from typing import Optional
import matplotlib as mpl
import pandas as pd
from matplotlib import pyplot as plt
import iccas as ic
import iccas.i18n
from iccas.i18n import translated
from iccas.i18n.lib import Translation
from iccas.charts.common import (
DEFAULT_CMAP,
Period,
check_age_group_size,
check_variable,
legend,
resample_if_needed,
)
DOUBLE_CHART_FIGSIZE = (15, 15)
[docs]@translated()
def area_chart(
counts_over_time: pd.DataFrame,
*,
strings: Translation,
normalize: bool = False,
ax: Optional[plt.Axes] = None,
cmap=DEFAULT_CMAP,
alpha: float = 0.8,
**kwargs,
) -> plt.Axes:
"""
A base for stacked area charts (tuned for iccas charts).
Args:
counts_over_time:
a DataFrame with a DateTimeIndex and a column for each age group
(e.g. ``ic.get().cases``)
strings:
normalize:
ax:
cmap:
alpha:
**kwargs:
Returns:
"""
data = counts_over_time
if normalize:
data = data.divide(data.sum(axis=1), axis=0)
ax = data.plot.area(ax=ax, alpha=alpha, cmap=cmap, **kwargs)
if normalize:
ax.set_ylim([0, 1.0])
ax.yaxis.set_major_formatter(mpl.ticker.PercentFormatter(xmax=1.0, decimals=0))
else:
ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter("{x:n}"))
ax.set_xlabel("")
ax.set_xlim(data.index[0], data.index[-1])
legend(ax, title=strings["age"])
return ax
[docs]@translated("""
en:
title.cases: Coronavirus cases in Italy since the beginning of the pandemic
title.deaths: Deaths for coronavirus in Italy since the beginning of the pandemic
it:
title.cases: Casi di coronavirus dall'inizio della epidemia
title.deaths: Decessi per coronavirus dall'inizio della pandemia
""")
def double_area_chart_of_cumulative_counts(
data: pd.DataFrame,
variable: str = "cases",
*,
age_group_size: int = 20,
period: Optional[Period] = None,
strings: Translation,
**figure_args,
) -> plt.Figure:
"""
Not a very interesting chart.
Args:
data:
DataFrame having 'cases' and/or 'deaths' as first-level columns
(e.g. ``ic.get()``)
variable:
age_group_size:
period:
strings:
lang:
Returns:
"""
check_variable(variable)
check_age_group_size(age_group_size)
period_slice: slice = slice(*period) if period else slice(data.index[0], None)
# resample for a smoother graph
d = resample_if_needed(data[variable], "D", hour=18, method="pchip")
d = ic.aggregate_age_groups(
d[period_slice].drop(columns="unknown"),
cuts=age_group_size,
fmt_last="{}+",
)
figure_args.setdefault("figsize", DOUBLE_CHART_FIGSIZE)
fig, ax = plt.subplots(2, 1, **figure_args)
title = strings[f"title.{variable}"]
ax[0].set_title(title)
area_chart(d, ax=ax[0], lang=strings.lang)
area_chart(d, normalize=True, ax=ax[1], lang=strings.lang)
[docs]@translated()
def double_area_chart_of_running_averages(
data: pd.DataFrame,
variable: str = "cases",
*,
strings: Translation,
window: int = 14,
age_group_size: int = 20,
period: Optional[Period] = None,
**figure_args,
):
check_variable(variable)
check_age_group_size(age_group_size)
period_slice = slice(*period) if period else slice(data.index[0], None)
r = resample_if_needed(data[variable].drop(columns="unknown"), "D")
d = r[period_slice]
d = d.diff(window).iloc[window:]
d = ic.aggregate_age_groups(d, cuts=age_group_size, fmt_last="{}+")
if window > 1:
d = d / window
figure_args.setdefault("figsize", DOUBLE_CHART_FIGSIZE)
fig, ax = plt.subplots(2, 1, **figure_args)
area_chart(d, ax=ax[0], lang=strings.lang)
area_chart(d, ax=ax[1], normalize=True, lang=strings.lang)
ax[0].set_title(strings.get(f"running_average_{variable}_title", count=window))
return fig
if __name__ == "__main__":
plt.style.use('seaborn')
resampled = ic.resample(ic.get()[["cases"]])
iccas.i18n.set_language('en')
double_area_chart_of_running_averages(resampled, window=14)
plt.show()
iccas.i18n.set_language('it')
double_area_chart_of_running_averages(resampled, window=14)
plt.show()