 'BTM'],\n",
       "  ['2017-07-17', null, 'BTM'], ['2017-07-17', null, 'BTM'], ['2017-07-17', null, 'BTM'],\n",
       "  ['2017-07-17', null, 'BTM'], ['2017-07-17', null, 'BTM'], ['2017-07-18', null, 'BTM'],\n",
       "  ['2017-07-18', null, 'BTM'], ['2017-07-18', null, 'BTM'], ['2017-07-18', null, 'BTM'],\n",
       "  ['2017-07-18', null, 'BTM'], ['2017-07-18', null, 'BTM'], ['2017-07-19', null, 'BTM'],\n",
       "  ['2017-07-19', null, 'BTM'], ['2017-07-19', null, 'BTM'], ['2017-07-19', null, 'BTM'],\n",
       "  ['2017-07-19', null, 'BTM'], ['2017-07-19', null, 'BTM'], ['2017-07-20', null, 'BTM'],\n",
       "  ['2017-07-20', null, 'BTM'], ['2017-07-20', null, 'BTM'], ['2017-07-20', null, 'BTM'],\n",
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       "  ['2016-06-30', 1.47, 'SGHALLI'], ['2016-06-30', 4.73, 'SGHALLI'], ['2016-06-30', 34.16, 'SGHALLI'],\n",
       "  ['2016-06-30', 43.39, 'SGHALLI'], ['2016-06-30', null, 'SGHALLI'], ['2016-07-01', null, 'SGHALLI'],\n",
       "  ['2016-07-01', 1.13, 'SGHALLI'], ['2016-07-01', 2.57, 'SGHALLI'], ['2016-07-01', 10.22, 'SGHALLI'],\n",
       "  ['2016-07-01', 8.66, 'SGHALLI'], ['2016-07-01', 4.54, 'SGHALLI'], ['2016-07-02', 4.42, 'SGHALLI'],\n",
       "  ['2016-07-02', 3.15, 'SGHALLI'], ['2016-07-02', 5.87, 'SGHALLI'], ['2016-07-02', 16.43, 'SGHALLI'],\n",
       "  ['2016-07-02', 21.6, 'SGHALLI'], ['2016-07-02', 8.69, 'SGHALLI'], ['2016-07-03', 6.27, 'SGHALLI'],\n",
       "  ['2016-07-03', 2.21, 'SGHALLI'], ['2016-07-03', 4.15, 'SGHALLI'], ['2016-07-03', 3.38, 'SGHALLI'],\n",
       "  ['2016-07-03', 3.57, 'SGHALLI'], ['2016-07-03', 6.02, 'SGHALLI'], ['2016-07-04', 2.95, 'SGHALLI'],\n",
       "  ['2016-07-04', 1.08, 'SGHALLI'], ['2016-07-04', null, 'SGHALLI'], ['2016-07-04', null, 'SGHALLI'],\n",
       "  ['2016-07-04', 9.39, 'SGHALLI'], ['2016-07-04', 7.85, 'SGHALLI'], ['2016-07-05', 2.96, 'SGHALLI'],\n",
       "  ['2016-07-05', 1.4, 'SGHALLI'], ['2016-07-05', 2.05, 'SGHALLI'], ['2016-07-05', 1.88, 'SGHALLI'],\n",
       "  ['2016-07-05', 2.59, 'SGHALLI'], ['2016-07-05', 4, 'SGHALLI'], ['2016-07-06', 4.18, 'SGHALLI'],\n",
       "  ['2016-07-06', 1.9, 'SGHALLI'], ['2016-07-06', 3.72, 'SGHALLI'], ['2016-07-06', 21.95, 'SGHALLI'],\n",
       "  ['2016-07-06', 19.17, 'SGHALLI'], ['2016-07-07', 2.25, 'SGHALLI'], ['2016-07-07', 1.98, 'SGHALLI'],\n",
       "  ['2016-07-07', 31.81, 'SGHALLI'], ['2016-07-07', 82.61, 'SGHALLI'],\n",
       "  ['2016-07-07', 23.83, 'SGHALLI'], ['2016-07-07', 26.07, 'SGHALLI'],\n",
       "  ['2016-07-08', 17.6, 'SGHALLI'], ['2016-07-08', 8.42, 'SGHALLI'], ['2016-07-08', 20.55, 'SGHALLI'],\n",
       "  ['2016-07-08', 38.78, 'SGHALLI'], ['2016-07-08', 39.12, 'SGHALLI'],\n",
       "  ['2016-07-08', 35.61, 'SGHALLI'], ['2016-07-09', 34.14, 'SGHALLI'],\n",
       "  ['2016-07-09', 30.12, 'SGHALLI'], ['2016-07-09', 38.33, 'SGHALLI'],\n",
       "  ['2016-07-09', 35.59, 'SGHALLI'], ['2016-07-09', 43.78, 'SGHALLI'],\n",
       "  ['2016-07-09', 29.98, 'SGHALLI'], ['2016-07-10', 20.12, 'SGHALLI'],\n",
       "  ['2016-07-10', 18.01, 'SGHALLI'], ['2016-07-10', 22.57, 'SGHALLI'],\n",
       "  ['2016-07-10', 51.8, 'SGHALLI'], ['2016-07-10', 40.1, 'SGHALLI'], ['2016-07-11', 28, 'SGHALLI'],\n",
       "  ['2016-07-11', 23.56, 'SGHALLI'], ['2016-07-11', 39.67, 'SGHALLI'],\n",
       "  ['2016-07-11', 68.02, 'SGHALLI'], ['2016-07-11', 68.43, 'SGHALLI'],\n",
       "  ['2016-07-11', 48.04, 'SGHALLI'], ['2016-07-12', 29.22, 'SGHALLI'],\n",
       "  ['2016-07-12', 28.76, 'SGHALLI'], ['2016-07-12', 41.06, 'SGHALLI'],\n",
       "  ['2016-07-12', 59.37, 'SGHALLI'], ['2016-07-12', 55.56, 'SGHALLI'],\n",
       "  ['2016-07-12', 34.43, 'SGHALLI'], ['2016-07-13', 25.76, 'SGHALLI'],\n",
       "  ['2016-07-13', 23.36, 'SGHALLI'], ['2016-07-13', 55.82, 'SGHALLI'],\n",
       "  ['2016-07-13', 53.53, 'SGHALLI'], ['2016-07-13', 54.39, 'SGHALLI'],\n",
       "  ['2016-07-13', 41.47, 'SGHALLI'], ['2016-07-14', 27.91, 'SGHALLI'],\n",
       "  ['2016-07-14', 27.32, 'SGHALLI'], ['2016-07-14', 46.88, 'SGHALLI'],\n",
       "  ['2016-07-14', 58.55, 'SGHALLI'], ['2016-07-14', 50.05, 'SGHALLI'],\n",
       "  ['2016-07-14', 49.07, 'SGHALLI'], ['2016-07-15', 31.67, 'SGHALLI'],\n",
       "  ['2016-07-15', 30.48, 'SGHALLI'], ['2016-07-15', 44.01, 'SGHALLI'],\n",
       "  ['2016-07-15', 45.31, 'SGHALLI'], ['2016-07-15', 62.89, 'SGHALLI'],\n",
       "  ['2016-07-17', 25.69, 'SGHALLI'], ['2016-07-18', 18.33, 'SGHALLI'],\n",
       "  ['2016-07-18', 14.48, 'SGHALLI'], ['2016-07-18', 21.36, 'SGHALLI'],\n",
       "  ['2016-07-18', 35.83, 'SGHALLI'], ['2016-07-18', 30.31, 'SGHALLI'],\n",
       "  ['2016-07-19', 21.16, 'SGHALLI'], ['2016-07-19', 22.78, 'SGHALLI'],\n",
       "  ['2016-07-19', 32.85, 'SGHALLI'], ['2016-07-19', 32.2, 'SGHALLI'],\n",
       "  ['2016-07-20', 31.25, 'SGHALLI'], ['2016-07-20', 27.32, 'SGHALLI'],\n",
       "  ['2016-07-21', 33.13, 'SGHALLI'], ['2016-07-22', 34.47, 'SGHALLI'],\n",
       "  ['2016-07-22', 34.32, 'SGHALLI'], ['2016-07-22', 39.87, 'SGHALLI'],\n",
       "  ['2016-07-23', 25.16, 'SGHALLI'], ['2016-07-23', 27.13, 'SGHALLI'],\n",
       "  ['2016-07-23', 35.47, 'SGHALLI'], ['2016-07-23', 43.46, 'SGHALLI'],\n",
       "  ['2016-08-01', 39.85, 'SGHALLI'], ['2016-08-01', 41.65, 'SGHALLI'],\n",
       "  ['2016-08-02', 42.01, 'SGHALLI'], ['2016-08-02', 36.69, 'SGHALLI'],\n",
       "  ['2016-08-05', 34.32, 'SGHALLI'], ['2016-08-11', 55.02, 'SGHALLI'],\n",
       "  ['2016-08-11', 51.37, 'SGHALLI'], ['2016-08-17', 27.3, 'SGHALLI'],\n",
       "  ['2016-08-17', 38.06, 'SGHALLI'], ['2016-08-18', 32.48, 'SGHALLI'],\n",
       "  ['2016-08-18', 26.34, 'SGHALLI'], ['2016-08-18', 29.86, 'SGHALLI'],\n",
       "  ['2016-08-18', 33.52, 'SGHALLI'], ['2016-08-19', 27.3, 'SGHALLI'],\n",
       "  ['2016-08-19', 26.53, 'SGHALLI'], ['2016-08-19', 34.91, 'SGHALLI'],\n",
       "  ['2016-08-19', 27.08, 'SGHALLI'], ['2016-08-19', 31.04, 'SGHALLI'],\n",
       "  ['2016-08-19', 36.26, 'SGHALLI'], ['2016-08-20', 25.09, 'SGHALLI'],\n",
       "  ['2016-08-20', 28.64, 'SGHALLI'], ['2016-08-20', 43.31, 'SGHALLI'],\n",
       "  ['2016-08-20', 33.2, 'SGHALLI'], ['2016-08-20', 43.43, 'SGHALLI'],\n",
       "  ['2016-08-20', 42.54, 'SGHALLI'], ['2016-08-21', 28.98, 'SGHALLI'],\n",
       "  ['2016-08-21', 33.48, 'SGHALLI'], ['2016-08-21', 38.7, 'SGHALLI'],\n",
       "  ['2016-08-21', 44.24, 'SGHALLI'], ['2016-08-21', 44.43, 'SGHALLI'],\n",
       "  ['2016-08-21', 33.93, 'SGHALLI'], ['2016-08-22', 22.71, 'SGHALLI'],\n",
       "  ['2016-08-22', 30.04, 'SGHALLI'], ['2016-08-22', 40.49, 'SGHALLI'],\n",
       "  ['2016-08-22', 36.36, 'SGHALLI'], ['2016-08-22', 36.9, 'SGHALLI'],\n",
       "  ['2016-08-22', 36.93, 'SGHALLI'], ['2016-08-23', null, 'SGHALLI'], ['2016-08-23', null, 'SGHALLI'],\n",
       "  ['2016-08-23', 28.55, 'SGHALLI'], ['2016-08-23', 42.26, 'SGHALLI'],\n",
       "  ['2016-08-23', 37.47, 'SGHALLI'], ['2016-08-24', 27.67, 'SGHALLI'],\n",
       "  ['2016-08-24', 23.34, 'SGHALLI'], ['2016-08-24', 31.33, 'SGHALLI'],\n",
       "  ['2016-08-24', 27.06, 'SGHALLI'], ['2016-08-24', 26.66, 'SGHALLI'],\n",
       "  ['2016-08-24', 40.54, 'SGHALLI'], ['2016-08-25', 31.56, 'SGHALLI'],\n",
       "  ['2016-08-25', 26.88, 'SGHALLI'], ['2016-08-25', 33.9, 'SGHALLI'],\n",
       "  ['2016-08-25', 32.13, 'SGHALLI'], ['2016-08-25', 32.01, 'SGHALLI'],\n",
       "  ['2016-08-25', 25.5, 'SGHALLI'], ['2016-08-26', 22.14, 'SGHALLI'],\n",
       "  ['2016-08-26', 20.76, 'SGHALLI'], ['2016-08-26', 30.38, 'SGHALLI'],\n",
       "  ['2016-08-26', 30.12, 'SGHALLI'], ['2016-08-26', 38.73, 'SGHALLI'],\n",
       "  ['2016-08-26', 39.58, 'SGHALLI'], ['2016-08-27', 25.09, 'SGHALLI'],\n",
       "  ['2016-08-27', 20.16, 'SGHALLI'], ['2016-08-27', 29.37, 'SGHALLI'],\n",
       "  ['2016-08-27', null, 'SGHALLI'], ['2016-08-27', 33.71, 'SGHALLI'],\n",
       "  ['2016-08-28', 25.65, 'SGHALLI'], ['2016-08-28', 22.6, 'SGHALLI'], ['2016-08-28', 32.3, 'SGHALLI'],\n",
       "  ['2016-08-28', null, 'SGHALLI'], ['2016-08-28', null, 'SGHALLI'], ['2016-08-28', 30.99, 'SGHALLI'],\n",
       "  ['2016-08-29', 24.36, 'SGHALLI'], ['2016-08-29', 21.53, 'SGHALLI'],\n",
       "  ['2016-08-29', 31.51, 'SGHALLI'], ['2016-08-29', 31.83, 'SGHALLI'],\n",
       "  ['2016-08-30', 27.64, 'SGHALLI'], ['2016-08-30', 29.47, 'SGHALLI'],\n",
       "  ['2016-08-30', 33.1, 'SGHALLI'], ['2016-08-30', 29.4, 'SGHALLI'], ['2016-08-31', 16.37, 'SGHALLI'],\n",
       "  ['2016-08-31', 13.95, 'SGHALLI'], ['2016-08-31', 22.42, 'SGHALLI'],\n",
       "  ['2016-08-31', 33.78, 'SGHALLI'], ['2016-08-31', 27.13, 'SGHALLI'],\n",
       "  ['2016-05-11', 36.53, 'SGHALLI'], ['2016-05-13', 26.03, 'SGHALLI'],\n",
       "  ['2016-05-13', 50.92, 'SGHALLI'], ['2016-05-16', 31.46, 'SGHALLI'],\n",
       "  ['2016-05-16', 50.08, 'SGHALLI'], ['2016-05-16', 59.53, 'SGHALLI'],\n",
       "  ['2016-05-17', 34.7, 'SGHALLI'], ['2016-05-17', 35.19, 'SGHALLI'],\n",
       "  ['2016-05-17', 30.94, 'SGHALLI'], ['2016-05-17', 57.93, 'SGHALLI'],\n",
       "  ['2016-05-18', 28.78, 'SGHALLI'], ['2016-05-18', 48, 'SGHALLI'], ['2016-05-18', 49.12, 'SGHALLI'],\n",
       "  ['2016-05-18', 60.33, 'SGHALLI'], ['2016-05-18', 31.88, 'SGHALLI'],\n",
       "  ['2016-05-19', 11.34, 'SGHALLI'], ['2016-05-19', 15.3, 'SGHALLI'],\n",
       "  ['2016-05-19', 34.36, 'SGHALLI'], ['2016-06-16', 21.24, 'SGHALLI'],\n",
       "  ['2016-07-17', 13.02, 'SGHALLI'], ['2016-07-22', 30.27, 'SGHALLI'],\n",
       "  ['2016-05-16', 60.75, 'SGHALLI'], ['2016-05-17', 42.88, 'SGHALLI'],\n",
       "  ['2016-05-17', 51.95, 'SGHALLI'], ['2016-05-18', 32.01, 'SGHALLI'],\n",
       "  ['2016-07-21', 31.02, 'SGHALLI'], ['2016-09-01', 20.55, 'CRS'], ['2016-09-01', 17.18, 'CRS'],\n",
       "  ['2016-09-01', 49.4, 'CRS'], ['2016-09-01', 49.02, 'CRS'], ['2016-09-01', 61.4, 'CRS'],\n",
       "  ['2016-09-01', 90.36, 'CRS'], ['2016-09-02', 65.5, 'CRS'], ['2016-09-02', 41.76, 'CRS'],\n",
       "  ['2016-09-02', 78.77, 'CRS'], ['2016-09-02', 66.73, 'CRS'], ['2016-09-02', 85.95, 'CRS'],\n",
       "  ['2016-09-02', 94.79, 'CRS'], ['2016-09-03', 37.21, 'CRS'], ['2016-09-03', 32.17, 'CRS'],\n",
       "  ['2016-09-03', 89.99, 'CRS'], ['2016-09-03', 77.1, 'CRS'], ['2016-09-03', 113.88, 'CRS'],\n",
       "  ['2016-09-03', 102, 'CRS'], ['2016-09-04', 52.3, 'CRS'], ['2016-09-04', 41.94, 'CRS'],\n",
       "  ['2016-09-04', 71.54, 'CRS'], ['2016-09-04', 57.95, 'CRS'], ['2016-09-04', 80.22, 'CRS'],\n",
       "  ['2016-09-04', 37.29, 'CRS'], ['2016-09-05', 21.67, 'CRS'], ['2016-09-05', 26.86, 'CRS'],\n",
       "  ['2016-09-05', 59.67, 'CRS'], ['2016-09-05', 53.76, 'CRS'], ['2016-09-05', 82.25, 'CRS'],\n",
       "  ['2016-09-05', 75.96, 'CRS'], ['2016-09-06', 44.41, 'CRS'], ['2016-09-06', 63.12, 'CRS'],\n",
       "  ['2016-09-06', 68.92, 'CRS'], ['2016-09-06', 71.01, 'CRS'], ['2016-09-06', 68.57, 'CRS'],\n",
       "  ['2016-09-06', 73.41, 'CRS'], ['2016-09-07', 35.32, 'CRS'], ['2016-09-07', 36.8, 'CRS'],\n",
       "  ['2016-09-07', 65.77, 'CRS'], ['2016-09-07', 55.9, 'CRS'], ['2016-09-07', 62.28, 'CRS'],\n",
       "  ['2016-09-07', 59.22, 'CRS'], ['2016-09-08', 48.88, 'CRS'], ['2016-09-08', 53.48, 'CRS'],\n",
       "  ['2016-09-08', 63.43, 'CRS'], ['2016-09-08', 54.08, 'CRS'], ['2016-09-08', 87.74, 'CRS'],\n",
       "  ['2016-09-08', 98.65, 'CRS'], ['2016-09-09', 54.69, 'CRS'], ['2016-09-09', 29.25, 'CRS'],\n",
       "  ['2016-09-09', 40.07, 'CRS'], ['2016-09-09', 47.81, 'CRS'], ['2016-09-09', 62.94, 'CRS'],\n",
       "  ['2016-09-09', 98.42, 'CRS'], ['2016-09-10', 47.66, 'CRS'], ['2016-09-10', 37.84, 'CRS'],\n",
       "  ['2016-09-10', 67.37, 'CRS'], ['2016-09-10', 73.78, 'CRS'], ['2016-09-10', 93.99, 'CRS'],\n",
       "  ['2016-09-10', 76.51, 'CRS'], ['2016-09-11', 33.07, 'CRS'], ['2016-09-11', 32.23, 'CRS'],\n",
       "  ['2016-09-11', 59.55, 'CRS'], ['2016-09-11', 63.42, 'CRS'], ['2016-09-11', 80.14, 'CRS'],\n",
       "  ['2016-09-11', 80.3, 'CRS'], ['2016-09-12', 47.19, 'CRS'], ['2016-09-12', 36.75, 'CRS'],\n",
       "  ['2016-09-12', 51.77, 'CRS'], ['2016-09-12', 69.02, 'CRS'], ['2016-09-12', 90.18, 'CRS'],\n",
       "  ['2016-09-12', 76.67, 'CRS'], ['2016-09-13', 39.39, 'CRS'], ['2016-09-13', 44.2, 'CRS'],\n",
       "  ['2016-09-13', 55.72, 'CRS'], ['2016-09-13', 37.56, 'CRS'], ['2016-09-13', 46.9, 'CRS'],\n",
       "  ['2016-09-13', 72.14, 'CRS'], ['2016-09-14', 32.19, 'CRS'], ['2016-09-14', 41.41, 'CRS'],\n",
       "  ['2016-09-14', 45.91, 'CRS'], ['2016-09-14', 37.43, 'CRS'], ['2016-09-14', 60.78, 'CRS'],\n",
       "  ['2016-09-14', 49.54, 'CRS'], ['2016-09-15', 25.68, 'CRS'], ['2016-09-15', 39.91, 'CRS'],\n",
       "  ['2016-09-15', 58.91, 'CRS'], ['2016-09-15', 45.77, 'CRS'], ['2016-09-15', 44.41, 'CRS'],\n",
       "  ['2016-09-15', 28.6, 'CRS'], ['2016-09-16', 22.37, 'CRS'], ['2016-09-16', 34.91, 'CRS'],\n",
       "  ['2016-09-16', 57.58, 'CRS'], ['2016-09-16', 72.86, 'CRS'], ['2016-09-16', 89.46, 'CRS'],\n",
       "  ['2016-09-16', 78.23, 'CRS'], ['2016-09-17', 51.36, 'CRS'], ['2016-09-17', 49.27, 'CRS'],\n",
       "  ['2016-09-17', 83.63, 'CRS'], ['2016-09-17', 89.12, 'CRS'], ['2016-09-17', 112.59, 'CRS'],\n",
       "  ['2016-09-17', 105.39, 'CRS'], ['2016-09-18', 69.58, 'CRS'], ['2016-09-18', 65.19, 'CRS'],\n",
       "  ['2016-09-18', 99.03, 'CRS'], ['2016-09-18', 76.34, 'CRS'], ['2016-09-18', 83.17, 'CRS'],\n",
       "  ['2016-09-18', 82.04, 'CRS'], ['2016-09-19', 35.39, 'CRS'], ['2016-09-19', 32.13, 'CRS'],\n",
       "  ['2016-09-19', 55.04, 'CRS'], ['2016-09-19', 50.63, 'CRS'], ['2016-09-19', 57.7, 'CRS'],\n",
       "  ['2016-09-19', 71.08, 'CRS'], ['2016-09-20', 28.87, 'CRS'], ['2016-09-20', 28.78, 'CRS'],\n",
       "  ['2016-09-20', 42.12, 'CRS'], ['2016-09-20', 51.95, 'CRS'], ['2016-09-20', 63.32, 'CRS'],\n",
       "  ['2016-09-20', 49.79, 'CRS'], ['2016-09-21', 25.55, 'CRS'], ['2016-09-21', 19.91, 'CRS'],\n",
       "  ['2016-09-21', 33.55, 'CRS'], ['2016-09-21', 40.84, 'CRS'], ['2016-09-21', 42.28, 'CRS'],\n",
       "  ['2016-09-21', 49.38, 'CRS'], ['2016-09-22', 19.54, 'CRS'], ['2016-09-22', 20.08, 'CRS'],\n",
       "  ['2016-09-22', 30.86, 'CRS'], ['2016-09-22', 124.35, 'CRS'], ['2016-09-22', 113.01, 'CRS'],\n",
       "  ['2016-09-23', 76.55, 'CRS'], ['2016-09-23', 96.1, 'CRS'], ['2016-09-23', 111.84, 'CRS'],\n",
       "  ['2016-09-23', 125.97, 'CRS'], ['2016-09-23', 108.75, 'CRS'], ['2016-09-23', 115.24, 'CRS'],\n",
       "  ['2016-09-24', 78.68, 'CRS'], ['2016-09-24', 49.29, 'CRS'], ['2016-09-24', 83.77, 'CRS'],\n",
       "  ['2016-09-24', 84.17, 'CRS'], ['2016-09-24', 164.15, 'CRS'], ['2016-09-24', 172.22, 'CRS'],\n",
       "  ['2016-09-25', 114.32, 'CRS'], ['2016-09-25', 85.88, 'CRS'], ['2016-09-25', 122.87, 'CRS'],\n",
       "  ['2016-09-25', 133.63, 'CRS'], ['2016-09-25', 170.13, 'CRS'], ['2016-09-25', 148.04, 'CRS'],\n",
       "  ['2016-09-26', 64.18, 'CRS'], ['2016-09-26', 111.75, 'CRS'], ['2016-09-26', 96.39, 'CRS'],\n",
       "  ['2016-09-26', 154.22, 'CRS'], ['2016-09-26', 164.92, 'CRS'], ['2016-09-27', 109.51, 'CRS'],\n",
       "  ['2016-09-27', 81.17, 'CRS'], ['2016-09-27', 71.22, 'CRS'], ['2016-09-27', 138.88, 'CRS'],\n",
       "  ['2016-09-27', 105.29, 'CRS'], ['2016-09-28', 76.97, 'CRS'], ['2016-09-28', 48.45, 'CRS'],\n",
       "  ['2016-09-28', 79.56, 'CRS'], ['2016-09-28', 135.99, 'CRS'], ['2016-09-28', 141.21, 'CRS'],\n",
       "  ['2016-09-29', 65.55, 'CRS'], ['2016-09-29', 55.97, 'CRS'], ['2016-09-29', 77.57, 'CRS'],\n",
       "  ['2016-09-30', 94.18, 'CRS'], ['2016-09-30', 119.78, 'CRS'], ['2016-09-30', 127.36, 'CRS'],\n",
       "  ['2016-09-30', 136.48, 'CRS'], ['2016-10-01', 76.04, 'CRS'], ['2016-10-01', 76.27, 'CRS'],\n",
       "  ['2016-10-01', 85.38, 'CRS'], ['2016-10-01', 97.52, 'CRS'], ['2016-10-01', 113.01, 'CRS'],\n",
       "  ['2016-10-01', 158.95, 'CRS'], ['2016-10-02', 83, 'CRS'], ['2016-10-02', 85.31, 'CRS'],\n",
       "  ['2016-10-02', 104.62, 'CRS'], ['2016-10-02', 88.56, 'CRS'], ['2016-10-02', 96.74, 'CRS'],\n",
       "  ['2016-10-02', 171.75, 'CRS'], ['2016-10-03', 144.02, 'CRS'], ['2016-10-03', 74.64, 'CRS'],\n",
       "  ['2016-10-03', 88.81, 'CRS'], ['2016-10-03', 112.92, 'CRS'], ['2016-10-03', 148.5, 'CRS'],\n",
       "  ['2016-10-03', 170.62, 'CRS'], ['2016-10-04', 87.84, 'CRS'], ['2016-10-04', 79.08, 'CRS'],\n",
       "  ['2016-10-04', 100.02, 'CRS'], ['2016-10-04', 138.96, 'CRS'], ['2016-10-04', 138.34, 'CRS'],\n",
       "  ['2016-10-05', 72.55, 'CRS'], ['2016-10-05', 90.75, 'CRS'], ['2016-10-05', 77.61, 'CRS'],\n",
       "  ['2016-10-05', 61.8, 'CRS'], ['2016-10-05', 139.25, 'CRS'], ['2016-10-06', 62.39, 'CRS'],\n",
       "  ['2016-10-06', 84.28, 'CRS'], ['2016-10-06', 73.99, 'CRS'], ['2016-10-06', 112.31, 'CRS'],\n",
       "  ['2016-10-06', 74, 'CRS'], ['2016-10-07', 98.25, 'CRS'], ['2016-10-07', 122.1, 'CRS'],\n",
       "  ['2016-10-07', 179.96, 'CRS'], ['2016-10-07', 165.1, 'CRS'], ['2016-10-07', 159.15, 'CRS'],\n",
       "  ['2016-10-07', 166.42, 'CRS'], ['2016-10-08', 119.23, 'CRS'], ['2016-10-08', 73.18, 'CRS'],\n",
       "  ['2016-10-08', 61.2, 'CRS'], ['2016-10-08', 51.44, 'CRS'], ['2016-10-08', 101.01, 'CRS'],\n",
       "  ['2016-10-08', 128.03, 'CRS'], ['2016-10-09', 91.63, 'CRS'], ['2016-10-09', 59.52, 'CRS'],\n",
       "  ['2016-10-09', 70.98, 'CRS'], ['2016-10-09', 74.05, 'CRS'], ['2016-10-09', 100.73, 'CRS'],\n",
       "  ['2016-10-09', 104.84, 'CRS'], ['2016-10-10', 55.8, 'CRS'], ['2016-10-10', 41.17, 'CRS'],\n",
       "  ['2016-10-10', 64.22, 'CRS'], ['2016-10-10', 65.94, 'CRS'], ['2016-10-10', 98.74, 'CRS'],\n",
       "  ['2016-10-10', 117.86, 'CRS'], ['2016-10-11', 72.69, 'CRS'], ['2016-10-11', 52.98, 'CRS'],\n",
       "  ['2016-10-11', 62.41, 'CRS'], ['2016-10-11', 58.47, 'CRS'], ['2016-10-11', 77.85, 'CRS'],\n",
       "  ['2016-10-11', 87.3, 'CRS'], ['2016-10-12', 40.86, 'CRS'], ['2016-10-12', 32.22, 'CRS'],\n",
       "  ['2016-10-12', 53.6, 'CRS'], ['2016-10-12', 55.08, 'CRS'], ['2016-10-12', 119.38, 'CRS'],\n",
       "  ['2016-10-12', 163.1, 'CRS'], ['2016-10-13', 75.82, 'CRS'], ['2016-10-13', 45.32, 'CRS'],\n",
       "  ['2016-10-13', 59.51, 'CRS'], ['2016-10-15', 147.99, 'CRS'], ['2016-10-15', 86.48, 'CRS'],\n",
       "  ['2016-10-15', 114.06, 'CRS'], ['2016-10-15', 192.84, 'CRS'], ['2016-10-15', 248.06, 'CRS'],\n",
       "  ['2016-10-16', 146.31, 'CRS'], ['2016-10-16', 180.99, 'CRS'], ['2016-10-16', 134.26, 'CRS'],\n",
       "  ['2016-10-16', 112.28, 'CRS'], ['2016-10-16', 154.09, 'CRS'], ['2016-10-16', 200.33, 'CRS'],\n",
       "  ['2016-10-17', 135.7, 'CRS'], ['2016-10-17', 188.57, 'CRS'], ['2016-10-17', 168.64, 'CRS'],\n",
       "  ['2016-10-17', 54.61, 'CRS'], ['2016-10-17', 162.39, 'CRS'], ['2016-10-17', 283.28, 'CRS'],\n",
       "  ['2016-10-18', 127.51, 'CRS'], ['2016-10-18', 186.19, 'CRS'], ['2016-10-18', 142.14, 'CRS'],\n",
       "  ['2016-10-18', 185.57, 'CRS'], ['2016-10-18', 216.28, 'CRS'], ['2016-10-18', 268.22, 'CRS'],\n",
       "  ['2016-10-19', 155.32, 'CRS'], ['2016-10-19', 230.92, 'CRS'], ['2016-10-19', 162.59, 'CRS'],\n",
       "  ['2016-10-19', 167.41, 'CRS'], ['2016-10-19', 181.09, 'CRS'], ['2016-10-19', 234.6, 'CRS'],\n",
       "  ['2016-10-20', 144.6, 'CRS'], ['2016-10-20', 224.9, 'CRS'], ['2016-10-20', 145.64, 'CRS'],\n",
       "  ['2016-10-20', 151.58, 'CRS'], ['2016-10-20', 211.23, 'CRS'], ['2016-10-20', 230.41, 'CRS'],\n",
       "  ['2016-10-21', 171.29, 'CRS'], ['2016-10-21', 211.05, 'CRS'], ['2016-10-21', 201.66, 'CRS'],\n",
       "  ['2016-10-21', 116.57, 'CRS'], ['2016-10-21', 184.45, 'CRS'], ['2016-10-21', 286.88, 'CRS'],\n",
       "  ['2016-10-22', 185.37, 'CRS'], ['2016-10-22', 201.69, 'CRS'], ['2016-10-22', 173.16, 'CRS'],\n",
       "  ['2016-10-22', 60.92, 'CRS'], ['2016-10-22', 155.2, 'CRS'], ['2016-10-22', 295.67, 'CRS'],\n",
       "  ['2016-10-23', 159.49, 'CRS'], ['2016-10-23', 248.37, 'CRS'], ['2016-10-23', 137.04, 'CRS'],\n",
       "  ['2016-10-23', 91.56, 'CRS'], ['2016-10-23', 136.48, 'CRS'], ['2016-10-23', 335.86, 'CRS'],\n",
       "  ['2016-10-24', 145.49, 'CRS'], ['2016-10-24', 171.46, 'CRS'], ['2016-10-24', 127.92, 'CRS'],\n",
       "  ['2016-10-24', 32.94, 'CRS'], ['2016-10-24', 302.75, 'CRS'], ['2016-10-24', 256.63, 'CRS'],\n",
       "  ['2016-10-25', 225.72, 'CRS'], ['2016-10-25', 220.04, 'CRS'], ['2016-10-25', 320.26, 'CRS'],\n",
       "  ['2016-10-25', null, 'CRS'], ['2016-10-25', 141.21, 'CRS'], ['2016-10-26', 106.42, 'CRS'],\n",
       "  ['2016-10-26', 111.66, 'CRS'], ['2016-10-26', 139.87, 'CRS'], ['2016-10-27', 230.19, 'CRS'],\n",
       "  ['2016-10-27', 129.77, 'CRS'], ['2016-10-27', 163.28, 'CRS'], ['2016-10-27', 146.64, 'CRS'],\n",
       "  ['2016-10-28', 98.77, 'CRS'], ['2016-10-28', 119.53, 'CRS'], ['2016-10-28', 150.57, 'CRS'],\n",
       "  ['2016-10-29', 114.32, 'CRS'], ['2016-10-29', 137.72, 'CRS'], ['2016-10-29', 98.56, 'CRS'],\n",
       "  ['2016-10-29', 109.98, 'CRS'], ['2016-10-29', 212.05, 'CRS'], ['2016-10-30', 122.44, 'CRS'],\n",
       "  ['2016-10-30', 116.04, 'CRS'], ['2016-10-30', 118.76, 'CRS'], ['2016-10-31', 89.54, 'CRS'],\n",
       "  ['2016-10-31', 103.07, 'CRS'], ['2016-10-31', 88.06, 'CRS'], ['2016-10-31', 87.5, 'CRS'],\n",
       "  ['2016-10-31', 121.71, 'CRS'], ['2016-11-02', 149.12, 'CRS'], ['2016-11-02', 167.86, 'CRS'],\n",
       "  ['2016-11-02', 131.72, 'CRS'], ['2016-11-02', 135.28, 'CRS'], ['2016-11-02', 133.45, 'CRS'],\n",
       "  ['2016-11-03', 109.27, 'CRS'], ['2016-11-03', 113.55, 'CRS'], ['2016-11-03', 133.21, 'CRS'],\n",
       "  ['2016-11-03', 100.4, 'CRS'], ['2016-11-03', 99.03, 'CRS'], ['2016-11-03', 111.01, 'CRS'],\n",
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       "  ['2016-11-05', 86.92, 'CRS'], ['2016-11-05', 98.77, 'CRS'], ['2016-11-05', 171.65, 'CRS'],\n",
       "  ['2016-11-06', 57.47, 'CRS'], ['2016-11-06', 68.07, 'CRS'], ['2016-11-06', 72.78, 'CRS'],\n",
       "  ['2016-11-07', 85.81, 'CRS'], ['2016-11-07', 86.63, 'CRS'], ['2016-11-07', 64.98, 'CRS'],\n",
       "  ['2016-11-07', 98.61, 'CRS'], ['2016-11-07', 148.94, 'CRS'], ['2016-11-08', 115.81, 'CRS'],\n",
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       "  ['2016-11-08', 110.91, 'CRS'], ['2016-11-08', 157.31, 'CRS'], ['2016-11-09', 114.33, 'CRS'],\n",
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       "  ['2016-11-09', 106.56, 'CRS'], ['2016-11-09', 163.57, 'CRS'], ['2016-11-10', 116.22, 'CRS'],\n",
       "  ['2016-11-10', 118, 'CRS'], ['2016-11-10', 153.58, 'CRS'], ['2016-11-10', 101.96, 'CRS'],\n",
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       "  ['2016-11-11', 109.35, 'CRS'], ['2016-11-11', 123.49, 'CRS'], ['2016-11-11', 214.34, 'CRS'],\n",
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       "  ['2016-11-21', 187.62, 'CRS'], ['2016-11-22', 114.67, 'CRS'], ['2016-11-22', 132.84, 'CRS'],\n",
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       "  ['2016-11-23', 103.1, 'CRS'], ['2016-11-23', 253.57, 'CRS'], ['2016-11-23', 152.21, 'CRS'],\n",
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       "  ['2016-11-24', 105.72, 'CRS'], ['2016-11-24', 203.07, 'CRS'], ['2016-11-24', 181.13, 'CRS'],\n",
       "  ['2016-11-25', 117.01, 'CRS'], ['2016-11-25', 129.75, 'CRS'], ['2016-11-25', 172.15, 'CRS'],\n",
       "  ['2016-11-25', 151.71, 'CRS'], ['2016-11-25', 220.3, 'CRS'], ['2016-11-25', 213.34, 'CRS'],\n",
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       "  ['2016-11-26', 125.74, 'CRS'], ['2016-11-26', 185.09, 'CRS'], ['2016-11-26', 201.07, 'CRS'],\n",
       "  ['2016-11-27', 190.28, 'CRS'], ['2016-11-27', 201.64, 'CRS'], ['2016-11-27', 142.05, 'CRS'],\n",
       "  ['2016-11-27', 147.78, 'CRS'], ['2016-11-27', 171.67, 'CRS'], ['2016-11-27', 181.69, 'CRS'],\n",
       "  ['2016-11-28', 156.85, 'CRS'], ['2016-11-28', 206.56, 'CRS'], ['2016-11-28', 176.38, 'CRS'],\n",
       "  ['2016-11-28', 228.58, 'CRS'], ['2016-11-28', 153.96, 'CRS'], ['2016-11-29', 199.73, 'CRS'],\n",
       "  ['2016-11-29', 191.36, 'CRS'], ['2016-11-29', 204.82, 'CRS'], ['2016-11-29', 148.34, 'CRS'],\n",
       "  ['2016-11-29', 197.76, 'CRS'], ['2016-11-29', 225.52, 'CRS'], ['2016-11-30', 174.75, 'CRS'],\n",
       "  ['2016-11-30', 178.8, 'CRS'], ['2016-11-30', 158.42, 'CRS'], ['2016-11-30', 153.48, 'CRS'],\n",
       "  ['2016-11-30', 165.21, 'CRS'], ['2016-11-30', 180.79, 'CRS'], ['2016-12-01', 175.87, 'CRS'],\n",
       "  ['2016-12-01', 135.99, 'CRS'], ['2016-12-01', 143.98, 'CRS'], ['2016-12-01', 131.29, 'CRS'],\n",
       "  ['2016-12-01', 134.94, 'CRS'], ['2016-12-01', 91.51, 'CRS'], ['2016-12-02', 82.28, 'CRS'],\n",
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       "  ['2016-12-02', 102.19, 'CRS'], ['2016-12-02', 51.89, 'CRS'], ['2016-12-03', 43.56, 'CRS'],\n",
       "  ['2016-12-03', 51.65, 'CRS'], ['2016-12-03', 49.42, 'CRS'], ['2016-12-03', null, 'CRS'],\n",
       "  ['2016-12-03', 208.6, 'CRS'], ['2016-12-03', 200.05, 'CRS'], ['2016-12-04', 85.51, 'CRS'],\n",
       "  ['2016-12-04', 107.21, 'CRS'], ['2016-12-04', 165.99, 'CRS'], ['2016-12-04', 132.65, 'CRS'],\n",
       "  ['2016-12-04', 194.37, 'CRS'], ['2016-12-04', 111.47, 'CRS'], ['2016-12-05', 63.85, 'CRS'],\n",
       "  ['2016-12-05', 99.84, 'CRS'], ['2016-12-05', 159.12, 'CRS'], ['2016-12-05', 142.13, 'CRS'],\n",
       "  ['2016-12-05', 208.05, 'CRS'], ['2016-12-05', 162.71, 'CRS'], ['2016-12-06', 91.84, 'CRS'],\n",
       "  ['2016-12-06', 135.99, 'CRS'], ['2016-12-06', 186.36, 'CRS'], ['2016-12-06', 205.02, 'CRS'],\n",
       "  ['2016-12-06', 182.63, 'CRS'], ['2016-12-07', 91.72, 'CRS'], ['2016-12-07', 141.84, 'CRS'],\n",
       "  ['2016-12-07', 154.72, 'CRS'], ['2016-12-07', 119.75, 'CRS'], ['2016-12-07', 154.74, 'CRS'],\n",
       "  ['2016-12-07', 139.1, 'CRS'], ['2016-12-08', 89.78, 'CRS'], ['2016-12-08', 134.58, 'CRS'],\n",
       "  ['2016-12-08', 152.67, 'CRS'], ['2016-12-08', 101.04, 'CRS'], ['2016-12-08', 137.97, 'CRS'],\n",
       "  ['2016-12-08', 176.83, 'CRS'], ['2016-12-09', 139.66, 'CRS'], ['2016-12-09', 150.25, 'CRS'],\n",
       "  ['2016-12-09', 148.71, 'CRS'], ['2016-12-09', 74.54, 'CRS'], ['2016-12-10', 110.79, 'CRS'],\n",
       "  ['2016-12-10', 88.84, 'CRS'], ['2016-12-10', 126.78, 'CRS'], ['2016-12-10', 181.64, 'CRS'],\n",
       "  ['2016-12-11', 115.06, 'CRS'], ['2016-12-11', 183.54, 'CRS'], ['2016-12-11', 158.86, 'CRS'],\n",
       "  ['2016-12-11', 90.64, 'CRS'], ['2016-12-11', 128.43, 'CRS'], ['2016-12-11', 141.58, 'CRS'],\n",
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       "  ['2016-12-12', 100.23, 'CRS'], ['2016-12-14', 48.4, 'CRS'], ['2016-12-14', 128.74, 'CRS'],\n",
       "  ['2016-12-14', 221.17, 'CRS'], ['2016-12-14', 187.09, 'CRS'], ['2016-12-15', 81.65, 'CRS'],\n",
       "  ['2016-12-15', 112.51, 'CRS'], ['2016-12-15', 196.31, 'CRS'], ['2016-12-15', 133.4, 'CRS'],\n",
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       "  ['2016-12-25', 95.91, 'CRS'], ['2016-12-25', 156.61, 'CRS'], ['2016-12-25', 119.46, 'CRS'],\n",
       "  ['2016-12-25', 156.97, 'CRS'], ['2016-12-25', 241.7, 'CRS'], ['2016-12-26', 102.23, 'CRS'],\n",
       "  ['2016-12-26', 101.92, 'CRS'], ['2016-12-26', 151.27, 'CRS'], ['2016-12-26', 88.15, 'CRS'],\n",
       "  ['2016-12-26', 114.44, 'CRS'], ['2016-12-26', 157.74, 'CRS'], ['2016-12-27', 101.66, 'CRS'],\n",
       "  ['2016-12-27', 96.22, 'CRS'], ['2016-12-27', 149.64, 'CRS'], ['2016-12-27', 107.99, 'CRS'],\n",
       "  ['2016-12-27', 85.2, 'CRS'], ['2016-12-28', 21.33, 'CRS'], ['2016-12-28', 127.33, 'CRS'],\n",
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       "  ['2016-12-29', 34.8, 'CRS'], ['2016-12-29', 132.71, 'CRS'], ['2016-12-29', 120.53, 'CRS'],\n",
       "  ['2016-12-30', 123.32, 'CRS'], ['2016-12-30', 125.84, 'CRS'], ['2016-12-30', 121.9, 'CRS'],\n",
       "  ['2016-12-30', 209.51, 'CRS'], ['2016-12-30', 147.36, 'CRS'], ['2016-12-30', 125.82, 'CRS'],\n",
       "  ['2016-12-31', 134.66, 'CRS'], ['2016-12-31', 123.25, 'CRS'], ['2016-12-31', 128.4, 'CRS'],\n",
       "  ['2016-12-31', 122.38, 'CRS'], ['2016-12-31', 150.92, 'CRS'], ['2016-12-31', 122.63, 'CRS'],\n",
       "  ['2015-11-10', 10.5, 'CRS'], ['2015-11-10', 41.62, 'CRS'], ['2015-11-13', 81.21, 'CRS'],\n",
       "  ['2015-11-13', 251.64, 'CRS'], ['2015-11-13', 349.78, 'CRS'], ['2015-11-13', 367.44, 'CRS'],\n",
       "  ['2015-11-14', 209.51, 'CRS'], ['2015-11-14', 176.91, 'CRS'], ['2015-11-14', 293.62, 'CRS'],\n",
       "  ['2015-11-14', 266.84, 'CRS'], ['2015-11-14', 261.33, 'CRS'], ['2015-11-23', 100.4, 'CRS'],\n",
       "  ['2015-11-23', 67.84, 'CRS'], ['2015-11-23', 44.75, 'CRS'], ['2015-11-24', 16.36, 'CRS'],\n",
       "  ['2015-11-24', 8.67, 'CRS'], ['2015-11-24', 50.3, 'CRS'], ['2015-11-24', 21.22, 'CRS'],\n",
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       "  ['2018-01-14', 184.73, 'CRS'], ['2018-01-14', 174.36, 'CRS'], ['2018-01-15', 109.6, 'CRS'],\n",
       "  ['2018-01-15', 180.52, 'CRS'], ['2018-01-15', 178.19, 'CRS'], ['2018-01-15', 78.13, 'CRS'],\n",
       "  ['2018-01-15', 175.71, 'CRS'], ['2018-01-15', 155.24, 'CRS'], ['2018-01-16', 89.52, 'CRS'],\n",
       "  ['2018-01-16', 160.33, 'CRS'], ['2018-01-16', 170.38, 'CRS'], ['2018-01-16', 114.17, 'CRS'],\n",
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       "  ['2018-01-17