def make_jhu_country_cases_chart(override_props) -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
jhu_df = jhu_df[(jhu_df.Province_State.isnull()) & (jhu_df.Country_Region != 'China')]
#qcsv = './data/quarantine-activity-Apr19.csv'
qcsv = './data/quarantine-activity-world-new-export.csv'
days_since = 50
groupcol = 'Country_Region'
chart = CovidChart(
jhu_df,
groupcol=groupcol,
start_criterion=DaysSinceNumReached(days_since, 'Confirmed'),
ycol='Confirmed',
level='country',
xcol='Date',
top_k_groups=30,
sample_every=3,
quarantine_df=qcsv
)
# chart.set_colormap()
chart.set_unfocused_opacity(0.05)
chart = chart.set_ytitle('Number of Confirmed Cases (log scale)')
chart = chart.set_xtitle(['Days since {} Confirmed'.format(days_since), '(Events prior to Day 0 not shown)'])
chart.set_width(600).set_height(400)
chart.set_ydomain((days_since, 1000000))
chart.set_xdomain((0, 72 + EXTRA_DAYS_TO_INCLUDE))
chart.click_selection_init = first_alphabetic_group(chart._preprocess_df(), groupcol)
chart = _maybe_add_staging_props(chart)
chart.spec.update(override_props)
return chart
def make_jhu_state_deaths_chart(override_props) -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
jhu_df = jhu_df.loc[(jhu_df.Country_Region == 'United States') & jhu_df.Province_State.notnull()]
if STAGING:
level = 'usa'
#qcsv = './data/quarantine-activity-US-Apr16.csv'
qcsv = './data/combined-activity-US-Jun9.csv'
else:
level = 'usa_old'
qcsv = './data/quarantine-activity-US.csv'
days_since = 10
groupcol = 'Province_State'
chart = CovidChart(
jhu_df,
groupcol=groupcol,
start_criterion=DaysSinceNumReached(days_since, 'Deaths'),
ycol='Deaths',
xcol='Date',
level=level,
top_k_groups=30,
sample_every=3,
quarantine_df=qcsv # should have a column with same name as `groupcol`
)
chart = chart.set_ytitle('Number of Deaths (log scale)')
chart = chart.set_xtitle(['Days since {} Deaths'.format(days_since), '(Events prior to Day 0 not shown)'])
chart.set_width(600).set_height(400)
chart.set_ydomain((days_since, 100000))
chart.set_xdomain((0, 47 + EXTRA_DAYS_TO_INCLUDE))
chart.click_selection_init = first_alphabetic_group(chart._preprocess_df(), groupcol)
chart = _maybe_add_staging_props(chart)
chart.spec.update(override_props)
return chart
def make_jhu_selected_state_chart(override_props) -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
# grab us-specific
jhu_df = jhu_df[(jhu_df.Country_Region == 'United States') & jhu_df.Province_State.notnull()]
# jhu_df[(nyt_df["state"]=="Illinois")|(nyt_df["state"]=="New York")| (nyt_df["state"]=="New Jersey")| (nyt_df["state"]=="Washington")| (nyt_df["state"]=="Michigan")]
days_since = 20
chart = CovidChart(
jhu_df,
groupcol='Province_State',
start_criterion=DaysSinceNumReached(days_since, 'Confirmed'),
ycol='Confirmed',
level='USA',
xcol='Date',
top_k_groups=20,
quarantine_df = './data/combined-activity-US-Jun9.csv'
#quarantine_df='./data/quarantine-activity-US.csv' # should have a column with same name as `groupcol`
)
# chart.set_colormap()
chart.set_unfocused_opacity(0.05)
chart = chart.set_ytitle('Number of Confirmed Cases (log scale)')
chart = chart.set_xtitle(['Days since {} Confirmed'.format(days_since), '(Events prior to Day 0 not shown)'])
chart.set_width(250).set_height(400)
chart.set_xdomain((0, 35)).set_ydomain((days_since, 100000))
chart.set_title("States With Significant Rate Decreases")
chart = _maybe_add_staging_props(chart)
chart.spec.update(override_props)
return chart
def make_jhu_country_deaths_chart(override_props) -> CovidChart:
jhu_df = pd.read_csv("./data/jhu-data.csv")
jhu_df = jhu_df.loc[(jhu_df.Country_Region != 'China') & jhu_df.Province_State.isnull()]
qcsv = './data/quarantine-activity-Apr19.csv'
days_since = 10
groupcol = 'Country_Region'
chart = CovidChart(
jhu_df,
groupcol=groupcol,
start_criterion=DaysSinceNumReached(days_since, 'Deaths'),
ycol='Deaths',
xcol='Date',
level='country',
top_k_groups=30,
sample_every=3,
quarantine_df=qcsv
)
chart = chart.set_ytitle('Number of Deaths (log scale)')
chart = chart.set_xtitle(['Days since {} Deaths'.format(days_since),'(Events prior to Day 0 not shown)'])
chart.set_width(600).set_height(400)
chart.set_ydomain((days_since, 100000))
chart.set_xdomain((0, 62 + EXTRA_DAYS_TO_INCLUDE))
chart.click_selection_init = first_alphabetic_group(chart._preprocess_df(), groupcol)
chart = _maybe_add_staging_props(chart)
chart.spec.update(override_props)
return chart
def make_jhu_country_chart() -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
jhu_df = jhu_df[(jhu_df.Province_State.isnull())
& (jhu_df.Country_Region != 'China')]
days_since = 50
chart = CovidChart(
jhu_df,
groupcol='Country_Region',
start_criterion=DaysSinceNumReached(days_since, 'Confirmed'),
ycol='Confirmed',
chart_type='country',
xcol='Date',
top_k_groups=20,
quarantine_df=
'./data/quarantine-activity.csv' # should have a column with same name as `groupcol`
)
# chart.set_colormap()
chart.set_unfocused_opacity(0.05)
chart = chart.set_ytitle('Number of Confirmed Cases (log)')
chart = chart.set_xtitle('Days since {} Confirmed'.format(days_since))
chart.set_width(600).set_height(400)
chart.set_ydomain((days_since, 200000))
chart.set_xdomain((0, 40))
return chart
def make_jhu_state_chart() -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
# grab us-specific
jhu_df = jhu_df[(jhu_df.Country_Region == 'United States')
& jhu_df.Province_State.notnull()]
days_since = 20
chart = CovidChart(
jhu_df,
groupcol='Province_State',
start_criterion=DaysSinceNumReached(days_since, 'Confirmed'),
ycol='Confirmed',
chart_type='USA',
xcol='Date',
top_k_groups=20,
quarantine_df=
'./data/quarantine-activity-US.csv' # should have a column with same name as `groupcol`
)
# chart.set_colormap()
chart.set_unfocused_opacity(0.05)
chart = chart.set_ytitle('Number of Confirmed Cases (log)')
chart = chart.set_xtitle('Days since {} Confirmed'.format(days_since))
chart.set_width(600).set_height(400)
chart.set_xdomain((0, 30)).set_ydomain((days_since, 100000))
return chart
def make_jhu_state_cases_chart(override_props) -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
# grab us-specific
jhu_df = jhu_df[(jhu_df.Country_Region == 'United States')
& jhu_df.Province_State.notnull()]
if STAGING:
level = 'usa'
qcsv = './data/quarantine-activity-US-Apr16.csv'
else:
level = 'usa_old'
qcsv = './data/quarantine-activity-US.csv'
days_since = 20
groupcol = 'Province_State'
chart = CovidChart(
jhu_df,
groupcol=groupcol,
start_criterion=DaysSinceNumReached(days_since, 'Confirmed'),
ycol='Confirmed',
level=level,
xcol='Date',
top_k_groups=30,
quarantine_df=qcsv # should have a column with same name as `groupcol`
)
# chart.set_colormap()
chart.set_unfocused_opacity(0.05)
chart = chart.set_ytitle('Number of Confirmed Cases (log scale)')
chart = chart.set_xtitle([
'Days since {} Confirmed'.format(days_since),
'(Events prior to Day 0 not shown)'
])
chart.set_width(600).set_height(400)
chart.set_xdomain((0, 47 + EXTRA_DAYS_TO_INCLUDE)).set_ydomain(
(days_since, 200000))
chart.click_selection_init = first_alphabetic_group(
chart._preprocess_df(), groupcol)
chart = _maybe_add_staging_props(chart)
chart.spec.update(override_props)
return chart
def make_jhu_state_death_chart() -> CovidChart:
jhu_df = pd.read_csv('./data/jhu-data.csv')
jhu_df = jhu_df.loc[(jhu_df.Country_Region == 'United States')
& jhu_df.Province_State.notnull()]
chart = CovidChart(
jhu_df,
groupcol='Province_State',
start_criterion=DaysSinceNumReached(10, 'Deaths'),
ycol='Deaths',
xcol='Date',
chart_type='usa',
top_k_groups=20,
quarantine_df=
'./data/quarantine-activity-us.csv' # should have a column with same name as `groupcol`
)
chart = chart.set_ytitle('Number of Deaths (log)')
chart = chart.set_xtitle('Days since 10 Deaths')
chart.set_width(600).set_height(400)
chart.set_ydomain((10, 10000))
chart.set_xdomain((0, 25)).compile()
return chart