king_county_covid.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jul 21 07:44:21 2020

@author: serge
"""

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns


sns.set(context='talk')

date = 'feb-17'

#########
#url = f'https://www.kingcounty.gov/depts/health/covid-19/data/~/media/depts/health/communicable-diseases/documents/C19/data/daily-counts-and-rate-{date}.ashx'
url = f'https://www.kingcounty.gov/depts/health/covid-19/data/~/media/depts/health/communicable-diseases/documents/C19/data/total-counts-by-date-city-{date}.ashx'
df1 = pd.read_excel(url, 'Positives')
flag = (df1['Result_Date'] >= '2020-03-01') & (df1['City'] == 'Seattle')
df1 = df1[flag]
df2 = pd.read_excel(url, 'Hospitalizations')[flag]
df3 = pd.read_excel(url, 'Deaths')[flag]

df1.plot(x='Result_Date', y='Positive_Rate', figsize=(20, 8), title='Seattle Daily Positive Rate')

ax = df2.plot(x='Admission_Date', y='HospitalizationRate', figsize=(20, 8))
df3.plot(ax=ax, x='Death_Date', y='Death_Rate', title='Seattle Daily Hospitalization and Death Rates')
 
#########
url = f'https://www.kingcounty.gov/depts/health/covid-19/data/~/media/depts/health/communicable-diseases/documents/C19/data/biweekly-counts-rates-by-geography-{date}.ashx'
df = pd.read_excel(url, 'ZIP')
df = df[df['ZIP'] == 98115]

df.plot(x='Week_End', y='Positive_Rate', figsize=(20, 8), title='98115 Biweekly Counts')

ax = df.plot(x='Week_End', y='Hospitalizations', figsize=(20, 8))
df.plot(ax=ax, x='Week_End', y='Deaths', title='98115 biweekly data')


#########
url = f'https://www.kingcounty.gov/depts/health/covid-19/data/~/media/depts/health/communicable-diseases/documents/C19/data/weekly-counts-by-date-all-demographics-{date}.ashx'
df = pd.read_excel(url, 'Age Group')
df['Week_Start'] = df['Week'].apply(lambda s: s.split(' - ')[0])
df['Week_Start'] = pd.to_datetime(df['Week_Start'])
df['Week_End'] = df['Week'].apply(lambda s: s.split(' - ')[1])
df['Week_End'] = pd.to_datetime(df['Week_End'])

fig, ax = plt.subplots(figsize=(20, 8))
for label, df_sub in df.groupby('Age_Group'):
    df_sub.plot(x='Week_End', y='Positives', ax=ax, label=label)
plt.legend()
plt.title('King County Weekly Positive Counts')
plt.show()

fig, ax = plt.subplots(figsize=(20, 8))
for label, df_sub in df.groupby('Age_Group'):
    df_sub.plot(x='Week_End', y='Hospitalizations', ax=ax, label=label)
plt.legend()
plt.title('King County Weekly Hospitalizations Counts')
plt.show()

fig, ax = plt.subplots(figsize=(20, 8))
for label, df_sub in df.groupby('Age_Group'):
    df_sub.plot(x='Week_End', y='Deaths', ax=ax, label=label)
plt.legend()
plt.title('King County Weekly Deaths Counts')
plt.show()