def generate_world_ts_options(resources=resources,
plot_confirmed=True,
plot_recovered=True,
plot_deaths=True):
df = df_from_path(resources['worldwide-aggregated'])
date = df['Date'].tolist()
confirmed = df['Confirmed'].tolist()
recovered = df['Recovered'].tolist()
deaths = df['Deaths'].tolist()
fig = go.Figure()
if plot_confirmed:
fig.add_trace(
go.Scatter(x=date,
y=confirmed,
name='Cases',
line=dict(color=CONFIRMED_COLOUR, width=2)))
if plot_recovered:
fig.add_trace(
go.Scatter(x=date,
y=recovered,
name='Recoveries',
line=dict(color=RECOVERED_COLOUR, width=2)))
if plot_deaths:
fig.add_trace(
go.Scatter(x=date,
y=deaths,
name='Deaths',
line=dict(color=DEATHS_COLOUR, width=2)))
fig.update_layout(title={
'text': f"<b>Global confirmed numbers over time</b>",
'x': 0.5,
'xanchor': 'center',
'y': 0.95,
},
margin={
"r": 10,
"t": 40,
"l": 10,
"b": 5
},
font=dict(
family=FONT,
size=12,
),
xaxis_title='Date',
yaxis_title='Confirmed numbers',
hovermode='x')
fig.update_yaxes(nticks=10)
fig.update_xaxes(nticks=10)
return fig
def generate_datatable(
df=df_from_path(resources['countries-aggregated']), date=False):
if not date:
date = df.iloc[len(df) - 1, 0]
df = filter_df(df, "Date", date)
df = df[['Country', 'Confirmed', 'Recovered', 'Deaths']]
for i in range(len(df)):
if len(df.iloc[i][0]) > 15:
df.at[df.iloc[i].name, 'Country'] = f"{df.iloc[i][0][:12]}..."
return df
def generate_comparable_time_series(plot="Confirmed",
countries=[
"China", "United Kingdom", "Italy",
"Spain", "Iran", "US", "Korea, South"
],
df=ts_df,
xth=100):
countries = [
"China", "United Kingdom", "Italy", "Spain", "Iran", "US",
"Korea, South"
]
df = df_from_path(resources['countries-aggregated'])
xth = 100
fig = go.Figure()
if plot == "Confirmed":
plot_word = "case"
plural_plot_word = "cases"
elif plot == "Recovered":
plot_word = "recovery"
plural_plot_word = "recoveries"
elif plot == "Deaths":
plot_word = "death"
plural_plot_word = "deaths"
else:
raise ValueError(
f"'plot' variable must be equal to 'Confirmed', 'Recovered' or 'Deaths'. Your input was '{plot}'"
)
for country in countries:
base_date = xth_date(country, xth, data=plural_plot_word, df=df)
country_df = df.loc[df["Country"] == country]
try:
country_df = country_df[country_df['Date'] >= base_date]
except:
continue
x_axis_data = []
y_axis_data = country_df[plot].tolist()
for i in range(len(y_axis_data)):
x_axis_data.append(i)
fig.add_trace(
go.Scatter(x=x_axis_data,
y=y_axis_data,
name=country,
mode='lines'))
fig.update_layout(title={
'text':
f"<b>Confirmed {plural_plot_word} over time (day 0 = {xth:,} {plural_plot_word})</b>",
'x': 0.5,
'xanchor': 'center',
},
margin={
"r": 10,
"t": 30,
"l": 10,
"b": 0
},
font=dict(
family=FONT,
size=12,
),
xaxis_title=f'Days since {xth}th {plot_word}',
yaxis_title=f'Confirmed {plural_plot_word}',
hovermode='x')
fig.update_yaxes(nticks=10)
fig.update_xaxes(nticks=10)
return fig
def generate_deathrates_by_country(resources=resources,
max_rows=30,
min_cases=1000,
min_deaths=200,
date=False):
df = df_from_path(resources['countries-aggregated'])
if not date:
date = df.iloc[len(df) - 1, 0]
df = filter_df(df, "Date", date)
x_data = []
y_data = []
y_label = []
for location in range((len(df))):
location_name = df.iloc[location][1]
if len(location_name.split(" ")) > 1 and len(location_name) > 13:
location_abbv = ""
for word in location_name.split(" "):
location_abbv += word[0]
location_name = location_abbv
cases = df.iloc[location][2]
if cases == 0:
cases += 1
deaths = df.iloc[location][4]
if cases > min_cases and deaths > min_deaths:
death_rate = deaths / cases
x_data.append(death_rate)
y_data.append(location_name)
y_label.append(f"{death_rate*100:.1f}% ({deaths:,}/{cases:,})")
num_rows = min(max_rows, len(x_data))
colours = []
for row in range(num_rows):
colours.append(
f'rgb(255,{230-128*(row/num_rows)},{230-128*(row/num_rows)})')
total_cases = df.sum(axis=0)[2]
total_deaths = df.sum(axis=0)[4]
average_death_rate = total_deaths / total_cases
x_data.append(average_death_rate)
y_data.append("Average")
y_label.append(
f"{average_death_rate*100:.1f}% ({total_deaths:,}/{total_cases:,})")
x_data, y_data, y_label = (list(t) for t in zip(
*sorted(zip(x_data, y_data, y_label))))
x_data = x_data[len(x_data) - max_rows:len(x_data)]
y_data = y_data[len(y_data) - max_rows:len(y_data)]
y_label = y_label[len(y_label) - max_rows:len(y_label)]
try:
colours[y_data.index('Average')] = 'rgba(168, 102, 255, 0.8)'
except:
print(f"Average not in top {num_rows}")
fig = go.Figure()
fig.add_trace(
go.Bar(x=y_data[::-1],
y=x_data[::-1],
text=y_label[::-1],
name="Death rate summary",
orientation='v',
marker=dict(color=colours[::-1],
line=dict(color='rgba(38, 24, 74, 0.8)', width=1))))
fig.update_yaxes(range=[0, 0.2])
fig.update_layout(title={
'text':
f"<b>Death rates ({min_cases}+ cases, {min_deaths}+ deaths)</b>",
'x': 0.5,
'y': 0.95,
'xanchor': 'center',
},
barmode='stack',
margin={
"r": 15,
"t": 40,
"l": 10,
"b": 10,
"pad": 5
},
width=1 * num_rows,
yaxis=dict(tickformat=".1%", ),
xaxis_tickangle=-90,
font=dict(
family=FONT,
size=12,
))
fig.update_yaxes(tickfont=dict(size=12), )
return fig
"toImage", "resetViews", "resetViewMapbox", "resetGeo", "resetScale2d"
],
hide_buttons=TOOLBAR_BUTTONS):
for button in buttons:
hide_buttons.remove(button)
return hide_buttons
CHOSEN_BUTTONS = add_buttons_to_default()
MINIMALIST_CONFIG = {
"displaylogo": False,
"modeBarButtonsToRemove": CHOSEN_BUTTONS,
}
headline_df = df_from_path(resources['worldwide-aggregated'])
current_date = headline_df.iloc[len(headline_df) - 1][0]
current_confirmed = headline_df.iloc[len(headline_df) - 1][1]
current_recovered = headline_df.iloc[len(headline_df) - 1][2]
current_deaths = headline_df.iloc[len(headline_df) - 1][3]
prev_date = headline_df.iloc[len(headline_df) - 2][0]
prev_confirmed = headline_df.iloc[len(headline_df) - 2][1]
prev_recovered = headline_df.iloc[len(headline_df) - 2][2]
prev_deaths = headline_df.iloc[len(headline_df) - 2][3]
confirmed_growth = (current_confirmed / prev_confirmed) - 1
recovered_growth = (current_recovered / prev_recovered) - 1
deaths_growth = (current_deaths / prev_deaths) - 1
def formatted_mvmt(figure, text):
if figure >= 0:
MINIMALIST_CONFIG ={
"displaylogo": False,
"modeBarButtonsToRemove": CHOSEN_BUTTONS,
}
# if we currently have no resources, get them
try:
resources
current_api
except NameError:
resources, current_api = get_resources(DATA_SOURCE)
try:
headline_df
except NameError:
headline_df = df_from_path(resources['worldwide-aggregate'])
try:
ts_df
except NameError:
ts_df = df_from_path(resources['countries-aggregated'])
try:
df2
except NameError:
df2 = get_df(current_api)
try:
ref_table
except NameError:
ref_table = df_from_path(resources['reference'])