Lifemap.layer_donuts

Lifemap.layer_donuts(counts_col, *, radius=None, leaves='hide', scheme=None, opacity=1, popup=True, label=None)

Add a donuts layer.

This layer displays the distribution of a categorical variable values among each nodes children. Optionally it can also represent leaves values as a point layer.

It should be applied to data computed with aggregate_freq.

Parameters

Name	Type	Description	Default
counts_col	str	DataFrame column containing the counts.	required
radius	float | None	Donut charts radius, by default None	None
leaves	Literal["show", "hide"]	If "show", add a points layer with individual leaves values, by default “hide”	'hide'
scheme	str | None	Color scheme for donut charts ans points. It is the name of a categorical Observable Plot color scale, by default None	None
opacity	float | None	Donut charts and points opacity, by default 1	1
popup	bool | None	If True, display informations in a popup when a point is clicked, by default False, by default True	True
label	str | None	Legend title for this layer. If None, the value of counts_col is used.	None

Returns

Type	Description
Lifemap	A Lifemap visualization object.

Raises

Type	Description
ValueError	If leaves is not one of the allowed values.

Examples

>>> import polars as pl
>>> from pylifemap import Lifemap, aggregate_freq
>>> d = pl.DataFrame({
...     "taxid": [9685, 9615, 9994, 2467430, 2514524, 2038938, 1021470, 1415565, 1928562, 1397240, 230741],
...     "category": ["a", "b", "b", "a", "a", "c", "a", "b", "b", "a", "b"]
... })
>>> d = aggregate_freq(d, column="category")
>>> (
...     Lifemap(d)
...     .layer_donuts(counts_col="category", leaves="hide")
...     .show()
... )

See Also

: aggregation of the values counts of a categorical variable.