covid data plots

covid.py

import requests
import matplotlib.pyplot as plt
import time


def main():
    response = requests.get('https://covidtracking.com/api/states/daily')
    data = response.json()
    fig, subplots = plt.subplots(2, 2)
    figure_row = 0
    
    number_of_early_days_to_eliminate = 3
    
    for state in ['NY', 'NJ']:
        data_for_state = list(filter(lambda d: d['state'] == state, data))
        data_for_state = data_for_state[:-number_of_early_days_to_eliminate]
        
        data_for_state.reverse()
        dates = list(map(lambda d: str(d['date']), data_for_state))

        positive_cases = list(map(lambda d: d['positive'], data_for_state))
        percent_changes_on_day = calculate_pct_change_on_day(positive_cases)

        state_infected_rate_plot = subplots[figure_row][1]
        state_infected_rate_plot.bar(dates[:-1], percent_changes_on_day)

        state_infected_rate_plot.set_xlabel('Date')
        state_infected_rate_plot.set_title(
            '%s infection %% change from prior day\nlatest=%0.2f' % (state, percent_changes_on_day[-1]))
        state_infected_rate_plot.set_aspect('auto')

        state_infected_plot = subplots[figure_row][0]
        state_infected_plot.bar(dates, positive_cases)

        state_infected_plot.set_xlabel('Date')
        state_infected_plot.set_title('%s infected (latest=%s)' % (state, positive_cases[-1]))
        state_infected_plot.set_aspect('auto')
        figure_row = figure_row + 1

    for ax in fig.axes:
        plt.sca(ax)
        plt.xticks(rotation=90)

    fig.tight_layout()
    fig.suptitle('data from https://covidtracking.com\niain toft (https://github.com/tofti)', fontsize=14)

    fig.show()
    fig.set_size_inches(12, 10)
    fig.savefig(str(int(round(time.time() * 1000))) + ".png")


def calculate_pct_change_on_day(data):
    percent_changes_on_day = []
    for i in range(len(data) - 1, 0, -1):
        percent_change_on_day = 100.0 * (data[i] - data[i - 1]) / data[i - 1]
        percent_changes_on_day.insert(0, percent_change_on_day)
    return percent_changes_on_day


if __name__ == "__main__":
    # execute only if run as a script
    main()