Micah P. Dombrowski / Mar 18 2020
COVID-19 Growth By State (US)
Growth of COVID-19 for the US by State.
#hide
%matplotlib inline
import requests
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
states_url = "https://covidtracking.com/api/states/daily"
us_url = "https://covidtracking.com/api/us/daily"
case_threshold = 100
3.3s
Python
#hide
r = requests.get(states_url)
states_df = pd.DataFrame(r.json())
states_df['date'] = pd.to_datetime(states_df.date, format="%Y%m%d")
states_df = states_df[['date', 'state', 'positive']].sort_values('date')
cols = {}
for state in states_df.state.unique():
cases = states_df[(states_df.state == state) & (states_df.positive > 100)]
cases = cases.reset_index().positive.reset_index(drop=True)
if len(cases):
cols[state] = cases
r = requests.get(us_url)
us_df = pd.DataFrame(r.json())
us_df['date'] = pd.to_datetime(us_df.date, format="%Y%m%d")
us_df = us_df[['date', 'positive']].sort_values('date')
cols['US'] = us_df.positive.reset_index(drop=True)
1.7s
Python
#collapse-hide
fig = plt.figure(figsize=(13.4, 9.54))
ax = plt.axes()
pd.concat(cols, axis=1).plot(ax=ax, marker='o')
plt.title('COVID19 Growth in US as a whole and by state')
plt.ylabel('Cumulative confirmed cases')
plt.xlabel(f'Number of days since {case_threshold}th case')
plt.annotate('Based on COVID Data Repository by the COVID Tracking Project\n'
f'Latest data from {states_df.date.max().strftime("%Y-%m-%d")}, varies by state\n'
'Chart by Avy Faingezicht, @avyfain',
(0.07, 0.02), xycoords='figure fraction', fontsize=10);
plt.legend(loc="lower right")
x = np.linspace(0, plt.xlim()[1])
plt.plot(x, 100 * (1.33) ** x, ls='--', color='k', label='33% daily growth')
plt.annotate('33% Daily Growth',
(0.85, 0.75), xycoords='figure fraction', fontsize=10);
formatter = ScalarFormatter()
formatter.set_scientific(False)
ax.yaxis.set_major_formatter(formatter)
ax.yaxis.set_minor_formatter(formatter)
1.0s
Python
Same Chart, Y-Axis On A Log Scale
#collapse-hide
fig = plt.figure(figsize=(13.4, 9.54))
ax = plt.axes()
pd.concat(cols, axis=1).plot(ax=ax, marker='o', logy=True)
plt.title('COVID19 Growth in US as a whole and by state')
plt.ylabel('Cumulative confirmed cases (log scale)')
plt.xlabel(f'Number of days since {case_threshold}th case')
plt.annotate('Based on COVID Data Repository by The COVID Tracking Project\n'
f'Latest data from {states_df.date.max().strftime("%Y-%m-%d")}, varies by state\n'
'Chart by Avy Faingezicht, @avyfain',
(0.07, 0.02), xycoords='figure fraction', fontsize=10);
plt.legend(loc="lower right")
plt.plot(x, 100 * (1.33) ** x, ls='--', color='k', label='33% daily growth')
plt.annotate('33% Daily Growth',
(0.85, 0.75), xycoords='figure fraction', fontsize=10);
ax.yaxis.set_major_formatter(formatter)
ax.yaxis.set_minor_formatter(formatter)
1.0s
Python
Updated hourly by GitHub Actions.
This visualization was made by Avy Faingezicht[^1].
[^1]: Data sourced from "The COVID Tracking Project". Link to original notebook.