01-find-candidate-data-ids.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we will identify candidate traces from the Dataport repo for our experiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the `metadata` view/document from Dataport."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('dataport-metadata.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of records it contains:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1436"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How does it look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>dataid</th>\n",
       "      <th>active_record</th>\n",
       "      <th>building_type</th>\n",
       "      <th>program_579</th>\n",
       "      <th>program_baseline</th>\n",
       "      <th>program_energy_internet_demo</th>\n",
       "      <th>program_lg_appliance</th>\n",
       "      <th>program_verizon</th>\n",
       "      <th>program_ccet_group</th>\n",
       "      <th>program_civita_group</th>\n",
       "      <th>...</th>\n",
       "      <th>refrigerator1</th>\n",
       "      <th>refrigerator2</th>\n",
       "      <th>security1</th>\n",
       "      <th>shed1</th>\n",
       "      <th>sprinkler1</th>\n",
       "      <th>utilityroom1</th>\n",
       "      <th>venthood1</th>\n",
       "      <th>waterheater1</th>\n",
       "      <th>waterheater2</th>\n",
       "      <th>winecooler1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2836</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5323</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8560</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 104 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   dataid active_record       building_type program_579 program_baseline  \\\n",
       "0    2836           NaN  Single-Family Home         NaN              NaN   \n",
       "1    2743           NaN  Single-Family Home         NaN              NaN   \n",
       "2    5323           NaN  Single-Family Home         NaN              yes   \n",
       "3    8560           NaN  Single-Family Home         NaN              yes   \n",
       "4    3313           NaN  Single-Family Home         NaN              yes   \n",
       "\n",
       "  program_energy_internet_demo program_lg_appliance program_verizon  \\\n",
       "0                          yes                  NaN             NaN   \n",
       "1                          yes                  NaN             NaN   \n",
       "2                          yes                  NaN             NaN   \n",
       "3                          yes                  NaN             NaN   \n",
       "4                          yes                  NaN             NaN   \n",
       "\n",
       "  program_ccet_group program_civita_group     ...      refrigerator1  \\\n",
       "0                NaN                  NaN     ...                NaN   \n",
       "1                NaN                  NaN     ...                NaN   \n",
       "2                NaN                  NaN     ...                NaN   \n",
       "3                NaN                  NaN     ...                NaN   \n",
       "4                NaN                  NaN     ...                NaN   \n",
       "\n",
       "  refrigerator2 security1 shed1 sprinkler1  utilityroom1  venthood1  \\\n",
       "0           NaN       NaN   NaN        NaN           NaN        NaN   \n",
       "1           NaN       NaN   NaN        NaN           NaN        NaN   \n",
       "2           NaN       NaN   NaN        NaN           NaN        NaN   \n",
       "3           NaN       NaN   NaN        NaN           NaN        NaN   \n",
       "4           NaN       NaN   NaN        NaN           NaN        NaN   \n",
       "\n",
       "   waterheater1  waterheater2  winecooler1  \n",
       "0           NaN           NaN          NaN  \n",
       "1           NaN           NaN          NaN  \n",
       "2           NaN           NaN          NaN  \n",
       "3           NaN           NaN          NaN  \n",
       "4           NaN           NaN          NaN  \n",
       "\n",
       "[5 rows x 104 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the proper index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('dataid', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>active_record</th>\n",
       "      <th>building_type</th>\n",
       "      <th>program_579</th>\n",
       "      <th>program_baseline</th>\n",
       "      <th>program_energy_internet_demo</th>\n",
       "      <th>program_lg_appliance</th>\n",
       "      <th>program_verizon</th>\n",
       "      <th>program_ccet_group</th>\n",
       "      <th>program_civita_group</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>refrigerator1</th>\n",
       "      <th>refrigerator2</th>\n",
       "      <th>security1</th>\n",
       "      <th>shed1</th>\n",
       "      <th>sprinkler1</th>\n",
       "      <th>utilityroom1</th>\n",
       "      <th>venthood1</th>\n",
       "      <th>waterheater1</th>\n",
       "      <th>waterheater2</th>\n",
       "      <th>winecooler1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2836</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2743</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5323</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8560</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3313</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       active_record       building_type program_579 program_baseline  \\\n",
       "dataid                                                                  \n",
       "2836             NaN  Single-Family Home         NaN              NaN   \n",
       "2743             NaN  Single-Family Home         NaN              NaN   \n",
       "5323             NaN  Single-Family Home         NaN              yes   \n",
       "8560             NaN  Single-Family Home         NaN              yes   \n",
       "3313             NaN  Single-Family Home         NaN              yes   \n",
       "\n",
       "       program_energy_internet_demo program_lg_appliance program_verizon  \\\n",
       "dataid                                                                     \n",
       "2836                            yes                  NaN             NaN   \n",
       "2743                            yes                  NaN             NaN   \n",
       "5323                            yes                  NaN             NaN   \n",
       "8560                            yes                  NaN             NaN   \n",
       "3313                            yes                  NaN             NaN   \n",
       "\n",
       "       program_ccet_group program_civita_group    city     ...       \\\n",
       "dataid                                                     ...        \n",
       "2836                  NaN                  NaN  Austin     ...        \n",
       "2743                  NaN                  NaN  Austin     ...        \n",
       "5323                  NaN                  NaN  Austin     ...        \n",
       "8560                  NaN                  NaN  Austin     ...        \n",
       "3313                  NaN                  NaN  Austin     ...        \n",
       "\n",
       "       refrigerator1 refrigerator2 security1 shed1  sprinkler1  utilityroom1  \\\n",
       "dataid                                                                         \n",
       "2836             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "2743             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "5323             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "8560             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "3313             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "\n",
       "        venthood1  waterheater1  waterheater2  winecooler1  \n",
       "dataid                                                      \n",
       "2836          NaN           NaN           NaN          NaN  \n",
       "2743          NaN           NaN           NaN          NaN  \n",
       "5323          NaN           NaN           NaN          NaN  \n",
       "8560          NaN           NaN           NaN          NaN  \n",
       "3313          NaN           NaN           NaN          NaN  \n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What columns do we have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['active_record',\n",
       " 'building_type',\n",
       " 'program_579',\n",
       " 'program_baseline',\n",
       " 'program_energy_internet_demo',\n",
       " 'program_lg_appliance',\n",
       " 'program_verizon',\n",
       " 'program_ccet_group',\n",
       " 'program_civita_group',\n",
       " 'city',\n",
       " 'state',\n",
       " 'pv',\n",
       " 'date_enrolled',\n",
       " 'date_withdrawn',\n",
       " 'house_construction_year',\n",
       " 'total_square_footage',\n",
       " 'first_floor_square_footage',\n",
       " 'second_floor_square_footage',\n",
       " 'third_floor_square_footage',\n",
       " 'half_floor_square_footage',\n",
       " 'lower_level_square_footage',\n",
       " 'audit_2011',\n",
       " 'audit_2013_2014',\n",
       " 'survey_2011',\n",
       " 'survey_2012',\n",
       " 'survey_2013',\n",
       " 'survey_2014',\n",
       " 'number_of_nests',\n",
       " 'indoor_temp_min_time',\n",
       " 'indoor_temp_max_time',\n",
       " 'gas_ert_min_time',\n",
       " 'gas_ert_max_time',\n",
       " 'water_ert_min_time',\n",
       " 'water_ert_max_time',\n",
       " 'egauge_min_time',\n",
       " 'egauge_max_time',\n",
       " 'use',\n",
       " 'grid',\n",
       " 'gen',\n",
       " 'air1',\n",
       " 'air2',\n",
       " 'air3',\n",
       " 'airwindowunit1',\n",
       " 'aquarium1',\n",
       " 'bathroom1',\n",
       " 'bathroom2',\n",
       " 'bedroom1',\n",
       " 'bedroom2',\n",
       " 'bedroom3',\n",
       " 'bedroom4',\n",
       " 'bedroom5',\n",
       " 'car1',\n",
       " 'clotheswasher1',\n",
       " 'clotheswasher_dryg1',\n",
       " 'diningroom1',\n",
       " 'diningroom2',\n",
       " 'dishwasher1',\n",
       " 'disposal1',\n",
       " 'drye1',\n",
       " 'dryg1',\n",
       " 'freezer1',\n",
       " 'furnace1',\n",
       " 'furnace2',\n",
       " 'garage1',\n",
       " 'garage2',\n",
       " 'heater1',\n",
       " 'housefan1',\n",
       " 'icemaker1',\n",
       " 'jacuzzi1',\n",
       " 'kitchen1',\n",
       " 'kitchen2',\n",
       " 'kitchenapp1',\n",
       " 'kitchenapp2',\n",
       " 'lights_plugs1',\n",
       " 'lights_plugs2',\n",
       " 'lights_plugs3',\n",
       " 'lights_plugs4',\n",
       " 'lights_plugs5',\n",
       " 'lights_plugs6',\n",
       " 'livingroom1',\n",
       " 'livingroom2',\n",
       " 'microwave1',\n",
       " 'office1',\n",
       " 'outsidelights_plugs1',\n",
       " 'outsidelights_plugs2',\n",
       " 'oven1',\n",
       " 'oven2',\n",
       " 'pool1',\n",
       " 'pool2',\n",
       " 'poollight1',\n",
       " 'poolpump1',\n",
       " 'pump1',\n",
       " 'range1',\n",
       " 'refrigerator1',\n",
       " 'refrigerator2',\n",
       " 'security1',\n",
       " 'shed1',\n",
       " 'sprinkler1',\n",
       " 'utilityroom1',\n",
       " 'venthood1',\n",
       " 'waterheater1',\n",
       " 'waterheater2',\n",
       " 'winecooler1']"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We wish to filter by:\n",
    "* `building_type`,\n",
    "* `city`,\n",
    "* whether a solar PV system is installed (`pv`),\n",
    "* and whether eGauge data is present (`egauge_min_time`, `egauge_max_time`) for the PV-generated power (`gen`), the grid power (`grid`), and the whole home electricity use (`use`).\n",
    "\n",
    "Let's look at the possible values for each of these criteria.\n",
    "\n",
    "See: https://chrisalbon.com/python/pandas_list_unique_values_in_column.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Single-Family Home', 'Town Home', 'Apartment', 'Mobile Home',\n",
       "       'Sales'], dtype=object)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['building_type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Austin', 'Georgetown', 'Dallas', 'Houston', 'Fort Worth',\n",
       "       'Benbrook', 'Willow Park', 'Weatherford', 'North Richland Hills',\n",
       "       'Argyle', 'Bedford', 'Grapevine', 'Hurst', 'Waxahachie',\n",
       "       'Grand Prairie', 'Arlington', 'Flower Mound', 'Richardson',\n",
       "       'Southlake', 'Tolar', 'Cedar Hill', 'Mansfield', 'Kingwood',\n",
       "       'Burleson', 'Santa Fe', 'Irving', 'Kennedale', 'Plano', 'Rowlett',\n",
       "       'Round Rock', 'Coppell', 'Wichita Falls', 'Allen', 'Bellaire',\n",
       "       'Midland', 'Colleyville', 'Katy', 'Sugar Land', 'Frisco', 'Spring',\n",
       "       'Euless', 'Carrollton', 'Haslet', 'Baytown', 'Richmond', 'Humble',\n",
       "       'Sherman', 'Sulphur Springs', 'Temple', 'Waco', 'Pflugerville',\n",
       "       'Little Elm', 'Brownwood', 'Flint', 'Freeport', 'Pottsboro',\n",
       "       'Taylor', 'Gainesville', 'Haltom City', 'Tomball', 'Friendswood',\n",
       "       'Heath', 'The Colony', 'Hutchins', 'Galveston', 'Pearland',\n",
       "       'Addison', 'Ennis', 'Aledo', 'Cypress', 'Killeen', 'El Lago',\n",
       "       'Mesquite', 'Forney', 'Missouri City', 'McKinney', 'Big Spring',\n",
       "       'Keller', 'Murphy', 'Lancaster', 'Malakoff', 'Palestine', 'Gorman',\n",
       "       'Terrell', 'Del Valle', 'Hudson Oaks', 'Lufkin', 'Sunnyvale',\n",
       "       'Midlothian', 'Odessa', 'Trophy Club', 'Cedar Park', 'San Diego',\n",
       "       'San Antonio', 'Spicewood', 'Lakeway', 'Bee Cave', 'Boulder',\n",
       "       'Spring Montgomery', 'Rio Hondo', 'San Benito', 'Harlingen',\n",
       "       'Los Fresnos', 'El Paso', 'Helotes', 'Chicago', 'austin'], dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['city'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'yes'], dtype=object)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['pv'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'yes'], dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['gen'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'yes'], dtype=object)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['grid'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'yes'], dtype=object)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['use'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following checks are from: https://chartio.com/resources/tutorials/how-to-check-if-any-value-is-nan-in-a-pandas-dataframe/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['egauge_min_time'].isnull().values.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['egauge_max_time'].isnull().values.any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So there are `NaN` values in those columns.\n",
    "\n",
    "We will need to eliminate the corresponding rows."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now set our criteria."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "choose_building_type = df['building_type'] == 'Single-Family Home'\n",
    "choose_city = df['city'] == 'Austin'\n",
    "choose_egauge_types = (df['pv'] == 'yes') & (df['gen'] == 'yes') & (df['grid'] == 'yes') & (df['use'] == 'yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate = df[choose_building_type & choose_city & choose_egauge_types].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How does it look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>active_record</th>\n",
       "      <th>building_type</th>\n",
       "      <th>program_579</th>\n",
       "      <th>program_baseline</th>\n",
       "      <th>program_energy_internet_demo</th>\n",
       "      <th>program_lg_appliance</th>\n",
       "      <th>program_verizon</th>\n",
       "      <th>program_ccet_group</th>\n",
       "      <th>program_civita_group</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>refrigerator1</th>\n",
       "      <th>refrigerator2</th>\n",
       "      <th>security1</th>\n",
       "      <th>shed1</th>\n",
       "      <th>sprinkler1</th>\n",
       "      <th>utilityroom1</th>\n",
       "      <th>venthood1</th>\n",
       "      <th>waterheater1</th>\n",
       "      <th>waterheater2</th>\n",
       "      <th>winecooler1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1114</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8872</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCET - Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1464</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCET - Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8047</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCET - Pricing Trial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8597</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCET - UT Text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Austin</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       active_record       building_type program_579 program_baseline  \\\n",
       "dataid                                                                  \n",
       "1114             NaN  Single-Family Home         NaN              yes   \n",
       "8872             NaN  Single-Family Home         NaN              yes   \n",
       "1464             NaN  Single-Family Home         NaN              yes   \n",
       "8047             NaN  Single-Family Home         NaN              yes   \n",
       "8597             NaN  Single-Family Home         NaN              yes   \n",
       "\n",
       "       program_energy_internet_demo program_lg_appliance program_verizon  \\\n",
       "dataid                                                                     \n",
       "1114                            yes                  NaN             NaN   \n",
       "8872                            yes                  NaN             NaN   \n",
       "1464                            yes                  NaN             NaN   \n",
       "8047                            yes                  NaN             NaN   \n",
       "8597                            yes                  NaN             NaN   \n",
       "\n",
       "          program_ccet_group program_civita_group    city     ...       \\\n",
       "dataid                                                        ...        \n",
       "1114                     NaN                  NaN  Austin     ...        \n",
       "8872          CCET - Control                  NaN  Austin     ...        \n",
       "1464          CCET - Control                  NaN  Austin     ...        \n",
       "8047    CCET - Pricing Trial                  NaN  Austin     ...        \n",
       "8597          CCET - UT Text                  NaN  Austin     ...        \n",
       "\n",
       "       refrigerator1 refrigerator2 security1 shed1  sprinkler1  utilityroom1  \\\n",
       "dataid                                                                         \n",
       "1114             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "8872             NaN           NaN       NaN   NaN         NaN           NaN   \n",
       "1464             yes           NaN       yes   NaN         yes           NaN   \n",
       "8047             yes           NaN       NaN   NaN         NaN           NaN   \n",
       "8597             yes           NaN       NaN   NaN         NaN           NaN   \n",
       "\n",
       "        venthood1  waterheater1  waterheater2  winecooler1  \n",
       "dataid                                                      \n",
       "1114          NaN           NaN           NaN          NaN  \n",
       "8872          NaN           NaN           NaN          NaN  \n",
       "1464          NaN           NaN           NaN          NaN  \n",
       "8047          yes           NaN           NaN          NaN  \n",
       "8597          NaN           NaN           NaN          NaN  \n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of records it contains:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "234"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Keep only the columns of interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate = df_candidate[['city', 'building_type', 'total_square_footage', 'house_construction_year', 'egauge_min_time', 'egauge_max_time']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How does it look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>city</th>\n",
       "      <th>building_type</th>\n",
       "      <th>total_square_footage</th>\n",
       "      <th>house_construction_year</th>\n",
       "      <th>egauge_min_time</th>\n",
       "      <th>egauge_max_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1114</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2122.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8872</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>1422.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-05-02 01:00:00-05</td>\n",
       "      <td>2013-06-10 00:59:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1464</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2345.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>2012-10-19 19:00:00-05</td>\n",
       "      <td>2014-03-05 17:59:00-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8047</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>3245.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>2013-04-16 00:00:00-05</td>\n",
       "      <td>2014-04-07 00:00:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8597</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2122.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-10-26 19:00:00-05</td>\n",
       "      <td>2014-10-21 18:59:00-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city       building_type  total_square_footage  \\\n",
       "dataid                                                     \n",
       "1114    Austin  Single-Family Home                2122.0   \n",
       "8872    Austin  Single-Family Home                1422.0   \n",
       "1464    Austin  Single-Family Home                2345.0   \n",
       "8047    Austin  Single-Family Home                3245.0   \n",
       "8597    Austin  Single-Family Home                2122.0   \n",
       "\n",
       "        house_construction_year         egauge_min_time  \\\n",
       "dataid                                                    \n",
       "1114                     2007.0                     NaN   \n",
       "8872                     2008.0  2012-05-02 01:00:00-05   \n",
       "1464                     2007.0  2012-10-19 19:00:00-05   \n",
       "8047                     2009.0  2013-04-16 00:00:00-05   \n",
       "8597                     2008.0  2012-10-26 19:00:00-05   \n",
       "\n",
       "               egauge_max_time  \n",
       "dataid                          \n",
       "1114                       NaN  \n",
       "8872    2013-06-10 00:59:00-05  \n",
       "1464    2014-03-05 17:59:00-06  \n",
       "8047    2014-04-07 00:00:00-05  \n",
       "8597    2014-10-21 18:59:00-05  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Filter out the rows with `Nan` values in the eGauge columns.\n",
    "\n",
    "See: https://stackoverflow.com/questions/13413590/how-to-drop-rows-of-pandas-dataframe-whose-value-in-certain-columns-is-nan#comment37529107_13434501"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate.dropna(subset=['egauge_min_time', 'egauge_max_time'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confirm the result.\n",
    "\n",
    "See: https://stackoverflow.com/a/29530559/2363529"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.notnull().any().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How does it look?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>city</th>\n",
       "      <th>building_type</th>\n",
       "      <th>total_square_footage</th>\n",
       "      <th>house_construction_year</th>\n",
       "      <th>egauge_min_time</th>\n",
       "      <th>egauge_max_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8872</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>1422.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-05-02 01:00:00-05</td>\n",
       "      <td>2013-06-10 00:59:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1464</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2345.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>2012-10-19 19:00:00-05</td>\n",
       "      <td>2014-03-05 17:59:00-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8047</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>3245.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>2013-04-16 00:00:00-05</td>\n",
       "      <td>2014-04-07 00:00:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8597</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2122.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-10-26 19:00:00-05</td>\n",
       "      <td>2014-10-21 18:59:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7982</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>1720.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>2013-02-22 18:00:00-06</td>\n",
       "      <td>2014-11-13 17:59:00-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city       building_type  total_square_footage  \\\n",
       "dataid                                                     \n",
       "8872    Austin  Single-Family Home                1422.0   \n",
       "1464    Austin  Single-Family Home                2345.0   \n",
       "8047    Austin  Single-Family Home                3245.0   \n",
       "8597    Austin  Single-Family Home                2122.0   \n",
       "7982    Austin  Single-Family Home                1720.0   \n",
       "\n",
       "        house_construction_year         egauge_min_time  \\\n",
       "dataid                                                    \n",
       "8872                     2008.0  2012-05-02 01:00:00-05   \n",
       "1464                     2007.0  2012-10-19 19:00:00-05   \n",
       "8047                     2009.0  2013-04-16 00:00:00-05   \n",
       "8597                     2008.0  2012-10-26 19:00:00-05   \n",
       "7982                     2007.0  2013-02-22 18:00:00-06   \n",
       "\n",
       "               egauge_max_time  \n",
       "dataid                          \n",
       "8872    2013-06-10 00:59:00-05  \n",
       "1464    2014-03-05 17:59:00-06  \n",
       "8047    2014-04-07 00:00:00-05  \n",
       "8597    2014-10-21 18:59:00-05  \n",
       "7982    2014-11-13 17:59:00-06  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sort by `dataid`.\n",
    "\n",
    "See: https://stackoverflow.com/a/22211821/2363529"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>city</th>\n",
       "      <th>building_type</th>\n",
       "      <th>total_square_footage</th>\n",
       "      <th>house_construction_year</th>\n",
       "      <th>egauge_min_time</th>\n",
       "      <th>egauge_max_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2075.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-11-02 19:00:00-05</td>\n",
       "      <td>2017-12-02 03:59:00-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2669.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>2014-06-06 00:00:00-05</td>\n",
       "      <td>2017-07-23 03:34:00-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2934.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>2012-12-08 18:00:00-06</td>\n",
       "      <td>2017-12-02 02:59:00-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>1842.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2013-10-15 19:00:00-05</td>\n",
       "      <td>2017-12-02 02:31:00-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2376.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-05-02 19:00:00-05</td>\n",
       "      <td>2017-12-02 02:59:00-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city       building_type  total_square_footage  \\\n",
       "dataid                                                     \n",
       "26      Austin  Single-Family Home                2075.0   \n",
       "77      Austin  Single-Family Home                2669.0   \n",
       "93      Austin  Single-Family Home                2934.0   \n",
       "114     Austin  Single-Family Home                1842.0   \n",
       "171     Austin  Single-Family Home                2376.0   \n",
       "\n",
       "        house_construction_year         egauge_min_time  \\\n",
       "dataid                                                    \n",
       "26                       2008.0  2012-11-02 19:00:00-05   \n",
       "77                       2009.0  2014-06-06 00:00:00-05   \n",
       "93                       1993.0  2012-12-08 18:00:00-06   \n",
       "114                      2008.0  2013-10-15 19:00:00-05   \n",
       "171                      2008.0  2012-05-02 19:00:00-05   \n",
       "\n",
       "               egauge_max_time  \n",
       "dataid                          \n",
       "26      2017-12-02 03:59:00-06  \n",
       "77      2017-07-23 03:34:00-05  \n",
       "93      2017-12-02 02:59:00-06  \n",
       "114     2017-12-02 02:31:00-06  \n",
       "171     2017-12-02 02:59:00-06  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city                        object\n",
       "building_type               object\n",
       "total_square_footage       float64\n",
       "house_construction_year    float64\n",
       "egauge_min_time             object\n",
       "egauge_max_time             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert `egauge_min_time` and `egauge_max_time` columns to `datetime` objects.\n",
    "\n",
    "See:\n",
    "https://stackoverflow.com/a/35630179/2363529\n",
    "https://stackoverflow.com/questions/26763344/convert-pandas-column-to-datetime#comment74177401_26763793"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate['egauge_min_time'] = pd.to_datetime(df_candidate['egauge_min_time'])\n",
    "df_candidate['egauge_max_time'] = pd.to_datetime(df_candidate['egauge_max_time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>city</th>\n",
       "      <th>building_type</th>\n",
       "      <th>total_square_footage</th>\n",
       "      <th>house_construction_year</th>\n",
       "      <th>egauge_min_time</th>\n",
       "      <th>egauge_max_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dataid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2075.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-11-03 00:00:00</td>\n",
       "      <td>2017-12-02 09:59:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2669.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>2014-06-06 05:00:00</td>\n",
       "      <td>2017-07-23 08:34:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2934.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>2012-12-09 00:00:00</td>\n",
       "      <td>2017-12-02 08:59:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>1842.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2013-10-16 00:00:00</td>\n",
       "      <td>2017-12-02 08:31:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Single-Family Home</td>\n",
       "      <td>2376.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2012-05-03 00:00:00</td>\n",
       "      <td>2017-12-02 08:59:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city       building_type  total_square_footage  \\\n",
       "dataid                                                     \n",
       "26      Austin  Single-Family Home                2075.0   \n",
       "77      Austin  Single-Family Home                2669.0   \n",
       "93      Austin  Single-Family Home                2934.0   \n",
       "114     Austin  Single-Family Home                1842.0   \n",
       "171     Austin  Single-Family Home                2376.0   \n",
       "\n",
       "        house_construction_year     egauge_min_time     egauge_max_time  \n",
       "dataid                                                                   \n",
       "26                       2008.0 2012-11-03 00:00:00 2017-12-02 09:59:00  \n",
       "77                       2009.0 2014-06-06 05:00:00 2017-07-23 08:34:00  \n",
       "93                       1993.0 2012-12-09 00:00:00 2017-12-02 08:59:00  \n",
       "114                      2008.0 2013-10-16 00:00:00 2017-12-02 08:31:00  \n",
       "171                      2008.0 2012-05-03 00:00:00 2017-12-02 08:59:00  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidate.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the data IDs against their corresponding segments.\n",
    "\n",
    "Assume a `dataid` which starts at `egauge_min_time` and ends at `egauge_max_time`.\n",
    "\n",
    "We want a straight line that starts at (egauge_min_time, data_id) and (egauge_max_time, data_id).\n",
    "\n",
    "See:\n",
    "http://nbviewer.jupyter.org/github/ipython/ipython/blob/1.x/examples/notebooks/Part%203%20-%20Plotting%20with%20Matplotlib.ipynb\n",
    "https://github.com/jakevdp/WhirlwindTourOfPython/blob/933b1c1507f443ea57bcb486fe5cd4cadfb377de/15-Preview-of-Data-Science-Tools.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = zip(df_candidate['egauge_min_time'], df_candidate['egauge_max_time'])\n",
    "ys = zip(df_candidate.index.values, df_candidate.index.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel='date', ylabel='data_id', title='eGauge traces for candidate houses')\n",
    "y_padding = 50\n",
    "ax.set(ylim=[max([min(df_candidate.index.values-y_padding),0]), max(df_candidate.index.values+y_padding)])\n",
    "\n",
    "for x, y in zip(xs, ys):\n",
    "    ax.plot(x, y, linewidth=1)\n",
    "fig.autofmt_xdate() # from: https://pythonspot.com/en/plot-time-with-matplotlib/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the figure above shows, it is practically impossible to to tell the most significant overlaps, both in terms of duration and number of data IDs.\n",
    "\n",
    "This is what we will attempt to extract programmatically in the following notebook in this series."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Store the resulting artifacts to disk.\n",
    "\n",
    "See: https://matplotlib.org/tutorials/introductory/lifecycle.html#saving-our-plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('01-segments-candidate-plot.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidate.to_csv('01-segments-candidate.csv')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}