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

Name	Type	Description
	Lifemap	A Lifemap visualization object.

Raises

Name	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.