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172 | class ESMGroupedBarChart:
"""
A class that produces multiple bar charts in subplots.
Parameters
----------
df
Metric data frame complying with the evaluation data model.
cfg
Plotly configuration object with styling and export settings.
"""
def __init__(self, df: pd.DataFrame, cfg: SimpleNamespace) -> None:
self._df = df
self.cfg = cfg
self.unit = self.cfg.unit or df.attrs["unit"]
self.metric_name = df.attrs["name"]
self.location = self._df.index.unique(DataModel.LOCATION)[0]
self.col_values = self._df.columns[0]
ncols = len(self.df[DataModel.BUS_CARRIER].unique())
ncols = ncols or 1
column_widths = [0.85 / ncols] * ncols
self.fig = make_subplots(
rows=1, cols=ncols, shared_yaxes=True, column_widths=column_widths
)
@cached_property
def df(self) -> pd.DataFrame:
"""
Plot data formatted for grouped bar charts.
Returns
-------
:
The formatted data for creating bar charts.
"""
df = apply_cutoff(self._df, limit=self.cfg.cutoff, drop=False)
df = df.reset_index()
fill_values = product(
df[DataModel.YEAR].unique(),
df[DataModel.LOCATION].unique(),
df[DataModel.CARRIER].unique(),
df[DataModel.BUS_CARRIER].unique(),
)
df_fill = pd.DataFrame(columns=DataModel.YEAR_IDX_NAMES, data=fill_values)
df_fill[self.col_values] = np.nan
df = pd.concat([df, df_fill], ignore_index=True)
df_list = []
for _, df_sector in df.groupby(self.cfg.facet_column, sort=True):
sorted_sector = custom_sort(
df_sector,
by=self.cfg.plot_category,
values=self.cfg.category_orders,
ascending=True,
)
df_list.append(sorted_sector)
df = pd.concat(df_list)
df = df.dropna(how="all", subset=self.col_values)
df["display_value"] = df[self.col_values].apply(prettify_number)
return df
def plot(self) -> None:
"""Create the bar chart."""
title = self.cfg.title.format(location=self.location, unit=self.unit)
if empty_input(self._df) or self.df[self.col_values].isna().all():
self.fig = empty_figure(title)
return
pattern = {
col: self.cfg.pattern.get(col, "")
for col in self.df[self.cfg.plot_category].unique()
}
self.fig = px.bar(
self.df,
x=self.cfg.plot_xaxis,
y=self.col_values,
facet_col=self.cfg.facet_column,
facet_col_spacing=0.04,
pattern_shape=self.cfg.plot_category,
pattern_shape_map=pattern,
color=self.cfg.plot_category,
color_discrete_map=self.cfg.colors,
text=self.cfg.facet_column,
title=title,
custom_data=[self.cfg.plot_category, "display_value"],
)
self.fig.for_each_xaxis(self._rename_xaxis)
total_renderer = TotalSumRenderer(
col_values=self.col_values,
plot_xaxis=self.cfg.plot_xaxis,
unit=self.unit,
)
total_renderer.add_subplot_traces(self.fig, self.df, self.cfg.facet_column)
self.fig.update_annotations(text="")
layout_styler = LayoutStyler(self.cfg)
bar_styler = BarTraceStyler(width=0.8)
layout_styler.set_base_layout(self.fig)
bar_styler.apply(self.fig, self.unit)
layout_styler.style_title_and_legend_and_xaxis_label(self.fig)
layout_styler.append_footnotes(self.fig)
self.fig.update_xaxes(fixedrange=True)
self.fig.update_yaxes(fixedrange=True)
self.fig.for_each_xaxis(self._style_inner_xaxis_labels)
def _rename_xaxis(self, xaxis: go.layout.XAxis) -> None:
"""
Update the xaxis labels.
Parameters
----------
xaxis
The subplot xaxis (a dictionary).
"""
layout = self.fig["layout"]
idx = xaxis["anchor"].lstrip("y")
for data in self.fig["data"]:
if data["xaxis"] == f"x{idx}":
sector = data["text"][0]
layout[f"xaxis{idx}"]["title"]["text"] = f"<b>{sector}"
break
def _style_inner_xaxis_labels(self, xaxis: go.layout.XAxis) -> None:
"""
Set the font size for inner xaxis labels.
Parameters
----------
xaxis
The subplot xaxis (a dictionary-like object).
"""
xaxis.update(
tickfont_size=self.cfg.xaxis_font_size,
categoryorder="category ascending",
)
|