def transform(self, data_frame, slicer, dimensions, references):
import matplotlib.pyplot as plt
data_frame = data_frame.copy()
n_axes = len(self.items)
figsize = (14, 5 * n_axes)
fig, plt_axes = plt.subplots(n_axes, sharex='row', figsize=figsize)
fig.suptitle(self.title)
if not hasattr(plt_axes, '__iter__'):
plt_axes = (plt_axes, )
colors = itertools.cycle('bgrcmyk')
for axis, plt_axis in zip(self.items, plt_axes):
for series in axis:
series_color = next(colors)
linestyles = itertools.cycle(['-', '--', '-.', ':'])
for reference in [None] + references:
metric = series.metric
f_metric_key = utils.alias_selector(
reference_alias(metric, reference))
f_metric_label = reference_label(metric, reference)
plot = self.get_plot_func_for_series_type(
data_frame[f_metric_key], f_metric_label, series)
plot(ax=plt_axis,
label=axis.label,
color=series_color,
stacked=series.stacking is not None,
linestyle=next(linestyles)) \
.legend(loc='center left',
bbox_to_anchor=(1, 0.5))
return plt_axes
def __init__(self, item, reference):
assert isinstance(reference, Reference)
self.data_type = item.data_type
self.alias = reference_alias(item, reference)
self.label = reference_label(item, reference)
self.prefix = reference_prefix(item, reference)
self.suffix = reference_suffix(item, reference)
self.thousands = item.thousands
self.precision = item.precision
def _render_pie_series(self, metric: Field, reference: Reference,
data_frame: pd.DataFrame,
dimension_fields: List[Field]) -> dict:
metric_alias = utils.alias_selector(metric.alias)
if self.split_dimension:
dimension_fields = [
dimension for dimension in dimension_fields
if dimension != self.split_dimension
]
data_frame = data_frame.reset_index(alias_selector(
self.split_dimension.alias),
drop=True)
data = []
for dimension_values, y in data_frame[metric_alias].iteritems():
dimension_values = utils.wrap_list(dimension_values)
name = self._format_dimension_values(dimension_fields,
dimension_values)
data.append({
"name": name or metric.label,
"y": formats.raw_value(y, metric)
})
return {
"name": reference_label(metric, reference),
"type": "pie",
"data": data,
"tooltip": {
"pointFormat":
'<span style="color:{point.color}">\u25CF</span> {series.name}: '
"<b>{point.y} ({point.percentage:.1f}%)</b><br/>",
"valueDecimals":
metric.precision,
"valuePrefix":
reference_prefix(metric, reference),
"valueSuffix":
reference_suffix(metric, reference),
},
}
def _render_pie_series(self, metric, reference, data_frame, dimension_fields):
metric_alias = utils.alias_selector(metric.alias)
data = []
for dimension_values, y in data_frame[metric_alias].iteritems():
dimension_values = utils.wrap_list(dimension_values)
name = self._format_dimension_values(dimension_fields, dimension_values)
data.append(
{"name": name or metric.label, "y": formats.raw_value(y, metric),}
)
return {
"name": reference_label(metric, reference),
"type": "pie",
"data": data,
"tooltip": {
"pointFormat": '<span style="color:{point.color}">\u25CF</span> {series.name}: '
"<b>{point.y} ({point.percentage:.1f}%)</b><br/>",
"valueDecimals": metric.precision,
"valuePrefix": reference_prefix(metric, reference),
"valueSuffix": reference_suffix(metric, reference),
},
}
def _render_highcharts_series(
self,
series,
series_df: pd.DataFrame,
references: List[Reference],
dimension_label: str,
is_timeseries: bool,
symbol: str,
axis_idx: int,
axis_color: str,
series_color: str,
):
"""
Note on colors:
- With a single axis, use different colors for each series
- With multiple axes, use the same color for the entire axis and only change the dash style
:param series:
:param series_df:
:param references:
:param dimension_label:
:param is_timeseries:
:param symbol:
:param axis_idx:
:param axis_color:
:param series_color:
:return:
"""
if is_timeseries:
series_df = series_df.sort_index(level=0)
results = []
for reference, dash_style in zip([None] + references,
itertools.cycle(DASH_STYLES)):
field_alias = utils.alias_selector(
reference_alias(series.metric, reference))
metric_label = reference_label(series.metric, reference)
if field_alias not in series_df:
continue
hc_series = {
"type":
series.type,
"name":
"{} ({})".format(metric_label, dimension_label)
if dimension_label else metric_label,
"data": (self._render_timeseries_data(series_df, field_alias,
series.metric)
if is_timeseries else self._render_category_data(
series_df, field_alias, series.metric)),
"tooltip":
self._render_tooltip(series.metric, reference),
"yAxis":
("{}_{}".format(axis_idx, reference.alias) if
reference is not None and reference.delta else str(axis_idx)),
"marker": ({
"symbol": symbol,
"fillColor": axis_color or series_color
} if isinstance(series, SERIES_NEEDING_MARKER) else {}),
"stacking":
series.stacking,
}
if isinstance(series, ContinuousAxisSeries):
# Set each series in a continuous series to a specific color
hc_series["color"] = series_color
hc_series["dashStyle"] = dash_style
results.append(hc_series)
return results