I used Python's Plotly library. With Geojson, it is attractive to be able to easily plot as an animation on a map from a data frame. On the other hand, the problem is that it is overwhelmingly heavier than Javascript.
Number of infected people by prefecture
Number of infected people by country
Number of infected people in China
###Data frame reading
dfs = []
for l in os.listdir("./csv_ja/"):
if ".csv" in l:
dfs.append(pd.read_csv("./csv_ja/" +l))
print(l)
###json read
with open("./geo_data/jp_prefs.geojson") as f:
geojson_japan = json.load(f)
###Creating an Animation Object
fig = px.choropleth(df_japan,
geojson = geojson_japan,
featureidkey="properties.NAME_JP",
locations="Province/State",
color="Confirmed",
hover_name="Province/State",
color_continuous_scale="PuRd",
projection="mercator",
animation_frame="date",
range_color=(0,df_japan[key].max()),
width=600, height=800)
fig.update_geos(fitbounds="locations", visible=False)
fig.update_layout(
title="Number of people infected with new coronavirus(Prefectures)")
Johns Hopkins University Dashboard Johns Hopkins University Spreadsheet
MIT (Prefecture Geojson Data) WHO NHC CDC Dingxiangyuan Ministry of Health, Labor and Welfare
The day when positive is confirmed is defined as Confirmed. The prefecture means the prefecture where you live (in the case of foreign nationality, the prefecture of the medical institution where you visited). Asymptomatic pathogen carriers are not included in infected individuals.