def index():
"""Main page of the dashboard."""
# Check pre-rendered HTML
rendered = data.get_rendered_page("country")
if rendered:
return rendered
city = "Россия"
main_links = filter_secondary_links(city)
secondary_links = []
# Getting data
#full_data = data.get_newest_data()
#request_file = request.files['data_file']
#df = pd.read_csv(request.files.get('data_file'))
df = pd.read_csv(request.files.get('data_file'), sep = ";")
#fstring = request_file.read()
#csv_dicts = [{k: v for k, v in row.items()} for row in csv.DictReader(fstring.splitlines(), skipinitialspace=True)]
#df = pd.DataFrame.from_dict(csv_dicts)
df["date"] = pd.to_datetime(df["date"], dayfirst=True)
df = df.set_index(["date", "category"]).unstack(level=-1)
full_data = df.sort_index()
del df
country_data_full, country_data = data.get_region_data(full_data, city)
# Map plot
borders = data.get_geo_data()
latest_data = full_data.iloc[-1].unstack(level=-1)
latest_diff = (full_data
.diff()
.iloc[-1]
.unstack(level=-1)
.rename(lambda x: f"{x}_diff", axis=1))
map_data = (borders
.join(latest_data, on="REGION")
.join(latest_diff, on="REGION")
.fillna(0))
map_data["total_color"] = 1. + map_data["total"]
map_plot = plotting.plot_map(map_data)
# Getting Bokeh components
script, div = components({"map": map_plot})
# Rendering HTML
rendered = render_template("main.html", city=city,
main_links=main_links,
secondary_links=secondary_links,
bokeh_script=script,
**div)
#data.save_rendered_page("country", rendered)
del map_data
return rendered
def moscow():
"""Moscow-specific page."""
# Check pre-rendered HTML
city = "Москва"
rendered = data.get_rendered_page(city)
if rendered:
return rendered
main_links = [{
"name": "Больницы",
"link": "#hospitals"
}, {
"name": "Транспорт",
"link": "#transport"
}]
secondary_links = filter_secondary_links(city)
# Getting data
full_data = data.get_newest_data()
moscow_data_full, moscow_data = data.get_region_data(full_data, city)
# Cases statistics block
stats = []
for category in cts.CATEGORIES[:-1]:
style = cts.CATEGORIES_STYLES[category].copy()
style["value"] = moscow_data[category]
style["diff"] = moscow_data[f"{category}_diff"]
stats.append(style)
# Cases plots
cases_plot = plotting.plot_region(moscow_data_full, city)
cases_log_plot = plotting.plot_region(moscow_data_full, city, log_y=True)
# Transport plots
transport_data = data.get_data_by_key([cts.MSK_DIR, "transport"],
sort_by="date",
set_index="date")
public_tr_plot = plotting.plot_region(
transport_data / 100.,
city,
plot_cols=[tr["key"] for tr in cts.PUBLIC_TR_COLS],
legend_map=[tr["name"] for tr in cts.PUBLIC_TR_COLS],
legend_loc="top_right",
dt_fmt="%d-%m-%Y %H:%S",
fmt="{0 %}",
set_yticks=True,
width_policy="max",
height=int(0.75 * cfg.MAX_MAIN_HEIGHT),
xaxis_ticks=5,
yrange=(-1.1, 0))
private_tr_plot = plotting.plot_region(
transport_data / 100.,
city,
plot_cols=[tr["key"] for tr in cts.PRIVATE_TR_COLS],
legend_map=[tr["name"] for tr in cts.PRIVATE_TR_COLS],
legend_loc="top_right",
dt_fmt="%d-%m-%Y %H:%S",
fmt="{0 %}",
set_yticks=True,
width_policy="max",
height=int(0.75 * cfg.MAX_MAIN_HEIGHT),
xaxis_ticks=5,
yrange=(-1.1, 0))
plots = {
"cases": cases_plot,
"cases_log": cases_log_plot,
"public_transport": public_tr_plot,
"private_transport": private_tr_plot
}
# Transport block
transport_data_latest = transport_data.iloc[-1].to_dict()
tr_stats = []
for category in cts.PUBLIC_TR_COLS + cts.PRIVATE_TR_COLS:
tr_stats.append({
"name": category["name"].capitalize(),
"value": transport_data_latest[category["key"]]
})
# Hospitals
hospitals = []
for hospital in cts.MSK_HOSPITALS:
hospital_data = data.get_data_by_key(
[cts.MSK_DIR, cts.MSK_HOSPITALS_DIR, hospital["key"]])
hospital_plot = plotting.plot_region(
hospital_data,
hospital["name"],
plot_cols=[tr["key"] for tr in hospital["fields"]],
legend_map=[tr["name"] for tr in hospital["fields"]],
glyphs={
tr["key"]: tr["glyph"]
for tr in hospital["fields"] if "glyph" in tr
},
alphas={
tr["key"]: tr["alpha"]
for tr in hospital["fields"] if "alpha" in tr
},
bar_bottom=0,
alpha=0.9,
legend_loc="top_left",
width_policy="max",
width=cfg.MAX_MAIN_WIDTH * 2,
height_policy="fit",
additional_tools=["ywheel_zoom", "ypan", "reset"])
plots[hospital["key"]] = hospital_plot
hospitals.append(hospital)
# Getting Bokeh components
script, div = components(plots)
for hospital in hospitals:
hospital_plot = div.pop(hospital["key"])
hospital["plot"] = hospital_plot
# Rendering HTML
rendered = render_template("moscow.html",
city=city,
main_links=main_links,
secondary_links=secondary_links,
stats=stats,
tr_stats=tr_stats,
bokeh_script=script,
hospitals=hospitals,
**div)
data.save_rendered_page("moscow", rendered)
return rendered
def index():
"""Main page of the dashboard."""
# Check pre-rendered HTML
rendered = data.get_rendered_page("country")
if rendered:
return rendered
city = "Россия"
main_links = filter_secondary_links(city)
secondary_links = []
# Getting data
full_data = data.get_newest_data()
country_data_full, country_data = data.get_region_data(full_data, city)
swabs_data = data.get_swabs_data()
swabs_data = swabs_data.join(country_data_full["total"], how="outer")
# Cases statistics block
stats = []
for category in cts.CATEGORIES:
style = cts.CATEGORIES_STYLES[category].copy()
style["value"] = country_data[category]
style["diff"] = country_data[f"{category}_diff"]
stats.append(style)
# Map plot
borders = data.get_geo_data()
latest_data = full_data.iloc[-1].unstack(level=-1)
latest_diff = (full_data.diff().iloc[-1].unstack(level=-1).rename(
lambda x: f"{x}_diff", axis=1))
map_data = (borders.join(latest_data,
on="REGION").join(latest_diff,
on="REGION").fillna(0))
map_data["total_color"] = 1. + map_data["total"]
map_plot = plotting.plot_map(map_data)
# Cases plots
cases_plot = plotting.plot_region(country_data_full, city)
cases_log_plot = plotting.plot_region(country_data_full, city, log_y=True)
# Swabs plots
swabs_plot = plotting.plot_swabs(swabs_data, city)
swabs_log_plot = plotting.plot_swabs(swabs_data, city, x_col="total")
# Getting Bokeh components
script, div = components({
"cases": cases_plot,
"cases_log": cases_log_plot,
"swabs": swabs_plot,
"swabs_log": swabs_log_plot,
"map": map_plot,
})
# Rendering HTML
rendered = render_template("main.html",
city=city,
main_links=main_links,
secondary_links=secondary_links,
stats=stats,
bokeh_script=script,
**div)
data.save_rendered_page("country", rendered)
return rendered