def plot_kde(data: Union["ps.DataFrame", "ps.Series"], **kwargs):
from plotly import express
import pyspark.pandas as ps
if isinstance(data, ps.DataFrame) and "color" not in kwargs:
kwargs["color"] = "names"
kdf = KdePlotBase.prepare_kde_data(data)
sdf = kdf._internal.spark_frame
data_columns = kdf._internal.data_spark_columns
ind = KdePlotBase.get_ind(sdf.select(*data_columns),
kwargs.pop("ind", None))
bw_method = kwargs.pop("bw_method", None)
pdfs = []
for label in kdf._internal.column_labels:
pdfs.append(
pd.DataFrame({
"Density":
KdePlotBase.compute_kde(
sdf.select(kdf._internal.spark_column_for(label)),
ind=ind,
bw_method=bw_method,
),
"names":
name_like_string(label),
"index":
ind,
}))
pdf = pd.concat(pdfs)
fig = express.line(pdf, x="index", y="Density", **kwargs)
fig["layout"]["xaxis"]["title"] = None
return fig
def _plot(cls,
ax,
y,
style=None,
bw_method=None,
ind=None,
column_num=None,
stacking_id=None,
**kwds):
y = KdePlotBase.compute_kde(y, bw_method=bw_method, ind=ind)
lines = PandasMPLPlot._plot(ax, ind, y, style=style, **kwds)
return lines
def _get_ind(self, y):
return KdePlotBase.get_ind(y, self.ind)
def _compute_plot_data(self):
self.data = KdePlotBase.prepare_kde_data(self.data)