def update_graph(selected_dropdown_value):
fig = viz_map.plot_hospital_severity_slider(
df, target_days=np.array(NUM_DAYS_LIST),
df_county=df_county, counties_json=counties_json, dark=True,
auto_open=False, plot=False,
county_filter=selected_dropdown_value
)
return fig
width=900,
height=600,
scale=2)
print('successfully updated png of map of deaths')
# load in hospital data and merge
df_hospital = load_data.load_hospital_level(
data_dir=oj(os.path.dirname(parentdir), 'covid-19-private-data'))
df = merge_data.merge_county_and_hosp(df_county, df_hospital)
df = severity_index.add_severity_index(df, NUM_DAYS_LIST)
# load counties geojson
# counties_json = json.load(open(oj(parentdir, 'data', 'geojson-counties-fips.json'), "r"))
# create hospital-level severity index plot
severity_fig = viz_map.plot_hospital_severity_slider(
df,
target_days=np.array(NUM_DAYS_LIST),
plot_choropleth=False,
dark=True,
auto_open=False,
filename=oj(parentdir, 'results', 'severity_map.html'))
print('successfully updated map of severity index')
severity_fig.write_image(oj(parentdir, 'results', 'severity_map.png'),
width=900,
height=600,
scale=2)
print('successfully updated png of map of severity index')
)
county_lat_lon['fips'] = (county_lat_lon['STATEFP'] + county_lat_lon['COUNTYFP'])#.astype(np.int64)
# add predictions
NUM_DAYS_LIST = [1, 2, 3, 4, 5]
df_county = add_preds(df_county, NUM_DAYS_LIST=NUM_DAYS_LIST, cached_dir=data_dir)
# join lat / lon to df_county
# This does not seem necessary as lat and lon is already in the df_county
#df_county = df_county.join(county_lat_lon.set_index('fips'), on='countyFIPS', how='left').rename(
# columns={'LATITUDE': 'lat', 'LONGITUDE': 'lon'}
#)
# create county-level predictions plot
viz_map.plot_counties_slider(df_county, auto_open=False,
n_past_days=1,
target_days=np.array(NUM_DAYS_LIST),
filename=oj(parentdir, 'results', 'deaths.html'))
# load in hospital data and merge
df_hospital = load_data.load_hospital_level(data_dir=oj(parentdir, 'data_hospital_level'))
df = merge_data.merge_county_and_hosp(df_county, df_hospital)
df = severity_index.add_severity_index(df, NUM_DAYS_LIST)
# load counties geojson
counties_json = json.load(open(oj(parentdir, 'data', 'geojson-counties-fips.json'), "r"))
# create hospital-level severity index plot
viz_map.plot_hospital_severity_slider(
df, target_days=np.array(NUM_DAYS_LIST),
df_county=df_county, counties_json=counties_json, dark=True,
auto_open=False, filename=oj(parentdir, 'results', 'severity_map.html')
)
df_county = add_preds(df_county, NUM_DAYS_LIST=NUM_DAYS_LIST, cached_dir=data_dir)
# load in hospital data and merge
df_hospital = load_data.load_hospital_level(
data_dir=oj(os.path.dirname(rootdir), 'covid-19-private-data')
)
df = merge_data.merge_county_and_hosp(df_county, df_hospital)
df = severity_index.add_severity_index(df, NUM_DAYS_LIST)
# load counties geojson
counties_json = json.load(open(oj(rootdir, 'data', 'geojson-counties-fips.json'), "r"))
# create hospital-level severity index plot
fig = viz_map.plot_hospital_severity_slider(
df, target_days=np.array(NUM_DAYS_LIST),
df_county=df_county, counties_json=counties_json, dark=True,
auto_open=False, plot=False
)
app = dash.Dash('app', server=server)
app.scripts.config.serve_locally = False
dcc._js_dist[0]['external_url'] = 'https://cdn.plot.ly/plotly-basic-latest.min.js'
# county dropdown
app.layout = html.Div([
html.H1('County'),
dcc.Dropdown(
id='my-dropdown',
options=[
{'label': 'Queens', 'value': 'Queens'},