provincial-gdp-by-industry-API-plotly.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": false
   },
   "source": [
    "## Provincial GDP by Industry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": false
   },
   "source": [
    "This notebook explores gross domestic product [data released by Statistics Canada on 2018-05-02](http://www.statcan.gc.ca/daily-quotidien/180502/dq180502a-eng.htm). The objective is to generate an overview of the 🇨🇦 economy, separated by provinces and industry sectors. The amounts are in `Chained (2007) dollars` (Millions).\n",
    "\n",
    "Specific Questions I want to understand:\n",
    "\n",
    "+ What are the top 10 industry sector line items in Canada? \n",
    "+ What are the top 10 industry sector line items in each province?\n",
    "\n",
    "Data was downladed directly from the API via the reference number: \"36-10-0402-01\"\n",
    "\n",
    "Full table in .csv format can be found [here](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3610040201) \n",
    "\n",
    "> Author: [J. Colliander](http://colliand.com)  \n",
    "> Date: 2018-05-03\n",
    "\n",
    "> Modified by: Laura Gutierrez Funderburk   \n",
    "> Date: 2019-02-07\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hidden": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import requests\n",
    "\n",
    "\n",
    "from tqdm import tnrange, tqdm_notebook\n",
    "from time import sleep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.10.0\n"
     ]
    }
   ],
   "source": [
    "import plotly.tools as tls\n",
    "from plotly import __version__\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "print (__version__) # requires version >= 1.9.0\n",
    "import cufflinks as cf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## run plotly offline\n",
    "cf.go_offline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%run -i ./StatsCan/helpers.py\n",
    "%run -i ./StatsCan/scwds.py\n",
    "%run -i ./StatsCan/sc.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "hidden": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2e10fe9cea434c81b4dde939cf3e4587",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, description='Downloading Dataset', max=1, style=ProgressStyle(description_…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "PARSING DATA AS PANDAS DATAFRAME\n"
     ]
    },
    {
     "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>REF_DATE</th>\n",
       "      <th>GEO</th>\n",
       "      <th>Value</th>\n",
       "      <th>North American Industry Classification System (NAICS)</th>\n",
       "      <th>SCALAR_FACTOR</th>\n",
       "      <th>VALUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>All industries [T001]</td>\n",
       "      <td>millions</td>\n",
       "      <td>9588.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Goods-producing industries [T002]</td>\n",
       "      <td>millions</td>\n",
       "      <td>2364.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Service-producing industries [T003]</td>\n",
       "      <td>millions</td>\n",
       "      <td>7224.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Industrial production [T010]</td>\n",
       "      <td>millions</td>\n",
       "      <td>1386.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Non-durable manufacturing industries [T011]</td>\n",
       "      <td>millions</td>\n",
       "      <td>488.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Durable manufacturing industries [T012]</td>\n",
       "      <td>millions</td>\n",
       "      <td>81.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Information and communication technology secto...</td>\n",
       "      <td>millions</td>\n",
       "      <td>334.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Information and communication technology, manu...</td>\n",
       "      <td>millions</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Information and communication technology, serv...</td>\n",
       "      <td>millions</td>\n",
       "      <td>334.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Energy sector [T016]</td>\n",
       "      <td>millions</td>\n",
       "      <td>441.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    REF_DATE                        GEO            Value  \\\n",
       "0 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "1 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "2 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "3 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "4 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "5 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "6 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "7 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "8 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "9 1997-01-01  Newfoundland and Labrador  Current dollars   \n",
       "\n",
       "  North American Industry Classification System (NAICS) SCALAR_FACTOR   VALUE  \n",
       "0                              All industries [T001]         millions  9588.2  \n",
       "1                  Goods-producing industries [T002]         millions  2364.1  \n",
       "2                Service-producing industries [T003]         millions  7224.1  \n",
       "3                       Industrial production [T010]         millions  1386.9  \n",
       "4        Non-durable manufacturing industries [T011]         millions   488.8  \n",
       "5            Durable manufacturing industries [T012]         millions    81.9  \n",
       "6  Information and communication technology secto...         millions   334.9  \n",
       "7  Information and communication technology, manu...         millions     0.8  \n",
       "8  Information and communication technology, serv...         millions   334.0  \n",
       "9                               Energy sector [T016]         millions   441.8  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "productId = \"36-10-0402-01\"\n",
    "\n",
    "download_tables(productId);\n",
    "\n",
    "df = zip_table_to_dataframe(productId)\n",
    "\n",
    "# OPTIONAL\n",
    "# REMOVE COLUMNS\n",
    "df2 = df.drop(columns=[\"DGUID\",\"UOM_ID\",\"UOM\",\"SCALAR_ID\",\"VECTOR\",\"COORDINATE\",\"STATUS\",\"TERMINATED\",\\\n",
    "              \"DECIMALS\",\"SYMBOL\"])\n",
    "\n",
    "df2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df2.rename(columns={'North American Industry Classification System (NAICS)': 'NAICS'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "subcategories_year = df.iloc[:,0].unique()\n",
    "\n",
    "subcategories_geog = df.iloc[:,1].unique()\n",
    "\n",
    "subcategories_value = df.iloc[:,3].unique()\n",
    "\n",
    "subcategories_NAICS = df.iloc[:,4].unique()\n",
    "\n",
    "sort_subcategories_NAICS = sorted(subcategories_NAICS)\n",
    "\n",
    "sort_subcategories_year = sorted(subcategories_year)\n",
    "\n",
    "sort_subcategories_geog = sorted(subcategories_geog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b0f89637be66400e9bfa3cfe002d1554",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Button(button_style='success', description='View Data Subset', layout=Layout(height='30px', width='15%'), styl…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d65a13fd4424bfebf7865a37733d434",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='NAICS category:', options=('Aboriginal public administration [914]', 'Accommodation and …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3aa292580c624544af8b778588105150",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='Location category:', options=('Alberta', 'British Columbia', 'Manitoba', 'New Brunswick'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e408e2b543f744c7a9e1be61987c274a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='Year category:', options=(numpy.datetime64('1997-01-01T00:00:00.000000000'), numpy.datet…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipywidgets import widgets, VBox, HBox, Button\n",
    "from ipywidgets import Button, Layout, widgets\n",
    "from IPython.display import display, Javascript, Markdown, HTML\n",
    "\n",
    "def rerun_cell( b ):\n",
    "    \n",
    "    display(Javascript('IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1,IPython.notebook.get_selected_index()+3)'))    \n",
    "\n",
    "style = {'description_width': 'initial'}\n",
    "\n",
    "MD_button = widgets.Button(\n",
    "    button_style='success',\n",
    "    description=\"View Data Subset\", \n",
    "    layout=Layout(width='15%', height='30px'),\n",
    "    style=style\n",
    ")    \n",
    "MD_button.on_click( rerun_cell )\n",
    "display(MD_button)\n",
    "\n",
    "NAICS_dp = widgets.Dropdown(\n",
    "    options = sort_subcategories_NAICS, \n",
    "    description ='NAICS category:', \n",
    "    style = style, \n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "\n",
    "geog_dp = widgets.Dropdown(\n",
    "    options = sort_subcategories_geog, \n",
    "    description ='Location category:', \n",
    "    style = style, \n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "value_dp = widgets.Dropdown(\n",
    "    options = subcategories_value, \n",
    "    description ='Value category:', \n",
    "    style = style, \n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "year_dp = widgets.Dropdown(\n",
    "    options = sort_subcategories_year, \n",
    "    description ='Year category:', \n",
    "    style = style, \n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "MD_button.on_click( rerun_cell )\n",
    "display(NAICS_dp)\n",
    "display(geog_dp)\n",
    "display(year_dp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>REF_DATE</th>\n",
       "      <th>GEO</th>\n",
       "      <th>Value</th>\n",
       "      <th>NAICS</th>\n",
       "      <th>SCALAR_FACTOR</th>\n",
       "      <th>VALUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8424</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Current dollars</td>\n",
       "      <td>Aboriginal public administration [914]</td>\n",
       "      <td>millions</td>\n",
       "      <td>258.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8761</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Aboriginal public administration [914]</td>\n",
       "      <td>millions</td>\n",
       "      <td>445.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9098</th>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Contributions to percent change</td>\n",
       "      <td>Aboriginal public administration [914]</td>\n",
       "      <td>units</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       REF_DATE      GEO                            Value  \\\n",
       "8424 1997-01-01  Alberta                  Current dollars   \n",
       "8761 1997-01-01  Alberta           Chained (2012) dollars   \n",
       "9098 1997-01-01  Alberta  Contributions to percent change   \n",
       "\n",
       "                                       NAICS SCALAR_FACTOR  VALUE  \n",
       "8424  Aboriginal public administration [914]      millions  258.7  \n",
       "8761  Aboriginal public administration [914]      millions  445.2  \n",
       "9098  Aboriginal public administration [914]        units     NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df3 = df2.loc[(df2['REF_DATE'] == year_dp.value) & (df2['GEO'] == geog_dp.value) & \\\n",
    "            (df2[\"NAICS\"] ==NAICS_dp.value) ]\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# df4 = df2.loc[(df2[\"REF_DATE\"] == \"2013-01-01\") & (df2[\"REF_DATE\"] <=  \"2017-01-01\")]\n",
    "\n",
    "def get_year_pd(dataframe,year):\n",
    "    df_year = dataframe.loc[(dataframe[\"REF_DATE\"] == str(year))]\n",
    "    df4 = df_year.rename(index=str, columns={\"VALUE\": year.split(\"-\")[0],\"GEO\":\"Geography\"})\n",
    "    df4 = df4.drop(columns=\"REF_DATE\")\n",
    "\n",
    "\n",
    "    columnsTitles = ['Geography', 'Value', 'NAICS',\\\n",
    "                    year.split(\"-\")[0]]\n",
    "\n",
    "    df4 = df4.reindex(columns=columnsTitles)\n",
    "\n",
    "    return df4\n",
    "df_2013 = get_year_pd(df2,\"2013-01-01\")\n",
    "df_2014 = get_year_pd(df2,\"2014-01-01\")\n",
    "df_2015 = get_year_pd(df2,\"2015-01-01\")\n",
    "df_2016 = get_year_pd(df2,\"2016-01-01\")\n",
    "df_2017 = get_year_pd(df2,\"2017-01-01\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df_2013_ = df_2013.loc[df_2013['Value'] == 'Chained (2012) dollars']\n",
    "df_2014_ = df_2014.loc[df_2014['Value'] == 'Chained (2012) dollars']\n",
    "df_2015_ = df_2015.loc[df_2015['Value'] == 'Chained (2012) dollars']\n",
    "df_2016_ = df_2016.loc[df_2016['Value'] == 'Chained (2012) dollars']\n",
    "df_2017_ = df_2017.loc[df_2017['Value'] == 'Chained (2012) dollars']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = pd.merge(pd.merge(pd.merge(pd.merge(df_2013_,df_2014_),df_2015_),df_2016_),df_2017_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    .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>Geography</th>\n",
       "      <th>Value</th>\n",
       "      <th>NAICS</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>All industries [T001]</td>\n",
       "      <td>31486.3</td>\n",
       "      <td>31143.3</td>\n",
       "      <td>30806.0</td>\n",
       "      <td>31334.5</td>\n",
       "      <td>31610.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Goods-producing industries [T002]</td>\n",
       "      <td>16022.7</td>\n",
       "      <td>15384.9</td>\n",
       "      <td>14913.2</td>\n",
       "      <td>15494.9</td>\n",
       "      <td>15787.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Service-producing industries [T003]</td>\n",
       "      <td>15482.4</td>\n",
       "      <td>15767.0</td>\n",
       "      <td>15875.5</td>\n",
       "      <td>15903.0</td>\n",
       "      <td>15925.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Industrial production [T010]</td>\n",
       "      <td>12475.0</td>\n",
       "      <td>11556.1</td>\n",
       "      <td>10876.1</td>\n",
       "      <td>11913.2</td>\n",
       "      <td>12550.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Non-durable manufacturing industries [T011]</td>\n",
       "      <td>625.5</td>\n",
       "      <td>570.4</td>\n",
       "      <td>568.4</td>\n",
       "      <td>560.8</td>\n",
       "      <td>594.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Durable manufacturing industries [T012]</td>\n",
       "      <td>258.2</td>\n",
       "      <td>292.9</td>\n",
       "      <td>362.6</td>\n",
       "      <td>317.1</td>\n",
       "      <td>352.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Information and communication technology secto...</td>\n",
       "      <td>699.6</td>\n",
       "      <td>709.3</td>\n",
       "      <td>751.4</td>\n",
       "      <td>754.3</td>\n",
       "      <td>762.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Information and communication technology, manu...</td>\n",
       "      <td>10.7</td>\n",
       "      <td>10.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>8.5</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Information and communication technology, serv...</td>\n",
       "      <td>689.0</td>\n",
       "      <td>699.2</td>\n",
       "      <td>742.3</td>\n",
       "      <td>744.9</td>\n",
       "      <td>751.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>Chained (2012) dollars</td>\n",
       "      <td>Energy sector [T016]</td>\n",
       "      <td>9028.7</td>\n",
       "      <td>8442.8</td>\n",
       "      <td>7281.4</td>\n",
       "      <td>8676.5</td>\n",
       "      <td>9288.2</td>\n",
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       "                   Geography                   Value  \\\n",
       "0  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "1  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "2  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "3  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "4  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "5  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "6  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "7  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "8  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "9  Newfoundland and Labrador  Chained (2012) dollars   \n",
       "\n",
       "                                               NAICS     2013     2014  \\\n",
       "0                              All industries [T001]  31486.3  31143.3   \n",
       "1                  Goods-producing industries [T002]  16022.7  15384.9   \n",
       "2                Service-producing industries [T003]  15482.4  15767.0   \n",
       "3                       Industrial production [T010]  12475.0  11556.1   \n",
       "4        Non-durable manufacturing industries [T011]    625.5    570.4   \n",
       "5            Durable manufacturing industries [T012]    258.2    292.9   \n",
       "6  Information and communication technology secto...    699.6    709.3   \n",
       "7  Information and communication technology, manu...     10.7     10.1   \n",
       "8  Information and communication technology, serv...    689.0    699.2   \n",
       "9                               Energy sector [T016]   9028.7   8442.8   \n",
       "\n",
       "      2015     2016     2017  \n",
       "0  30806.0  31334.5  31610.6  \n",
       "1  14913.2  15494.9  15787.7  \n",
       "2  15875.5  15903.0  15925.9  \n",
       "3  10876.1  11913.2  12550.5  \n",
       "4    568.4    560.8    594.0  \n",
       "5    362.6    317.1    352.3  \n",
       "6    751.4    754.3    762.6  \n",
       "7      7.8      8.5     11.3  \n",
       "8    742.3    744.9    751.7  \n",
       "9   7281.4   8676.5   9288.2  "
      ]
     },
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       "NAICS\n",
       "All industries [T001]                                        1818029.1\n",
       "All industries (except unlicensed cannabis sector) [T024]    1812613.1\n",
       "All industries (except cannabis sector) [T020]               1812598.3\n",
       "Service-producing industries [T003]                          1271363.1\n",
       "Goods-producing industries [T002]                             545765.7\n",
       "Industrial production [T010]                                  373014.6\n",
       "Public sector [T018]                                          344986.5\n",
       "Real estate and rental and leasing [53]                       228649.1\n",
       "Real estate [531]                                             215160.0\n",
       "Manufacturing [31-33]                                         188985.5\n",
       "Energy sector [T016]                                          163787.0\n",
       "Owner-occupied dwellings [5311A]                              144503.8\n",
       "Construction [23]                                             140961.9\n",
       "Mining, quarrying, and oil and gas extraction [21]            137422.1\n",
       "Health care and social assistance [62]                        126040.4\n",
       "Public administration [91]                                    121394.5\n",
       "Finance and insurance [52]                                    117322.7\n",
       "Health care [62X]                                             113077.9\n",
       "Professional, scientific and technical services [54]          104205.4\n",
       "Durable manufacturing industries [T012]                       102221.1\n",
       "Educational services [61]                                      97669.0\n",
       "Wholesale trade [41]                                           94613.2\n",
       "Oil and gas extraction [211]                                   92080.5\n",
       "Retail trade [44-45]                                           91209.3\n",
       "Retail trade (except cannabis) [4AA]                           89663.1\n",
       "Name: 2015, dtype: float64"
      ]
     },
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   ],
   "source": [
    "## Industry sectors sorted by total value across all provinces and territories\n",
    "new_df.groupby(['NAICS']).sum()['2015'].sort_values(ascending=False).head(n=25)"
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    "## GDP vs Provinces\n",
    "pd.pivot_table(new_df,index=['Geography'], \n",
    "               aggfunc = sum, \n",
    "               values = ['2017','2016','2015','2014','2013']).sort_values(by=['2017'], \n",
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   "source": [
    "## 2017 Single Largest GDP Sector Sorted\n",
    "pd.pivot_table(new_df,index=['NAICS'], \n",
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       "                                                                         2017\n",
       "Geography        NAICS                                                       \n",
       "Ontario          All industries [T001]                               712984.3\n",
       "                 All industries (except cannabis sector) [T020]      711993.5\n",
       "                 All industries (except unlicensed cannabis sect...  711870.5\n",
       "                 Service-producing industries [T003]                 546740.3\n",
       "Quebec           All industries [T001]                               356677.9\n",
       "                 All industries (except cannabis sector) [T020]      355036.9\n",
       "                 All industries (except unlicensed cannabis sect...  355020.7\n",
       "Alberta          All industries [T001]                               327596.2\n",
       "                 All industries (except cannabis sector) [T020]      327379.0\n",
       "                 All industries (except unlicensed cannabis sect...  327360.1\n",
       "Quebec           Service-producing industries [T003]                 258732.7\n",
       "British Columbia All industries [T001]                               240657.9\n",
       "                 All industries (except cannabis sector) [T020]      238790.4\n",
       "                 All industries (except unlicensed cannabis sect...  238766.6\n",
       "Alberta          Service-producing industries [T003]                 182725.9\n",
       "British Columbia Service-producing industries [T003]                 182289.7\n",
       "Ontario          Goods-producing industries [T002]                   166176.5\n",
       "Alberta          Goods-producing industries [T002]                   143383.1\n",
       "Ontario          Public sector [T018]                                138594.7\n",
       "Alberta          Industrial production [T010]                        114828.4\n",
       "Ontario          Industrial production [T010]                        110045.4\n",
       "Quebec           Goods-producing industries [T002]                    97966.1\n",
       "Alberta          Energy sector [T016]                                 97579.1\n",
       "Ontario          Real estate and rental and leasing [53]              92404.5\n",
       "                 Manufacturing [31-33]                                87783.7"
      ]
     },
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   ],
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    "## 2017 GDP vs Sector separated by Geography and sorted by maximum value\n",
    "pd.pivot_table(new_df,index=['Geography', 'NAICS'], \n",
    "               aggfunc = max, values = ['2017']).sort_values(by=['2017'], ascending=[False]).head(n=25)"
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   "source": [
    "## 2017 Individual Lines Items in the GDP breakdown of Geography X Sector\n",
    "pd.pivot_table(new_df,index=['Geography','NAICS'], \n",
    "               aggfunc = sum, values = ['2017','2016','2015','2014','2013']).sort_values(by='2017', \n",
    "                ascending=False).head(n=10).iplot(kind='bar')"
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    "The GDP from `Alberta, Oil and gas extraction [211]` is comparable to the GDP from `Ontario, Real estate [531]`. The GDP from `British Columbia (66), Real Estate [531]` is about half the size of the contribution from Alberta Oil and Gas and Ontario Real Estate."
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   "source": [
    "## Analyze Provincial GDP across Sectors"
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     "data": {
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       "[Newfoundland and Labrador, Prince Edward Island, Nova Scotia, New Brunswick, Quebec, ..., Alberta, British Columbia, Yukon, Northwest Territories, Nunavut]\n",
       "Length: 13\n",
       "Categories (13, object): [Newfoundland and Labrador, Prince Edward Island, Nova Scotia, New Brunswick, ..., British Columbia, Yukon, Northwest Territories, Nunavut]"
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    "new_df['Geography'].unique()"
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    "provinces = ['Newfoundland and Labrador', 'Prince Edward Island', 'Nova Scotia',\n",
    "       'New Brunswick', 'Quebec', 'Ontario', 'Manitoba', 'Saskatchewan',\n",
    "       'Alberta', 'British Columbia (66)', 'Yukon',\n",
    "       'Northwest Territories', 'Nunavut']"
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   ],
   "source": [
    "whichprovince = 'Alberta'\n",
    "pd.pivot_table(new_df.loc[new_df['Geography']== whichprovince],index=['NAICS'], \n",
    "               aggfunc = sum, values = ['2017','2016','2015','2014','2013']).sort_values(by='2017', \n",
    "               ascending=False).head(n=20).iplot(kind='bar', title= whichprovince)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "hidden": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x1c210d4780>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "whichprovince = 'Alberta'\n",
    "pd.pivot_table(new_df.loc[new_df['Geography']== whichprovince],index=['NAICS'], \n",
    "               aggfunc = sum, values = ['2017']).sort_values(by='2017', ascending=False).head(n=15).plot(\n",
    "                kind='pie', subplots=True, title= whichprovince, legend=False, figsize=(6,6), autopct='%1.1f%%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "hidden": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x1c1ef8ad30>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "whichprovince = 'Ontario'\n",
    "pd.pivot_table(new_df.loc[new_df['Geography']== whichprovince],index=['NAICS'], \n",
    "               aggfunc = sum, values = ['2017']).sort_values(by='2017', ascending=False).head(n=10).plot(\n",
    "                kind='pie', subplots=True, title= whichprovince, legend=False, figsize=(6,6), autopct='%1.1f%%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "hidden": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x1c213f6ef0>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "whichprovince = 'British Columbia'\n",
    "pd.pivot_table(new_df.loc[new_df['Geography']== whichprovince],index=['NAICS'], \n",
    "               aggfunc = sum, values = ['2017']).sort_values(by='2017', ascending=False).head(n=10).plot(\n",
    "                kind='pie', subplots=True, \n",
    "                title= whichprovince, legend=False, autopct='%1.1f%%', radius=1, figsize =(6,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "hidden": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"500\"\n",
       "            src=\"pivottablejs.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1c1ef8a278>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## This code creates a pivot table. Drag the column headings and play with the drop down menus to explore.\n",
    "from pivottablejs import pivot_ui\n",
    "pivot_ui(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "hidden": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}