Plotly Dash Tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "czech-decimal",
   "metadata": {},
   "source": [
    "# Plotly Dash Tutorial\n",
    "\n",
    "In this tutorial session we're going to explore how to make dashboard using [Dash by Plotly](https://dash.plotly.com/)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "competent-chorus",
   "metadata": {},
   "source": [
    "## What is Plotly Dash?\n",
    "\n",
    "Dash is a productive Python framework for building web analytic applications.\n",
    "Written on top of Flask, Plotly.js, and React.js, Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python. It's particularly suited for anyone who works with data in Python.\n",
    "\n",
    "### Front-End\n",
    "\n",
    "Dash’s frontend renders HTML components using **React.js**, the Javascript user-interface library written and maintained by Facebook.\n",
    "\n",
    "### Back-End\n",
    "Dash applications are web servers running **Flask** and communicating JSON packets over HTTP requests. \n",
    "\n",
    "### Graphs \n",
    "Graphs in Dash use the Plotly python library"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "lucky-victor",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "familiar-earth",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "pd.set_option(\"display.max_rows\", 500)\n",
    "pd.set_option(\"display.max_columns\", 500)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "incorporated-negotiation",
   "metadata": {},
   "source": [
    "## Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "limiting-delay",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(71895, 59)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"./data/owid-covid-data.csv\")\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "engaging-nepal",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>...</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0      AFG      Asia  Afghanistan  2020-02-24          1.0        1.0   \n",
       "1      AFG      Asia  Afghanistan  2020-02-25          1.0        0.0   \n",
       "2      AFG      Asia  Afghanistan  2020-02-26          1.0        0.0   \n",
       "3      AFG      Asia  Afghanistan  2020-02-27          1.0        0.0   \n",
       "4      AFG      Asia  Afghanistan  2020-02-28          1.0        0.0   \n",
       "\n",
       "   new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  ...  \\\n",
       "0                 NaN           NaN         NaN                  NaN  ...   \n",
       "1                 NaN           NaN         NaN                  NaN  ...   \n",
       "2                 NaN           NaN         NaN                  NaN  ...   \n",
       "3                 NaN           NaN         NaN                  NaN  ...   \n",
       "4                 NaN           NaN         NaN                  NaN  ...   \n",
       "\n",
       "   gdp_per_capita  extreme_poverty  cardiovasc_death_rate  \\\n",
       "0        1803.987              NaN                597.029   \n",
       "1        1803.987              NaN                597.029   \n",
       "2        1803.987              NaN                597.029   \n",
       "3        1803.987              NaN                597.029   \n",
       "4        1803.987              NaN                597.029   \n",
       "\n",
       "   diabetes_prevalence  female_smokers  male_smokers  handwashing_facilities  \\\n",
       "0                 9.59             NaN           NaN                  37.746   \n",
       "1                 9.59             NaN           NaN                  37.746   \n",
       "2                 9.59             NaN           NaN                  37.746   \n",
       "3                 9.59             NaN           NaN                  37.746   \n",
       "4                 9.59             NaN           NaN                  37.746   \n",
       "\n",
       "   hospital_beds_per_thousand  life_expectancy  human_development_index  \n",
       "0                         0.5            64.83                    0.511  \n",
       "1                         0.5            64.83                    0.511  \n",
       "2                         0.5            64.83                    0.511  \n",
       "3                         0.5            64.83                    0.511  \n",
       "4                         0.5            64.83                    0.511  \n",
       "\n",
       "[5 rows x 59 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "exposed-brown",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iso_code                                  object\n",
       "continent                                 object\n",
       "location                                  object\n",
       "date                                      object\n",
       "total_cases                              float64\n",
       "new_cases                                float64\n",
       "new_cases_smoothed                       float64\n",
       "total_deaths                             float64\n",
       "new_deaths                               float64\n",
       "new_deaths_smoothed                      float64\n",
       "total_cases_per_million                  float64\n",
       "new_cases_per_million                    float64\n",
       "new_cases_smoothed_per_million           float64\n",
       "total_deaths_per_million                 float64\n",
       "new_deaths_per_million                   float64\n",
       "new_deaths_smoothed_per_million          float64\n",
       "reproduction_rate                        float64\n",
       "icu_patients                             float64\n",
       "icu_patients_per_million                 float64\n",
       "hosp_patients                            float64\n",
       "hosp_patients_per_million                float64\n",
       "weekly_icu_admissions                    float64\n",
       "weekly_icu_admissions_per_million        float64\n",
       "weekly_hosp_admissions                   float64\n",
       "weekly_hosp_admissions_per_million       float64\n",
       "new_tests                                float64\n",
       "total_tests                              float64\n",
       "total_tests_per_thousand                 float64\n",
       "new_tests_per_thousand                   float64\n",
       "new_tests_smoothed                       float64\n",
       "new_tests_smoothed_per_thousand          float64\n",
       "positive_rate                            float64\n",
       "tests_per_case                           float64\n",
       "tests_units                               object\n",
       "total_vaccinations                       float64\n",
       "people_vaccinated                        float64\n",
       "people_fully_vaccinated                  float64\n",
       "new_vaccinations                         float64\n",
       "new_vaccinations_smoothed                float64\n",
       "total_vaccinations_per_hundred           float64\n",
       "people_vaccinated_per_hundred            float64\n",
       "people_fully_vaccinated_per_hundred      float64\n",
       "new_vaccinations_smoothed_per_million    float64\n",
       "stringency_index                         float64\n",
       "population                               float64\n",
       "population_density                       float64\n",
       "median_age                               float64\n",
       "aged_65_older                            float64\n",
       "aged_70_older                            float64\n",
       "gdp_per_capita                           float64\n",
       "extreme_poverty                          float64\n",
       "cardiovasc_death_rate                    float64\n",
       "diabetes_prevalence                      float64\n",
       "female_smokers                           float64\n",
       "male_smokers                             float64\n",
       "handwashing_facilities                   float64\n",
       "hospital_beds_per_thousand               float64\n",
       "life_expectancy                          float64\n",
       "human_development_index                  float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "canadian-thanks",
   "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>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>new_cases_per_million</th>\n",
       "      <th>new_cases_smoothed_per_million</th>\n",
       "      <th>total_deaths_per_million</th>\n",
       "      <th>...</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.093300e+04</td>\n",
       "      <td>70931.000000</td>\n",
       "      <td>69930.000000</td>\n",
       "      <td>6.185400e+04</td>\n",
       "      <td>62012.000000</td>\n",
       "      <td>69930.000000</td>\n",
       "      <td>70545.000000</td>\n",
       "      <td>70543.000000</td>\n",
       "      <td>69547.000000</td>\n",
       "      <td>61479.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>65584.000000</td>\n",
       "      <td>44799.000000</td>\n",
       "      <td>66193.000000</td>\n",
       "      <td>67018.000000</td>\n",
       "      <td>52096.000000</td>\n",
       "      <td>51381.000000</td>\n",
       "      <td>33212.000000</td>\n",
       "      <td>60651.000000</td>\n",
       "      <td>68316.000000</td>\n",
       "      <td>66171.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.068499e+05</td>\n",
       "      <td>5105.586316</td>\n",
       "      <td>5126.638594</td>\n",
       "      <td>1.831622e+04</td>\n",
       "      <td>131.216861</td>\n",
       "      <td>115.200623</td>\n",
       "      <td>7139.394665</td>\n",
       "      <td>64.820478</td>\n",
       "      <td>64.811251</td>\n",
       "      <td>170.642827</td>\n",
       "      <td>...</td>\n",
       "      <td>19136.464863</td>\n",
       "      <td>13.252561</td>\n",
       "      <td>257.059990</td>\n",
       "      <td>7.792841</td>\n",
       "      <td>10.560287</td>\n",
       "      <td>32.650412</td>\n",
       "      <td>51.028831</td>\n",
       "      <td>3.037860</td>\n",
       "      <td>73.139962</td>\n",
       "      <td>0.728095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.285003e+06</td>\n",
       "      <td>32188.728177</td>\n",
       "      <td>31956.693848</td>\n",
       "      <td>1.066911e+05</td>\n",
       "      <td>720.766814</td>\n",
       "      <td>657.731277</td>\n",
       "      <td>14155.550538</td>\n",
       "      <td>166.344126</td>\n",
       "      <td>139.609605</td>\n",
       "      <td>305.380365</td>\n",
       "      <td>...</td>\n",
       "      <td>19682.904401</td>\n",
       "      <td>19.911393</td>\n",
       "      <td>118.372675</td>\n",
       "      <td>3.929761</td>\n",
       "      <td>10.413011</td>\n",
       "      <td>13.462357</td>\n",
       "      <td>31.769188</td>\n",
       "      <td>2.468071</td>\n",
       "      <td>7.550833</td>\n",
       "      <td>0.150147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>-46076.000000</td>\n",
       "      <td>-1121.714000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>-1918.000000</td>\n",
       "      <td>-232.143000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>-2153.437000</td>\n",
       "      <td>-276.825000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>...</td>\n",
       "      <td>661.240000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>79.370000</td>\n",
       "      <td>0.990000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>7.700000</td>\n",
       "      <td>1.188000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>53.280000</td>\n",
       "      <td>0.394000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.040000e+02</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.714000</td>\n",
       "      <td>3.500000e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>136.271000</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.971000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>...</td>\n",
       "      <td>4466.507000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>167.295000</td>\n",
       "      <td>5.290000</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>21.600000</td>\n",
       "      <td>20.859000</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>67.440000</td>\n",
       "      <td>0.602000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.533000e+03</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>68.857000</td>\n",
       "      <td>2.360000e+02</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1016.687000</td>\n",
       "      <td>6.101000</td>\n",
       "      <td>8.114000</td>\n",
       "      <td>29.465000</td>\n",
       "      <td>...</td>\n",
       "      <td>12951.839000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>242.648000</td>\n",
       "      <td>7.110000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>31.400000</td>\n",
       "      <td>49.839000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>74.530000</td>\n",
       "      <td>0.748000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.221100e+04</td>\n",
       "      <td>655.000000</td>\n",
       "      <td>683.429000</td>\n",
       "      <td>2.229000e+03</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>6502.954000</td>\n",
       "      <td>54.202500</td>\n",
       "      <td>61.557000</td>\n",
       "      <td>179.964500</td>\n",
       "      <td>...</td>\n",
       "      <td>27216.445000</td>\n",
       "      <td>21.200000</td>\n",
       "      <td>329.635000</td>\n",
       "      <td>10.080000</td>\n",
       "      <td>19.300000</td>\n",
       "      <td>41.100000</td>\n",
       "      <td>83.241000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>78.730000</td>\n",
       "      <td>0.848000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.140680e+08</td>\n",
       "      <td>879905.000000</td>\n",
       "      <td>738686.000000</td>\n",
       "      <td>2.530716e+06</td>\n",
       "      <td>17845.000000</td>\n",
       "      <td>14379.286000</td>\n",
       "      <td>140632.887000</td>\n",
       "      <td>8652.658000</td>\n",
       "      <td>2648.773000</td>\n",
       "      <td>2180.447000</td>\n",
       "      <td>...</td>\n",
       "      <td>116935.600000</td>\n",
       "      <td>77.600000</td>\n",
       "      <td>724.417000</td>\n",
       "      <td>30.530000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>78.100000</td>\n",
       "      <td>98.999000</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>86.750000</td>\n",
       "      <td>0.957000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        total_cases      new_cases  new_cases_smoothed  total_deaths  \\\n",
       "count  7.093300e+04   70931.000000        69930.000000  6.185400e+04   \n",
       "mean   6.068499e+05    5105.586316         5126.638594  1.831622e+04   \n",
       "std    4.285003e+06   32188.728177        31956.693848  1.066911e+05   \n",
       "min    1.000000e+00  -46076.000000        -1121.714000  1.000000e+00   \n",
       "25%    7.040000e+02       1.000000            5.714000  3.500000e+01   \n",
       "50%    7.533000e+03      57.000000           68.857000  2.360000e+02   \n",
       "75%    8.221100e+04     655.000000          683.429000  2.229000e+03   \n",
       "max    1.140680e+08  879905.000000       738686.000000  2.530716e+06   \n",
       "\n",
       "         new_deaths  new_deaths_smoothed  total_cases_per_million  \\\n",
       "count  62012.000000         69930.000000             70545.000000   \n",
       "mean     131.216861           115.200623              7139.394665   \n",
       "std      720.766814           657.731277             14155.550538   \n",
       "min    -1918.000000          -232.143000                 0.001000   \n",
       "25%        0.000000             0.000000               136.271000   \n",
       "50%        2.000000             1.000000              1016.687000   \n",
       "75%       16.000000            12.000000              6502.954000   \n",
       "max    17845.000000         14379.286000            140632.887000   \n",
       "\n",
       "       new_cases_per_million  new_cases_smoothed_per_million  \\\n",
       "count           70543.000000                    69547.000000   \n",
       "mean               64.820478                       64.811251   \n",
       "std               166.344126                      139.609605   \n",
       "min             -2153.437000                     -276.825000   \n",
       "25%                 0.125000                        0.971000   \n",
       "50%                 6.101000                        8.114000   \n",
       "75%                54.202500                       61.557000   \n",
       "max              8652.658000                     2648.773000   \n",
       "\n",
       "       total_deaths_per_million  ...  gdp_per_capita  extreme_poverty  \\\n",
       "count              61479.000000  ...    65584.000000     44799.000000   \n",
       "mean                 170.642827  ...    19136.464863        13.252561   \n",
       "std                  305.380365  ...    19682.904401        19.911393   \n",
       "min                    0.001000  ...      661.240000         0.100000   \n",
       "25%                    5.420000  ...     4466.507000         0.500000   \n",
       "50%                   29.465000  ...    12951.839000         2.000000   \n",
       "75%                  179.964500  ...    27216.445000        21.200000   \n",
       "max                 2180.447000  ...   116935.600000        77.600000   \n",
       "\n",
       "       cardiovasc_death_rate  diabetes_prevalence  female_smokers  \\\n",
       "count           66193.000000         67018.000000    52096.000000   \n",
       "mean              257.059990             7.792841       10.560287   \n",
       "std               118.372675             3.929761       10.413011   \n",
       "min                79.370000             0.990000        0.100000   \n",
       "25%               167.295000             5.290000        1.900000   \n",
       "50%               242.648000             7.110000        6.300000   \n",
       "75%               329.635000            10.080000       19.300000   \n",
       "max               724.417000            30.530000       44.000000   \n",
       "\n",
       "       male_smokers  handwashing_facilities  hospital_beds_per_thousand  \\\n",
       "count  51381.000000            33212.000000                60651.000000   \n",
       "mean      32.650412               51.028831                    3.037860   \n",
       "std       13.462357               31.769188                    2.468071   \n",
       "min        7.700000                1.188000                    0.100000   \n",
       "25%       21.600000               20.859000                    1.300000   \n",
       "50%       31.400000               49.839000                    2.400000   \n",
       "75%       41.100000               83.241000                    4.000000   \n",
       "max       78.100000               98.999000                   13.800000   \n",
       "\n",
       "       life_expectancy  human_development_index  \n",
       "count     68316.000000             66171.000000  \n",
       "mean         73.139962                 0.728095  \n",
       "std           7.550833                 0.150147  \n",
       "min          53.280000                 0.394000  \n",
       "25%          67.440000                 0.602000  \n",
       "50%          74.530000                 0.748000  \n",
       "75%          78.730000                 0.848000  \n",
       "max          86.750000                 0.957000  \n",
       "\n",
       "[8 rows x 54 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "legal-wallace",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>...</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46877</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46878</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46879</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46880</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46881</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47239</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2021-02-24</td>\n",
       "      <td>153842.0</td>\n",
       "      <td>655.0</td>\n",
       "      <td>639.000</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.000</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47240</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2021-02-25</td>\n",
       "      <td>154476.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>604.286</td>\n",
       "      <td>1891.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.571</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47241</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2021-02-26</td>\n",
       "      <td>155076.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>595.429</td>\n",
       "      <td>1902.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.714</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47242</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2021-02-27</td>\n",
       "      <td>155417.0</td>\n",
       "      <td>341.0</td>\n",
       "      <td>552.000</td>\n",
       "      <td>1905.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.571</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47243</th>\n",
       "      <td>NGA</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>2021-02-28</td>\n",
       "      <td>155657.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>511.857</td>\n",
       "      <td>1907.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.714</td>\n",
       "      <td>...</td>\n",
       "      <td>5338.454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.013</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>41.949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.69</td>\n",
       "      <td>0.539</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>367 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      iso_code continent location        date  total_cases  new_cases  \\\n",
       "46877      NGA    Africa  Nigeria  2020-02-28          1.0        1.0   \n",
       "46878      NGA    Africa  Nigeria  2020-02-29          1.0        0.0   \n",
       "46879      NGA    Africa  Nigeria  2020-03-01          1.0        0.0   \n",
       "46880      NGA    Africa  Nigeria  2020-03-02          1.0        0.0   \n",
       "46881      NGA    Africa  Nigeria  2020-03-03          1.0        0.0   \n",
       "...        ...       ...      ...         ...          ...        ...   \n",
       "47239      NGA    Africa  Nigeria  2021-02-24     153842.0      655.0   \n",
       "47240      NGA    Africa  Nigeria  2021-02-25     154476.0      634.0   \n",
       "47241      NGA    Africa  Nigeria  2021-02-26     155076.0      600.0   \n",
       "47242      NGA    Africa  Nigeria  2021-02-27     155417.0      341.0   \n",
       "47243      NGA    Africa  Nigeria  2021-02-28     155657.0      240.0   \n",
       "\n",
       "       new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  ...  \\\n",
       "46877                 NaN           NaN         NaN                  NaN  ...   \n",
       "46878                 NaN           NaN         NaN                  NaN  ...   \n",
       "46879                 NaN           NaN         NaN                  NaN  ...   \n",
       "46880                 NaN           NaN         NaN                  NaN  ...   \n",
       "46881                 NaN           NaN         NaN                  NaN  ...   \n",
       "...                   ...           ...         ...                  ...  ...   \n",
       "47239             639.000        1885.0        11.0               14.000  ...   \n",
       "47240             604.286        1891.0         6.0               12.571  ...   \n",
       "47241             595.429        1902.0        11.0               12.714  ...   \n",
       "47242             552.000        1905.0         3.0               10.571  ...   \n",
       "47243             511.857        1907.0         2.0                9.714  ...   \n",
       "\n",
       "       gdp_per_capita  extreme_poverty  cardiovasc_death_rate  \\\n",
       "46877        5338.454              NaN                181.013   \n",
       "46878        5338.454              NaN                181.013   \n",
       "46879        5338.454              NaN                181.013   \n",
       "46880        5338.454              NaN                181.013   \n",
       "46881        5338.454              NaN                181.013   \n",
       "...               ...              ...                    ...   \n",
       "47239        5338.454              NaN                181.013   \n",
       "47240        5338.454              NaN                181.013   \n",
       "47241        5338.454              NaN                181.013   \n",
       "47242        5338.454              NaN                181.013   \n",
       "47243        5338.454              NaN                181.013   \n",
       "\n",
       "       diabetes_prevalence  female_smokers  male_smokers  \\\n",
       "46877                 2.42             0.6          10.8   \n",
       "46878                 2.42             0.6          10.8   \n",
       "46879                 2.42             0.6          10.8   \n",
       "46880                 2.42             0.6          10.8   \n",
       "46881                 2.42             0.6          10.8   \n",
       "...                    ...             ...           ...   \n",
       "47239                 2.42             0.6          10.8   \n",
       "47240                 2.42             0.6          10.8   \n",
       "47241                 2.42             0.6          10.8   \n",
       "47242                 2.42             0.6          10.8   \n",
       "47243                 2.42             0.6          10.8   \n",
       "\n",
       "       handwashing_facilities  hospital_beds_per_thousand  life_expectancy  \\\n",
       "46877                  41.949                         NaN            54.69   \n",
       "46878                  41.949                         NaN            54.69   \n",
       "46879                  41.949                         NaN            54.69   \n",
       "46880                  41.949                         NaN            54.69   \n",
       "46881                  41.949                         NaN            54.69   \n",
       "...                       ...                         ...              ...   \n",
       "47239                  41.949                         NaN            54.69   \n",
       "47240                  41.949                         NaN            54.69   \n",
       "47241                  41.949                         NaN            54.69   \n",
       "47242                  41.949                         NaN            54.69   \n",
       "47243                  41.949                         NaN            54.69   \n",
       "\n",
       "       human_development_index  \n",
       "46877                    0.539  \n",
       "46878                    0.539  \n",
       "46879                    0.539  \n",
       "46880                    0.539  \n",
       "46881                    0.539  \n",
       "...                        ...  \n",
       "47239                    0.539  \n",
       "47240                    0.539  \n",
       "47241                    0.539  \n",
       "47242                    0.539  \n",
       "47243                    0.539  \n",
       "\n",
       "[367 rows x 59 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.query(\"location == 'Nigeria'\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "assigned-satellite",
   "metadata": {},
   "source": [
    "## Plotting graphs with Plotly"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bulgarian-pearl",
   "metadata": {},
   "source": [
    "### Using Plotly Express\n",
    "\n",
    "Documentation: https://plotly.com/python/plotly-express/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "detected-spiritual",
   "metadata": {},
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\"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"date\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"total_cases\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('6ddd1a7b-871e-43eb-bcd8-9b55c90571b6');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_px = px.line(df.query(\"location == 'Nigeria'\"), x='date', y=\"total_cases\")\n",
    "fig_px.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "supported-deadline",
   "metadata": {},
   "source": [
    "### Creating multiple plots in one graph with Plotly \n",
    "\n",
    "Documentation: https://plotly.com/python/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "future-knowing",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df = df.query(\"location == 'Nigeria'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "brief-client",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "mode": "lines",
         "name": "New Cases per million",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
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          "2020-03-08",
          "2020-03-09",
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          "2020-03-12",
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          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
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          "2020-03-20",
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          "2020-05-12",
          "2020-05-13",
          "2020-05-14",
          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
          "2020-05-18",
          "2020-05-19",
          "2020-05-20",
          "2020-05-21",
          "2020-05-22",
          "2020-05-23",
          "2020-05-24",
          "2020-05-25",
          "2020-05-26",
          "2020-05-27",
          "2020-05-28",
          "2020-05-29",
          "2020-05-30",
          "2020-05-31",
          "2020-06-01",
          "2020-06-02",
          "2020-06-03",
          "2020-06-04",
          "2020-06-05",
          "2020-06-06",
          "2020-06-07",
          "2020-06-08",
          "2020-06-09",
          "2020-06-10",
          "2020-06-11",
          "2020-06-12",
          "2020-06-13",
          "2020-06-14",
          "2020-06-15",
          "2020-06-16",
          "2020-06-17",
          "2020-06-18",
          "2020-06-19",
          "2020-06-20",
          "2020-06-21",
          "2020-06-22",
          "2020-06-23",
          "2020-06-24",
          "2020-06-25",
          "2020-06-26",
          "2020-06-27",
          "2020-06-28",
          "2020-06-29",
          "2020-06-30",
          "2020-07-01",
          "2020-07-02",
          "2020-07-03",
          "2020-07-04",
          "2020-07-05",
          "2020-07-06",
          "2020-07-07",
          "2020-07-08",
          "2020-07-09",
          "2020-07-10",
          "2020-07-11",
          "2020-07-12",
          "2020-07-13",
          "2020-07-14",
          "2020-07-15",
          "2020-07-16",
          "2020-07-17",
          "2020-07-18",
          "2020-07-19",
          "2020-07-20",
          "2020-07-21",
          "2020-07-22",
          "2020-07-23",
          "2020-07-24",
          "2020-07-25",
          "2020-07-26",
          "2020-07-27",
          "2020-07-28",
          "2020-07-29",
          "2020-07-30",
          "2020-07-31",
          "2020-08-01",
          "2020-08-02",
          "2020-08-03",
          "2020-08-04",
          "2020-08-05",
          "2020-08-06",
          "2020-08-07",
          "2020-08-08",
          "2020-08-09",
          "2020-08-10",
          "2020-08-11",
          "2020-08-12",
          "2020-08-13",
          "2020-08-14",
          "2020-08-15",
          "2020-08-16",
          "2020-08-17",
          "2020-08-18",
          "2020-08-19",
          "2020-08-20",
          "2020-08-21",
          "2020-08-22",
          "2020-08-23",
          "2020-08-24",
          "2020-08-25",
          "2020-08-26",
          "2020-08-27",
          "2020-08-28",
          "2020-08-29",
          "2020-08-30",
          "2020-08-31",
          "2020-09-01",
          "2020-09-02",
          "2020-09-03",
          "2020-09-04",
          "2020-09-05",
          "2020-09-06",
          "2020-09-07",
          "2020-09-08",
          "2020-09-09",
          "2020-09-10",
          "2020-09-11",
          "2020-09-12",
          "2020-09-13",
          "2020-09-14",
          "2020-09-15",
          "2020-09-16",
          "2020-09-17",
          "2020-09-18",
          "2020-09-19",
          "2020-09-20",
          "2020-09-21",
          "2020-09-22",
          "2020-09-23",
          "2020-09-24",
          "2020-09-25",
          "2020-09-26",
          "2020-09-27",
          "2020-09-28",
          "2020-09-29",
          "2020-09-30",
          "2020-10-01",
          "2020-10-02",
          "2020-10-03",
          "2020-10-04",
          "2020-10-05",
          "2020-10-06",
          "2020-10-07",
          "2020-10-08",
          "2020-10-09",
          "2020-10-10",
          "2020-10-11",
          "2020-10-12",
          "2020-10-13",
          "2020-10-14",
          "2020-10-15",
          "2020-10-16",
          "2020-10-17",
          "2020-10-18",
          "2020-10-19",
          "2020-10-20",
          "2020-10-21",
          "2020-10-22",
          "2020-10-23",
          "2020-10-24",
          "2020-10-25",
          "2020-10-26",
          "2020-10-27",
          "2020-10-28",
          "2020-10-29",
          "2020-10-30",
          "2020-10-31",
          "2020-11-01",
          "2020-11-02",
          "2020-11-03",
          "2020-11-04",
          "2020-11-05",
          "2020-11-06",
          "2020-11-07",
          "2020-11-08",
          "2020-11-09",
          "2020-11-10",
          "2020-11-11",
          "2020-11-12",
          "2020-11-13",
          "2020-11-14",
          "2020-11-15",
          "2020-11-16",
          "2020-11-17",
          "2020-11-18",
          "2020-11-19",
          "2020-11-20",
          "2020-11-21",
          "2020-11-22",
          "2020-11-23",
          "2020-11-24",
          "2020-11-25",
          "2020-11-26",
          "2020-11-27",
          "2020-11-28",
          "2020-11-29",
          "2020-11-30",
          "2020-12-01",
          "2020-12-02",
          "2020-12-03",
          "2020-12-04",
          "2020-12-05",
          "2020-12-06",
          "2020-12-07",
          "2020-12-08",
          "2020-12-09",
          "2020-12-10",
          "2020-12-11",
          "2020-12-12",
          "2020-12-13",
          "2020-12-14",
          "2020-12-15",
          "2020-12-16",
          "2020-12-17",
          "2020-12-18",
          "2020-12-19",
          "2020-12-20",
          "2020-12-21",
          "2020-12-22",
          "2020-12-23",
          "2020-12-24",
          "2020-12-25",
          "2020-12-26",
          "2020-12-27",
          "2020-12-28",
          "2020-12-29",
          "2020-12-30",
          "2020-12-31",
          "2021-01-01",
          "2021-01-02",
          "2021-01-03",
          "2021-01-04",
          "2021-01-05",
          "2021-01-06",
          "2021-01-07",
          "2021-01-08",
          "2021-01-09",
          "2021-01-10",
          "2021-01-11",
          "2021-01-12",
          "2021-01-13",
          "2021-01-14",
          "2021-01-15",
          "2021-01-16",
          "2021-01-17",
          "2021-01-18",
          "2021-01-19",
          "2021-01-20",
          "2021-01-21",
          "2021-01-22",
          "2021-01-23",
          "2021-01-24",
          "2021-01-25",
          "2021-01-26",
          "2021-01-27",
          "2021-01-28",
          "2021-01-29",
          "2021-01-30",
          "2021-01-31",
          "2021-02-01",
          "2021-02-02",
          "2021-02-03",
          "2021-02-04",
          "2021-02-05",
          "2021-02-06",
          "2021-02-07",
          "2021-02-08",
          "2021-02-09",
          "2021-02-10",
          "2021-02-11",
          "2021-02-12",
          "2021-02-13",
          "2021-02-14",
          "2021-02-15",
          "2021-02-16",
          "2021-02-17",
          "2021-02-18",
          "2021-02-19",
          "2021-02-20",
          "2021-02-21",
          "2021-02-22",
          "2021-02-23",
          "2021-02-24",
          "2021-02-25",
          "2021-02-26",
          "2021-02-27",
          "2021-02-28"
         ],
         "y": [
          0.005,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0.005,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0.005,
          0.024,
          0,
          0.019,
          0.049,
          0.039,
          0.049,
          0.019,
          0.034,
          0.068,
          0.024,
          0.092,
          0.107,
          0.097,
          0.019,
          0.189,
          0.049,
          0.126,
          0.019,
          0.087,
          0.029,
          0.078,
          0.107,
          0.058,
          0.082,
          0.063,
          0.024,
          0.097,
          0.146,
          0.165,
          0.17,
          0.247,
          0.238,
          0.412,
          0.184,
          0,
          1.009,
          0.524,
          0.553,
          0.422,
          0.441,
          0.31,
          0.946,
          0.951,
          0.99,
          1.155,
          1.058,
          0.825,
          1.184,
          0.718,
          0.946,
          1.848,
          1.873,
          1.159,
          1.203,
          1.174,
          0.708,
          0.893,
          0.927,
          1.397,
          0.83,
          1.64,
          1.048,
          1.096,
          1.339,
          1.645,
          1.189,
          1.286,
          1.518,
          1.111,
          1.339,
          1.887,
          0.883,
          1.877,
          2.683,
          1.489,
          2.018,
          1.169,
          1.683,
          1.698,
          1.591,
          1.887,
          1.227,
          1.528,
          3.216,
          1.984,
          3.304,
          3.042,
          2.43,
          1.955,
          2.78,
          2.377,
          2.848,
          3.614,
          3.236,
          3.207,
          2.115,
          3.274,
          2.193,
          3.148,
          2.882,
          3.318,
          3.779,
          2.377,
          2.746,
          2.721,
          3.832,
          3.037,
          2.202,
          2.925,
          2.639,
          2.789,
          2.44,
          2.231,
          2.421,
          2.789,
          3.221,
          2.77,
          2.886,
          2.246,
          3.119,
          2.886,
          2.911,
          3.168,
          2.697,
          2.726,
          2.794,
          2.634,
          2.93,
          2.867,
          2.125,
          2.692,
          3.144,
          3.027,
          1.96,
          2.333,
          2.241,
          1.873,
          1.475,
          1.397,
          1.475,
          2.217,
          1.717,
          2.149,
          2.198,
          2.12,
          1.407,
          2.052,
          2.198,
          1.809,
          1.596,
          1.577,
          1.446,
          2.023,
          1.989,
          2.877,
          2.309,
          1.649,
          2.916,
          1.562,
          1.557,
          1.222,
          1.072,
          1.436,
          0.776,
          1.213,
          0.669,
          0.694,
          1.159,
          1.048,
          0.606,
          0.752,
          0.786,
          0.485,
          0.752,
          1.436,
          0.854,
          0.956,
          0.912,
          0.776,
          0.383,
          0.64,
          0.437,
          0.611,
          0.635,
          1.072,
          0.917,
          0.471,
          0.946,
          0.854,
          0.538,
          0.606,
          1.033,
          0.66,
          0.611,
          0.66,
          0.907,
          0.975,
          0.742,
          0.611,
          0.776,
          0.281,
          0.582,
          0.572,
          0.752,
          0.5,
          0.733,
          0.538,
          0.791,
          0.796,
          1.091,
          0.868,
          0.718,
          1.028,
          0.548,
          0.645,
          0.572,
          0.349,
          0.179,
          0.669,
          0.374,
          0.233,
          0.301,
          0.577,
          0.548,
          0.713,
          0.728,
          0.825,
          0.786,
          0.538,
          0.349,
          0.665,
          0.752,
          0.873,
          1.082,
          0.286,
          1.455,
          0.456,
          0.737,
          0.873,
          1.028,
          0.757,
          0.543,
          0.737,
          0.762,
          0.737,
          1.145,
          0.708,
          0.694,
          1.193,
          0.752,
          0.272,
          0.815,
          0.961,
          0.82,
          1.193,
          0.534,
          0.398,
          0.703,
          1.363,
          0.592,
          1.664,
          1.572,
          1.504,
          1.543,
          1.892,
          2.668,
          2.299,
          3.274,
          3.861,
          2.993,
          2.028,
          0.965,
          3.677,
          4.512,
          5.554,
          3.91,
          4.463,
          2.43,
          1.727,
          4.846,
          5.496,
          5.05,
          3.803,
          4.022,
          4.065,
          1.926,
          3.633,
          4.929,
          5.001,
          4.754,
          2.794,
          4.448,
          6.166,
          6.568,
          8.072,
          7.592,
          7.49,
          7.689,
          4.968,
          6.035,
          6.161,
          6.782,
          7.175,
          9.057,
          7.752,
          7.005,
          7.844,
          6.311,
          6.724,
          9.528,
          7.194,
          11.953,
          4.676,
          6.937,
          6.321,
          9.028,
          4.191,
          8.004,
          9.135,
          3.323,
          3.279,
          7.927,
          5.521,
          6.5,
          7.878,
          7.704,
          2.455,
          3.119,
          5.123,
          5.487,
          4.55,
          4.875,
          5.545,
          2.523,
          3.609,
          6.636,
          5.205,
          4.254,
          3.211,
          3.129,
          2.527,
          2.629,
          2.77,
          3.177,
          3.076,
          2.911,
          1.654,
          1.164
         ]
        },
        {
         "mode": "lines",
         "name": "Total Deaths per million",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
          "2020-03-07",
          "2020-03-08",
          "2020-03-09",
          "2020-03-10",
          "2020-03-11",
          "2020-03-12",
          "2020-03-13",
          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
          "2020-03-19",
          "2020-03-20",
          "2020-03-21",
          "2020-03-22",
          "2020-03-23",
          "2020-03-24",
          "2020-03-25",
          "2020-03-26",
          "2020-03-27",
          "2020-03-28",
          "2020-03-29",
          "2020-03-30",
          "2020-03-31",
          "2020-04-01",
          "2020-04-02",
          "2020-04-03",
          "2020-04-04",
          "2020-04-05",
          "2020-04-06",
          "2020-04-07",
          "2020-04-08",
          "2020-04-09",
          "2020-04-10",
          "2020-04-11",
          "2020-04-12",
          "2020-04-13",
          "2020-04-14",
          "2020-04-15",
          "2020-04-16",
          "2020-04-17",
          "2020-04-18",
          "2020-04-19",
          "2020-04-20",
          "2020-04-21",
          "2020-04-22",
          "2020-04-23",
          "2020-04-24",
          "2020-04-25",
          "2020-04-26",
          "2020-04-27",
          "2020-04-28",
          "2020-04-29",
          "2020-04-30",
          "2020-05-01",
          "2020-05-02",
          "2020-05-03",
          "2020-05-04",
          "2020-05-05",
          "2020-05-06",
          "2020-05-07",
          "2020-05-08",
          "2020-05-09",
          "2020-05-10",
          "2020-05-11",
          "2020-05-12",
          "2020-05-13",
          "2020-05-14",
          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
          "2020-05-18",
          "2020-05-19",
          "2020-05-20",
          "2020-05-21",
          "2020-05-22",
          "2020-05-23",
          "2020-05-24",
          "2020-05-25",
          "2020-05-26",
          "2020-05-27",
          "2020-05-28",
          "2020-05-29",
          "2020-05-30",
          "2020-05-31",
          "2020-06-01",
          "2020-06-02",
          "2020-06-03",
          "2020-06-04",
          "2020-06-05",
          "2020-06-06",
          "2020-06-07",
          "2020-06-08",
          "2020-06-09",
          "2020-06-10",
          "2020-06-11",
          "2020-06-12",
          "2020-06-13",
          "2020-06-14",
          "2020-06-15",
          "2020-06-16",
          "2020-06-17",
          "2020-06-18",
          "2020-06-19",
          "2020-06-20",
          "2020-06-21",
          "2020-06-22",
          "2020-06-23",
          "2020-06-24",
          "2020-06-25",
          "2020-06-26",
          "2020-06-27",
          "2020-06-28",
          "2020-06-29",
          "2020-06-30",
          "2020-07-01",
          "2020-07-02",
          "2020-07-03",
          "2020-07-04",
          "2020-07-05",
          "2020-07-06",
          "2020-07-07",
          "2020-07-08",
          "2020-07-09",
          "2020-07-10",
          "2020-07-11",
          "2020-07-12",
          "2020-07-13",
          "2020-07-14",
          "2020-07-15",
          "2020-07-16",
          "2020-07-17",
          "2020-07-18",
          "2020-07-19",
          "2020-07-20",
          "2020-07-21",
          "2020-07-22",
          "2020-07-23",
          "2020-07-24",
          "2020-07-25",
          "2020-07-26",
          "2020-07-27",
          "2020-07-28",
          "2020-07-29",
          "2020-07-30",
          "2020-07-31",
          "2020-08-01",
          "2020-08-02",
          "2020-08-03",
          "2020-08-04",
          "2020-08-05",
          "2020-08-06",
          "2020-08-07",
          "2020-08-08",
          "2020-08-09",
          "2020-08-10",
          "2020-08-11",
          "2020-08-12",
          "2020-08-13",
          "2020-08-14",
          "2020-08-15",
          "2020-08-16",
          "2020-08-17",
          "2020-08-18",
          "2020-08-19",
          "2020-08-20",
          "2020-08-21",
          "2020-08-22",
          "2020-08-23",
          "2020-08-24",
          "2020-08-25",
          "2020-08-26",
          "2020-08-27",
          "2020-08-28",
          "2020-08-29",
          "2020-08-30",
          "2020-08-31",
          "2020-09-01",
          "2020-09-02",
          "2020-09-03",
          "2020-09-04",
          "2020-09-05",
          "2020-09-06",
          "2020-09-07",
          "2020-09-08",
          "2020-09-09",
          "2020-09-10",
          "2020-09-11",
          "2020-09-12",
          "2020-09-13",
          "2020-09-14",
          "2020-09-15",
          "2020-09-16",
          "2020-09-17",
          "2020-09-18",
          "2020-09-19",
          "2020-09-20",
          "2020-09-21",
          "2020-09-22",
          "2020-09-23",
          "2020-09-24",
          "2020-09-25",
          "2020-09-26",
          "2020-09-27",
          "2020-09-28",
          "2020-09-29",
          "2020-09-30",
          "2020-10-01",
          "2020-10-02",
          "2020-10-03",
          "2020-10-04",
          "2020-10-05",
          "2020-10-06",
          "2020-10-07",
          "2020-10-08",
          "2020-10-09",
          "2020-10-10",
          "2020-10-11",
          "2020-10-12",
          "2020-10-13",
          "2020-10-14",
          "2020-10-15",
          "2020-10-16",
          "2020-10-17",
          "2020-10-18",
          "2020-10-19",
          "2020-10-20",
          "2020-10-21",
          "2020-10-22",
          "2020-10-23",
          "2020-10-24",
          "2020-10-25",
          "2020-10-26",
          "2020-10-27",
          "2020-10-28",
          "2020-10-29",
          "2020-10-30",
          "2020-10-31",
          "2020-11-01",
          "2020-11-02",
          "2020-11-03",
          "2020-11-04",
          "2020-11-05",
          "2020-11-06",
          "2020-11-07",
          "2020-11-08",
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\"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('ff46b197-3b8a-46fc-b43a-1601d7b78e96');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig =  go.Figure()\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['new_cases_per_million'], mode='lines', \n",
    "                         name='New Cases per million'))\n",
    "\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_deaths_per_million'], mode='lines', \n",
    "                         name='Total Deaths per million'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "supreme-helmet",
   "metadata": {},
   "source": [
    "### Multiple Axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "drawn-niagara",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "mode": "lines",
         "name": "New Cases per million",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
          "2020-03-07",
          "2020-03-08",
          "2020-03-09",
          "2020-03-10",
          "2020-03-11",
          "2020-03-12",
          "2020-03-13",
          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
          "2020-03-19",
          "2020-03-20",
          "2020-03-21",
          "2020-03-22",
          "2020-03-23",
          "2020-03-24",
          "2020-03-25",
          "2020-03-26",
          "2020-03-27",
          "2020-03-28",
          "2020-03-29",
          "2020-03-30",
          "2020-03-31",
          "2020-04-01",
          "2020-04-02",
          "2020-04-03",
          "2020-04-04",
          "2020-04-05",
          "2020-04-06",
          "2020-04-07",
          "2020-04-08",
          "2020-04-09",
          "2020-04-10",
          "2020-04-11",
          "2020-04-12",
          "2020-04-13",
          "2020-04-14",
          "2020-04-15",
          "2020-04-16",
          "2020-04-17",
          "2020-04-18",
          "2020-04-19",
          "2020-04-20",
          "2020-04-21",
          "2020-04-22",
          "2020-04-23",
          "2020-04-24",
          "2020-04-25",
          "2020-04-26",
          "2020-04-27",
          "2020-04-28",
          "2020-04-29",
          "2020-04-30",
          "2020-05-01",
          "2020-05-02",
          "2020-05-03",
          "2020-05-04",
          "2020-05-05",
          "2020-05-06",
          "2020-05-07",
          "2020-05-08",
          "2020-05-09",
          "2020-05-10",
          "2020-05-11",
          "2020-05-12",
          "2020-05-13",
          "2020-05-14",
          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
          "2020-05-18",
          "2020-05-19",
          "2020-05-20",
          "2020-05-21",
          "2020-05-22",
          "2020-05-23",
          "2020-05-24",
          "2020-05-25",
          "2020-05-26",
          "2020-05-27",
          "2020-05-28",
          "2020-05-29",
          "2020-05-30",
          "2020-05-31",
          "2020-06-01",
          "2020-06-02",
          "2020-06-03",
          "2020-06-04",
          "2020-06-05",
          "2020-06-06",
          "2020-06-07",
          "2020-06-08",
          "2020-06-09",
          "2020-06-10",
          "2020-06-11",
          "2020-06-12",
          "2020-06-13",
          "2020-06-14",
          "2020-06-15",
          "2020-06-16",
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          "2020-06-18",
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          "2020-03-01",
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          "2020-03-03",
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{\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 0.94]}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}, \"yaxis2\": {\"anchor\": \"x\", \"overlaying\": \"y\", \"side\": \"right\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('9dd81a62-b2d5-4332-a1bd-b8aec74421c2');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig =  make_subplots(specs=[[{\"secondary_y\": True}]])\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['new_cases_per_million'], mode='lines', \n",
    "                         name='New Cases per million'), secondary_y=False,)\n",
    "# fig.update_xaxes(type=\"log\")\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_deaths_per_million'], mode='lines', \n",
    "                         name='Total Deaths per million'), secondary_y=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sexual-nickname",
   "metadata": {},
   "source": [
    "### Log Scale Y axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "challenging-comparative",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "mode": "lines",
         "name": "Total Cases",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
          "2020-03-07",
          "2020-03-08",
          "2020-03-09",
          "2020-03-10",
          "2020-03-11",
          "2020-03-12",
          "2020-03-13",
          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
          "2020-03-19",
          "2020-03-20",
          "2020-03-21",
          "2020-03-22",
          "2020-03-23",
          "2020-03-24",
          "2020-03-25",
          "2020-03-26",
          "2020-03-27",
          "2020-03-28",
          "2020-03-29",
          "2020-03-30",
          "2020-03-31",
          "2020-04-01",
          "2020-04-02",
          "2020-04-03",
          "2020-04-04",
          "2020-04-05",
          "2020-04-06",
          "2020-04-07",
          "2020-04-08",
          "2020-04-09",
          "2020-04-10",
          "2020-04-11",
          "2020-04-12",
          "2020-04-13",
          "2020-04-14",
          "2020-04-15",
          "2020-04-16",
          "2020-04-17",
          "2020-04-18",
          "2020-04-19",
          "2020-04-20",
          "2020-04-21",
          "2020-04-22",
          "2020-04-23",
          "2020-04-24",
          "2020-04-25",
          "2020-04-26",
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          "2020-05-03",
          "2020-05-04",
          "2020-05-05",
          "2020-05-06",
          "2020-05-07",
          "2020-05-08",
          "2020-05-09",
          "2020-05-10",
          "2020-05-11",
          "2020-05-12",
          "2020-05-13",
          "2020-05-14",
          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
          "2020-05-18",
          "2020-05-19",
          "2020-05-20",
          "2020-05-21",
          "2020-05-22",
          "2020-05-23",
          "2020-05-24",
          "2020-05-25",
          "2020-05-26",
          "2020-05-27",
          "2020-05-28",
          "2020-05-29",
          "2020-05-30",
          "2020-05-31",
          "2020-06-01",
          "2020-06-02",
          "2020-06-03",
          "2020-06-04",
          "2020-06-05",
          "2020-06-06",
          "2020-06-07",
          "2020-06-08",
          "2020-06-09",
          "2020-06-10",
          "2020-06-11",
          "2020-06-12",
          "2020-06-13",
          "2020-06-14",
          "2020-06-15",
          "2020-06-16",
          "2020-06-17",
          "2020-06-18",
          "2020-06-19",
          "2020-06-20",
          "2020-06-21",
          "2020-06-22",
          "2020-06-23",
          "2020-06-24",
          "2020-06-25",
          "2020-06-26",
          "2020-06-27",
          "2020-06-28",
          "2020-06-29",
          "2020-06-30",
          "2020-07-01",
          "2020-07-02",
          "2020-07-03",
          "2020-07-04",
          "2020-07-05",
          "2020-07-06",
          "2020-07-07",
          "2020-07-08",
          "2020-07-09",
          "2020-07-10",
          "2020-07-11",
          "2020-07-12",
          "2020-07-13",
          "2020-07-14",
          "2020-07-15",
          "2020-07-16",
          "2020-07-17",
          "2020-07-18",
          "2020-07-19",
          "2020-07-20",
          "2020-07-21",
          "2020-07-22",
          "2020-07-23",
          "2020-07-24",
          "2020-07-25",
          "2020-07-26",
          "2020-07-27",
          "2020-07-28",
          "2020-07-29",
          "2020-07-30",
          "2020-07-31",
          "2020-08-01",
          "2020-08-02",
          "2020-08-03",
          "2020-08-04",
          "2020-08-05",
          "2020-08-06",
          "2020-08-07",
          "2020-08-08",
          "2020-08-09",
          "2020-08-10",
          "2020-08-11",
          "2020-08-12",
          "2020-08-13",
          "2020-08-14",
          "2020-08-15",
          "2020-08-16",
          "2020-08-17",
          "2020-08-18",
          "2020-08-19",
          "2020-08-20",
          "2020-08-21",
          "2020-08-22",
          "2020-08-23",
          "2020-08-24",
          "2020-08-25",
          "2020-08-26",
          "2020-08-27",
          "2020-08-28",
          "2020-08-29",
          "2020-08-30",
          "2020-08-31",
          "2020-09-01",
          "2020-09-02",
          "2020-09-03",
          "2020-09-04",
          "2020-09-05",
          "2020-09-06",
          "2020-09-07",
          "2020-09-08",
          "2020-09-09",
          "2020-09-10",
          "2020-09-11",
          "2020-09-12",
          "2020-09-13",
          "2020-09-14",
          "2020-09-15",
          "2020-09-16",
          "2020-09-17",
          "2020-09-18",
          "2020-09-19",
          "2020-09-20",
          "2020-09-21",
          "2020-09-22",
          "2020-09-23",
          "2020-09-24",
          "2020-09-25",
          "2020-09-26",
          "2020-09-27",
          "2020-09-28",
          "2020-09-29",
          "2020-09-30",
          "2020-10-01",
          "2020-10-02",
          "2020-10-03",
          "2020-10-04",
          "2020-10-05",
          "2020-10-06",
          "2020-10-07",
          "2020-10-08",
          "2020-10-09",
          "2020-10-10",
          "2020-10-11",
          "2020-10-12",
          "2020-10-13",
          "2020-10-14",
          "2020-10-15",
          "2020-10-16",
          "2020-10-17",
          "2020-10-18",
          "2020-10-19",
          "2020-10-20",
          "2020-10-21",
          "2020-10-22",
          "2020-10-23",
          "2020-10-24",
          "2020-10-25",
          "2020-10-26",
          "2020-10-27",
          "2020-10-28",
          "2020-10-29",
          "2020-10-30",
          "2020-10-31",
          "2020-11-01",
          "2020-11-02",
          "2020-11-03",
          "2020-11-04",
          "2020-11-05",
          "2020-11-06",
          "2020-11-07",
          "2020-11-08",
          "2020-11-09",
          "2020-11-10",
          "2020-11-11",
          "2020-11-12",
          "2020-11-13",
          "2020-11-14",
          "2020-11-15",
          "2020-11-16",
          "2020-11-17",
          "2020-11-18",
          "2020-11-19",
          "2020-11-20",
          "2020-11-21",
          "2020-11-22",
          "2020-11-23",
          "2020-11-24",
          "2020-11-25",
          "2020-11-26",
          "2020-11-27",
          "2020-11-28",
          "2020-11-29",
          "2020-11-30",
          "2020-12-01",
          "2020-12-02",
          "2020-12-03",
          "2020-12-04",
          "2020-12-05",
          "2020-12-06",
          "2020-12-07",
          "2020-12-08",
          "2020-12-09",
          "2020-12-10",
          "2020-12-11",
          "2020-12-12",
          "2020-12-13",
          "2020-12-14",
          "2020-12-15",
          "2020-12-16",
          "2020-12-17",
          "2020-12-18",
          "2020-12-19",
          "2020-12-20",
          "2020-12-21",
          "2020-12-22",
          "2020-12-23",
          "2020-12-24",
          "2020-12-25",
          "2020-12-26",
          "2020-12-27",
          "2020-12-28",
          "2020-12-29",
          "2020-12-30",
          "2020-12-31",
          "2021-01-01",
          "2021-01-02",
          "2021-01-03",
          "2021-01-04",
          "2021-01-05",
          "2021-01-06",
          "2021-01-07",
          "2021-01-08",
          "2021-01-09",
          "2021-01-10",
          "2021-01-11",
          "2021-01-12",
          "2021-01-13",
          "2021-01-14",
          "2021-01-15",
          "2021-01-16",
          "2021-01-17",
          "2021-01-18",
          "2021-01-19",
          "2021-01-20",
          "2021-01-21",
          "2021-01-22",
          "2021-01-23",
          "2021-01-24",
          "2021-01-25",
          "2021-01-26",
          "2021-01-27",
          "2021-01-28",
          "2021-01-29",
          "2021-01-30",
          "2021-01-31",
          "2021-02-01",
          "2021-02-02",
          "2021-02-03",
          "2021-02-04",
          "2021-02-05",
          "2021-02-06",
          "2021-02-07",
          "2021-02-08",
          "2021-02-09",
          "2021-02-10",
          "2021-02-11",
          "2021-02-12",
          "2021-02-13",
          "2021-02-14",
          "2021-02-15",
          "2021-02-16",
          "2021-02-17",
          "2021-02-18",
          "2021-02-19",
          "2021-02-20",
          "2021-02-21",
          "2021-02-22",
          "2021-02-23",
          "2021-02-24",
          "2021-02-25",
          "2021-02-26",
          "2021-02-27",
          "2021-02-28"
         ],
         "y": [
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          2,
          2,
          2,
          2,
          2,
          2,
          2,
          2,
          3,
          8,
          8,
          12,
          22,
          30,
          40,
          44,
          51,
          65,
          70,
          89,
          111,
          131,
          135,
          174,
          184,
          210,
          214,
          232,
          238,
          254,
          276,
          288,
          305,
          318,
          323,
          343,
          373,
          407,
          442,
          493,
          542,
          627,
          665,
          665,
          873,
          981,
          1095,
          1182,
          1273,
          1337,
          1532,
          1728,
          1932,
          2170,
          2388,
          2558,
          2802,
          2950,
          3145,
          3526,
          3912,
          4151,
          4399,
          4641,
          4787,
          4971,
          5162,
          5450,
          5621,
          5959,
          6175,
          6401,
          6677,
          7016,
          7261,
          7526,
          7839,
          8068,
          8344,
          8733,
          8915,
          9302,
          9855,
          10162,
          10578,
          10819,
          11166,
          11516,
          11844,
          12233,
          12486,
          12801,
          13464,
          13873,
          14554,
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          15682,
          16085,
          16658,
          17148,
          17735,
          18480,
          19147,
          19808,
          20244,
          20919,
          21371,
          22020,
          22614,
          23298,
          24077,
          24567,
          25133,
          25694,
          26484,
          27110,
          27564,
          28167,
          28711,
          29286,
          29789,
          30249,
          30748,
          31323,
          31987,
          32558,
          33153,
          33616,
          34259,
          34854,
          35454,
          36107,
          36663,
          37225,
          37801,
          38344,
          38948,
          39539,
          39977,
          40532,
          41180,
          41804,
          42208,
          42689,
          43151,
          43537,
          43841,
          44129,
          44433,
          44890,
          45244,
          45687,
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          153842,
          154476,
          155076,
          155417,
          155657
         ]
        },
        {
         "mode": "lines",
         "name": "Total Deaths",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
          "2020-03-07",
          "2020-03-08",
          "2020-03-09",
          "2020-03-10",
          "2020-03-11",
          "2020-03-12",
          "2020-03-13",
          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
          "2020-03-19",
          "2020-03-20",
          "2020-03-21",
          "2020-03-22",
          "2020-03-23",
          "2020-03-24",
          "2020-03-25",
          "2020-03-26",
          "2020-03-27",
          "2020-03-28",
          "2020-03-29",
          "2020-03-30",
          "2020-03-31",
          "2020-04-01",
          "2020-04-02",
          "2020-04-03",
          "2020-04-04",
          "2020-04-05",
          "2020-04-06",
          "2020-04-07",
          "2020-04-08",
          "2020-04-09",
          "2020-04-10",
          "2020-04-11",
          "2020-04-12",
          "2020-04-13",
          "2020-04-14",
          "2020-04-15",
          "2020-04-16",
          "2020-04-17",
          "2020-04-18",
          "2020-04-19",
          "2020-04-20",
          "2020-04-21",
          "2020-04-22",
          "2020-04-23",
          "2020-04-24",
          "2020-04-25",
          "2020-04-26",
          "2020-04-27",
          "2020-04-28",
          "2020-04-29",
          "2020-04-30",
          "2020-05-01",
          "2020-05-02",
          "2020-05-03",
          "2020-05-04",
          "2020-05-05",
          "2020-05-06",
          "2020-05-07",
          "2020-05-08",
          "2020-05-09",
          "2020-05-10",
          "2020-05-11",
          "2020-05-12",
          "2020-05-13",
          "2020-05-14",
          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
          "2020-05-18",
          "2020-05-19",
          "2020-05-20",
          "2020-05-21",
          "2020-05-22",
          "2020-05-23",
          "2020-05-24",
          "2020-05-25",
          "2020-05-26",
          "2020-05-27",
          "2020-05-28",
          "2020-05-29",
          "2020-05-30",
          "2020-05-31",
          "2020-06-01",
          "2020-06-02",
          "2020-06-03",
          "2020-06-04",
          "2020-06-05",
          "2020-06-06",
          "2020-06-07",
          "2020-06-08",
          "2020-06-09",
          "2020-06-10",
          "2020-06-11",
          "2020-06-12",
          "2020-06-13",
          "2020-06-14",
          "2020-06-15",
          "2020-06-16",
          "2020-06-17",
          "2020-06-18",
          "2020-06-19",
          "2020-06-20",
          "2020-06-21",
          "2020-06-22",
          "2020-06-23",
          "2020-06-24",
          "2020-06-25",
          "2020-06-26",
          "2020-06-27",
          "2020-06-28",
          "2020-06-29",
          "2020-06-30",
          "2020-07-01",
          "2020-07-02",
          "2020-07-03",
          "2020-07-04",
          "2020-07-05",
          "2020-07-06",
          "2020-07-07",
          "2020-07-08",
          "2020-07-09",
          "2020-07-10",
          "2020-07-11",
          "2020-07-12",
          "2020-07-13",
          "2020-07-14",
          "2020-07-15",
          "2020-07-16",
          "2020-07-17",
          "2020-07-18",
          "2020-07-19",
          "2020-07-20",
          "2020-07-21",
          "2020-07-22",
          "2020-07-23",
          "2020-07-24",
          "2020-07-25",
          "2020-07-26",
          "2020-07-27",
          "2020-07-28",
          "2020-07-29",
          "2020-07-30",
          "2020-07-31",
          "2020-08-01",
          "2020-08-02",
          "2020-08-03",
          "2020-08-04",
          "2020-08-05",
          "2020-08-06",
          "2020-08-07",
          "2020-08-08",
          "2020-08-09",
          "2020-08-10",
          "2020-08-11",
          "2020-08-12",
          "2020-08-13",
          "2020-08-14",
          "2020-08-15",
          "2020-08-16",
          "2020-08-17",
          "2020-08-18",
          "2020-08-19",
          "2020-08-20",
          "2020-08-21",
          "2020-08-22",
          "2020-08-23",
          "2020-08-24",
          "2020-08-25",
          "2020-08-26",
          "2020-08-27",
          "2020-08-28",
          "2020-08-29",
          "2020-08-30",
          "2020-08-31",
          "2020-09-01",
          "2020-09-02",
          "2020-09-03",
          "2020-09-04",
          "2020-09-05",
          "2020-09-06",
          "2020-09-07",
          "2020-09-08",
          "2020-09-09",
          "2020-09-10",
          "2020-09-11",
          "2020-09-12",
          "2020-09-13",
          "2020-09-14",
          "2020-09-15",
          "2020-09-16",
          "2020-09-17",
          "2020-09-18",
          "2020-09-19",
          "2020-09-20",
          "2020-09-21",
          "2020-09-22",
          "2020-09-23",
          "2020-09-24",
          "2020-09-25",
          "2020-09-26",
          "2020-09-27",
          "2020-09-28",
          "2020-09-29",
          "2020-09-30",
          "2020-10-01",
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          "2020-10-03",
          "2020-10-04",
          "2020-10-05",
          "2020-10-06",
          "2020-10-07",
          "2020-10-08",
          "2020-10-09",
          "2020-10-10",
          "2020-10-11",
          "2020-10-12",
          "2020-10-13",
          "2020-10-14",
          "2020-10-15",
          "2020-10-16",
          "2020-10-17",
          "2020-10-18",
          "2020-10-19",
          "2020-10-20",
          "2020-10-21",
          "2020-10-22",
          "2020-10-23",
          "2020-10-24",
          "2020-10-25",
          "2020-10-26",
          "2020-10-27",
          "2020-10-28",
          "2020-10-29",
          "2020-10-30",
          "2020-10-31",
          "2020-11-01",
          "2020-11-02",
          "2020-11-03",
          "2020-11-04",
          "2020-11-05",
          "2020-11-06",
          "2020-11-07",
          "2020-11-08",
          "2020-11-09",
          "2020-11-10",
          "2020-11-11",
          "2020-11-12",
          "2020-11-13",
          "2020-11-14",
          "2020-11-15",
          "2020-11-16",
          "2020-11-17",
          "2020-11-18",
          "2020-11-19",
          "2020-11-20",
          "2020-11-21",
          "2020-11-22",
          "2020-11-23",
          "2020-11-24",
          "2020-11-25",
          "2020-11-26",
          "2020-11-27",
          "2020-11-28",
          "2020-11-29",
          "2020-11-30",
          "2020-12-01",
          "2020-12-02",
          "2020-12-03",
          "2020-12-04",
          "2020-12-05",
          "2020-12-06",
          "2020-12-07",
          "2020-12-08",
          "2020-12-09",
          "2020-12-10",
          "2020-12-11",
          "2020-12-12",
          "2020-12-13",
          "2020-12-14",
          "2020-12-15",
          "2020-12-16",
          "2020-12-17",
          "2020-12-18",
          "2020-12-19",
          "2020-12-20",
          "2020-12-21",
          "2020-12-22",
          "2020-12-23",
          "2020-12-24",
          "2020-12-25",
          "2020-12-26",
          "2020-12-27",
          "2020-12-28",
          "2020-12-29",
          "2020-12-30",
          "2020-12-31",
          "2021-01-01",
          "2021-01-02",
          "2021-01-03",
          "2021-01-04",
          "2021-01-05",
          "2021-01-06",
          "2021-01-07",
          "2021-01-08",
          "2021-01-09",
          "2021-01-10",
          "2021-01-11",
          "2021-01-12",
          "2021-01-13",
          "2021-01-14",
          "2021-01-15",
          "2021-01-16",
          "2021-01-17",
          "2021-01-18",
          "2021-01-19",
          "2021-01-20",
          "2021-01-21",
          "2021-01-22",
          "2021-01-23",
          "2021-01-24",
          "2021-01-25",
          "2021-01-26",
          "2021-01-27",
          "2021-01-28",
          "2021-01-29",
          "2021-01-30",
          "2021-01-31",
          "2021-02-01",
          "2021-02-02",
          "2021-02-03",
          "2021-02-04",
          "2021-02-05",
          "2021-02-06",
          "2021-02-07",
          "2021-02-08",
          "2021-02-09",
          "2021-02-10",
          "2021-02-11",
          "2021-02-12",
          "2021-02-13",
          "2021-02-14",
          "2021-02-15",
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     "metadata": {},
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   ],
   "source": [
    "fig =  go.Figure()\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_cases'], mode='lines', \n",
    "                         name='Total Cases'))\n",
    "\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_deaths'], mode='lines', \n",
    "                         name='Total Deaths'))\n",
    "# fig.update_yaxes(type=\"log\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "southern-leisure",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "config": {
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          "2020-09-19",
          "2020-09-20",
          "2020-09-21",
          "2020-09-22",
          "2020-09-23",
          "2020-09-24",
          "2020-09-25",
          "2020-09-26",
          "2020-09-27",
          "2020-09-28",
          "2020-09-29",
          "2020-09-30",
          "2020-10-01",
          "2020-10-02",
          "2020-10-03",
          "2020-10-04",
          "2020-10-05",
          "2020-10-06",
          "2020-10-07",
          "2020-10-08",
          "2020-10-09",
          "2020-10-10",
          "2020-10-11",
          "2020-10-12",
          "2020-10-13",
          "2020-10-14",
          "2020-10-15",
          "2020-10-16",
          "2020-10-17",
          "2020-10-18",
          "2020-10-19",
          "2020-10-20",
          "2020-10-21",
          "2020-10-22",
          "2020-10-23",
          "2020-10-24",
          "2020-10-25",
          "2020-10-26",
          "2020-10-27",
          "2020-10-28",
          "2020-10-29",
          "2020-10-30",
          "2020-10-31",
          "2020-11-01",
          "2020-11-02",
          "2020-11-03",
          "2020-11-04",
          "2020-11-05",
          "2020-11-06",
          "2020-11-07",
          "2020-11-08",
          "2020-11-09",
          "2020-11-10",
          "2020-11-11",
          "2020-11-12",
          "2020-11-13",
          "2020-11-14",
          "2020-11-15",
          "2020-11-16",
          "2020-11-17",
          "2020-11-18",
          "2020-11-19",
          "2020-11-20",
          "2020-11-21",
          "2020-11-22",
          "2020-11-23",
          "2020-11-24",
          "2020-11-25",
          "2020-11-26",
          "2020-11-27",
          "2020-11-28",
          "2020-11-29",
          "2020-11-30",
          "2020-12-01",
          "2020-12-02",
          "2020-12-03",
          "2020-12-04",
          "2020-12-05",
          "2020-12-06",
          "2020-12-07",
          "2020-12-08",
          "2020-12-09",
          "2020-12-10",
          "2020-12-11",
          "2020-12-12",
          "2020-12-13",
          "2020-12-14",
          "2020-12-15",
          "2020-12-16",
          "2020-12-17",
          "2020-12-18",
          "2020-12-19",
          "2020-12-20",
          "2020-12-21",
          "2020-12-22",
          "2020-12-23",
          "2020-12-24",
          "2020-12-25",
          "2020-12-26",
          "2020-12-27",
          "2020-12-28",
          "2020-12-29",
          "2020-12-30",
          "2020-12-31",
          "2021-01-01",
          "2021-01-02",
          "2021-01-03",
          "2021-01-04",
          "2021-01-05",
          "2021-01-06",
          "2021-01-07",
          "2021-01-08",
          "2021-01-09",
          "2021-01-10",
          "2021-01-11",
          "2021-01-12",
          "2021-01-13",
          "2021-01-14",
          "2021-01-15",
          "2021-01-16",
          "2021-01-17",
          "2021-01-18",
          "2021-01-19",
          "2021-01-20",
          "2021-01-21",
          "2021-01-22",
          "2021-01-23",
          "2021-01-24",
          "2021-01-25",
          "2021-01-26",
          "2021-01-27",
          "2021-01-28",
          "2021-01-29",
          "2021-01-30",
          "2021-01-31",
          "2021-02-01",
          "2021-02-02",
          "2021-02-03",
          "2021-02-04",
          "2021-02-05",
          "2021-02-06",
          "2021-02-07",
          "2021-02-08",
          "2021-02-09",
          "2021-02-10",
          "2021-02-11",
          "2021-02-12",
          "2021-02-13",
          "2021-02-14",
          "2021-02-15",
          "2021-02-16",
          "2021-02-17",
          "2021-02-18",
          "2021-02-19",
          "2021-02-20",
          "2021-02-21",
          "2021-02-22",
          "2021-02-23",
          "2021-02-24",
          "2021-02-25",
          "2021-02-26",
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          "2021-02-28"
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          2,
          2,
          2,
          3,
          8,
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          12,
          22,
          30,
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          51,
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          70,
          89,
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          131,
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          174,
          184,
          210,
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          254,
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        },
        {
         "mode": "lines",
         "name": "Total Deaths",
         "type": "scatter",
         "x": [
          "2020-02-28",
          "2020-02-29",
          "2020-03-01",
          "2020-03-02",
          "2020-03-03",
          "2020-03-04",
          "2020-03-05",
          "2020-03-06",
          "2020-03-07",
          "2020-03-08",
          "2020-03-09",
          "2020-03-10",
          "2020-03-11",
          "2020-03-12",
          "2020-03-13",
          "2020-03-14",
          "2020-03-15",
          "2020-03-16",
          "2020-03-17",
          "2020-03-18",
          "2020-03-19",
          "2020-03-20",
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          "2020-04-03",
          "2020-04-04",
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          "2020-04-06",
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          "2020-04-08",
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          "2020-04-17",
          "2020-04-18",
          "2020-04-19",
          "2020-04-20",
          "2020-04-21",
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          "2020-05-05",
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          "2020-05-13",
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          "2020-05-15",
          "2020-05-16",
          "2020-05-17",
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          "2020-05-21",
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          "2020-05-23",
          "2020-05-24",
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          "2020-06-21",
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          "2020-07-16",
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          "2021-01-18",
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          "2021-02-10",
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          "2021-02-14",
          "2021-02-15",
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          "2021-02-18",
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          "2021-02-21",
          "2021-02-22",
          "2021-02-23",
          "2021-02-24",
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   "source": [
    "fig =  go.Figure()\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_cases'], mode='lines', \n",
    "                         name='Total Cases'))\n",
    "\n",
    "fig.add_trace(go.Scatter(x=test_df['date'], y=test_df['total_deaths'], mode='lines', \n",
    "                         name='Total Deaths'))\n",
    "fig.update_yaxes(type=\"log\")"
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    "## Dash dashboard\n",
    "Switch to the *app.py* file, open this in your prefered IDE.\n",
    "### Exercises\n",
    "The goal is to try to replicate the covid dashboard on the site [Our World in Data.](https://ourworldindata.org/coronavirus-data-explorer?zoomToSelection=true&time=2020-03-01..latest&country=USA~GBR~CAN~DEU~ITA~IND&region=World&cfrMetric=true&interval=smoothed&perCapita=true&smoothing=7&pickerMetric=location&pickerSort=asc) The are features we need to add to make this happen are:\n",
    " - **Ability to filter by date**\n",
    " - **Ability to view multiple countries**\n",
    " - **Ability to have a log scale**\n",
    " - **Ability to select which metric to look at**\n",
    " - **Ability to look at multiple metrics together**\n",
    " - **Create a heatmap of the world with the daily cases**"
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