.ipynb_checkpoints/Insight Chart-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pygal\n",
    "from IPython.display import SVG, display\n",
    "from memair import Memair\n",
    "# Use Otto the sandbox user's access token or create your own at https://memair.com/temporary_access_token\n",
    "access_token = '0000000000000000000000000000000000000000000000000000000000000000'\n",
    "\n",
    "user = Memair(access_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data': {'CreateInsight': {'id': '10',\n",
       "   'chart': {'title': 'Social Media Usage',\n",
       "    'type': 'line',\n",
       "    'category_axis': ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'],\n",
       "    'series': [{'label': 'facebook', 'data': [2.1, 2.4, 1.8, 4.3, 2.7]},\n",
       "     {'label': 'twitter', 'data': [1.6, 0.4, 0.8, 2.4, 1.2]}]}}}}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response = user.query('''\n",
    "    mutation { \n",
    "      CreateInsight(\n",
    "        chart: {\n",
    "          title: \"Social Media Usage\"\n",
    "          type: line\n",
    "          category_axis: [\"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\"]\n",
    "          series: [\n",
    "            {label: \"facebook\" data: [2.1, 2.4, 1.8, 4.3, 2.7]}\n",
    "            {label: \"twitter\" data: [1.6, 0.4, 0.8, 2.4, 1.2]}\n",
    "          ]\n",
    "        }\n",
    "      )\n",
    "      {\n",
    "        id\n",
    "        chart\n",
    "      }\n",
    "    }\n",
    "''')\n",
    "chart = response['data']['CreateInsight']['chart']\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['facebook', [2.1, 2.4, 1.8, 4.3, 2.7]],\n",
       " ['twitter', [1.6, 0.4, 0.8, 2.4, 1.2]]]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = []\n",
    "for series in chart['series']:\n",
    "    data.append([series['label'], series['data']])\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "stackedline_chart = pygal.StackedLine(fill=True)\n",
    "stackedline_chart.title = \"Hours spend on Social Media\"\n",
    "stackedline_chart.x_labels = chart['category_axis']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for label, data_points in data:\n",
    "    stackedline_chart.add(label, data_points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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