python-cheatsheet/web/update_plots.py at main · gto76/python-cheatsheet · GitHub

Name: python-cheatsheet/web/update_plots.py at main · gto76/python-cheatsheet · GitHub
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#!/usr/bin/env python3
#
# Usage: ./update_plots.py
# Updates plots from the Plotly section so they show the latest data.

frompathlibimportPath
importdatetime
importpandasaspd
fromplotly.expressimportline
importplotly.graph_objectsasgo
importre


defmain():
print('Updating covid deaths...')
update_covid_deaths()
print('Updating covid cases...')
update_confirmed_cases()


defupdate_covid_deaths():
covid=pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
usecols=['iso_code', 'date', 'total_deaths', 'population'])
continents=pd.read_csv('https://gist.githubusercontent.com/stevewithington/20a69c0b6d2ff'
'846ea5d35e5fc47f26c/raw/country-and-continent-codes-list-csv.csv',
usecols=['Three_Letter_Country_Code', 'Continent_Name'])
df=pd.merge(covid, continents, left_on='iso_code', right_on='Three_Letter_Country_Code')
df=df.groupby(['Continent_Name', 'date']).sum().reset_index()
df['Total Deaths per Million'] =round(df.total_deaths*1e6/df.population)
today=str(datetime.date.today())
df=df[('2020-02-22'<df.date) & (df.date<today)]
df=df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns')
gb=df.groupby('Continent')
df['Max Total Deaths'] =gb[['Total Deaths per Million']].transform('max')
df=df.sort_values(['Max Total Deaths', 'Date'], ascending=[False, True])
f=line(df, x='Date', y='Total Deaths per Million', color='Continent')
f.update_layout(margin=dict(t=24, b=0), paper_bgcolor='rgba(0, 0, 0, 0)')
update_file('covid_deaths.js', f)
f.layout.paper_bgcolor='rgb(255, 255, 255)'
write_to_png_file('covid_deaths.png', f, width=960, height=340)


defupdate_confirmed_cases():
defmain():
df=wrangle_data(*scrape_data())
f=get_figure(df)
update_file('covid_cases.js', f)
f.layout.paper_bgcolor='rgb(255, 255, 255)'
write_to_png_file('covid_cases.png', f, width=960, height=315)

defscrape_data():
defscrape_covid():
url='https://covid.ourworldindata.org/data/owid-covid-data.csv'
df=pd.read_csv(url, usecols=['location', 'date', 'total_cases'])
returndf[df.location=='World'].set_index('date').total_cases
defscrape_yahoo(slug):
url=f'https://query1.finance.yahoo.com/v7/finance/download/{slug}'+ \
'?period1=1579651200&period2=9999999999&interval=1d&events=history'
df=pd.read_csv(url, usecols=['Date', 'Close'])
returndf.set_index('Date').Close
out= [scrape_covid(), scrape_yahoo('BTC-USD'), scrape_yahoo('GC=F'),
scrape_yahoo('^DJI')]
returnmap(pd.Series.rename, out, ['Total Cases', 'Bitcoin', 'Gold', 'Dow Jones'])

defwrangle_data(covid, bitcoin, gold, dow):
df=pd.concat([dow, gold, bitcoin], axis=1) # Joins columns on dates.
df=df.sort_index().interpolate() # Sorts by date and interpolates NaN-s.
yesterday=str(datetime.date.today() -datetime.timedelta(1))
df=df.loc['2020-02-23':yesterday] # Discards rows before '2020-02-23'.
df=round((df/df.iloc[0]) *100, 2) # Calculates percentages relative to day 1
df=df.join(covid) # Adds column with covid cases.
returndf.sort_values(df.index[-1], axis=1) # Sorts columns by last day's value.

defget_figure(df):
figure=go.Figure()
forcol_nameinreversed(df.columns):
yaxis='y1'ifcol_name=='Total Cases'else'y2'
colors= {'Total Cases': '#EF553B', 'Bitcoin': '#636efa', 'Gold': '#FFA15A',
'Dow Jones': '#00cc96'}
trace=go.Scatter(x=df.index, y=df[col_name], name=col_name, yaxis=yaxis,
line=dict(color=colors[col_name]))
figure.add_trace(trace)
figure.update_layout(
yaxis1=dict(title='Total Cases', rangemode='tozero'),
yaxis2=dict(title='%', rangemode='tozero', overlaying='y', side='right'),
legend=dict(x=1.1),
margin=dict(t=24, b=0),
paper_bgcolor='rgba(0, 0, 0, 0)'
 )
returnfigure

main()


###
## UTIL
#

defupdate_file(filename, figure):
lines=read_file(filename)
f_json=figure.to_json(pretty=True).replace('\n', '\n ')
out=lines[:6] + [f' {f_json}\n', ' )\n', '};\n']
write_to_file(filename, out)


defread_file(filename):
p=Path(__file__).resolve().parent/filename
withopen(p, encoding='utf-8') asfile:
returnfile.readlines()


defwrite_to_file(filename, lines):
p=Path(__file__).resolve().parent/filename
withopen(p, 'w', encoding='utf-8') asfile:
file.writelines(lines)


defwrite_to_png_file(filename, figure, width, height):
p=Path(__file__).resolve().parent/filename
figure.write_image(str(p), width=width, height=height)


if__name__=='__main__':
main()