Simple (but grim) example of using Matplotlib and Pandas for data visualization

covid-data.py

import matplotlib.pyplot as plt
import pandas as pd

#
# Read data and compute some summaries:
#
data = pd.read_csv('covid-data.csv')

data['Total'] = data['New'].cumsum()
data['Deceased'] = data['Deaths'].cumsum()
data['Recovered'] = data['Recoveries'].cumsum()
data['Hospitalized'] = data['Hospitalizations'].cumsum()
data['Active'] = data['Total']-data['Recovered']-data['Deceased']

#
# Construct two plots: one for daily accumulation (new vs total)
# and one for active vs recovered, etc.
#
fig, ax = plt.subplots(2, constrained_layout=True)
fig.suptitle('COVID-19 cases in Newfoundland and Labrador',
             fontsize=14, fontweight='bold')

data.plot.area(ax=ax[0], x='Date', y=['Deceased', 'Recovered', 'Active'],
               color=['dimgrey', 'mediumturquoise', 'lightcoral'],
               title='Total cases by category')

data.plot(ax=ax[1], x='Date', y=['Total', 'New'], title='New and total cases')

# Show the results!
plt.show()