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_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
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_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_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_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_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