Lifemap.layer_points

Lifemap.layer_points(
    leaves='show',
    radius=5,
    radius_range=(2, 30),
    fill=None,
    fill_cat=None,
    scheme=None,
    opacity=0.8,
    popup=True,
    hover=None,
    label=None,
)

Add a points layer.

It can be used to display leaves values, or aggregated counts or values already computed or generated by aggregate_num or aggregate_count.

Parameters

Name	Type	Description	Default
leaves	Literal["show", "only", "omit"]	If "only", only show tree leaves. If "omit", only show nodes that are not leaves. If "show", show all nodes, by default “show”	'show'
radius	int | float | str	If numeric, the fixed radius of the points. If a string, the name of a numerical DataFrame column to compute radius width from.	5
radius_range	tuple | list	Range of values for points radius, only used if radius_col is not None, by default (2, 30)	(2, 30)
fill	str | None	Either the name of a numerical DataFrame column to determine points color, or a fixed CSS color for points.	None
fill_cat	bool | None	If True, force color scheme to be categorical. If False, force it to be continuous. If None, let pylifemap decide. By default None.	None
scheme	str | None	Color scheme for points color. It is the name of an Observable Plot color scale.	None
opacity	float	Points opacity as a floating number between 0 and 1, by default 0.8	0.8
popup	bool	If True, display informations in a popup when a point is clicked, by default False	True
hover	bool | None	If True, highlight points on mouse hovering. By default True if less than 10_000 data points, False otherwise.	None
label	str | None	Legend title for this layer if fill is defined. If None, the value of fill 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
>>> d = pl.DataFrame(
...     {
...         "taxid": [
...             9685,
...             9615,
...             9994,
...             2467430,
...             2514524,
...             2038938,
...             1021470,
...             1415565,
...             1928562,
...             1397240,
...             230741,
...         ],
...         "value": [7.4, 2.5, 8.3, 1.0, 1.4, 5.6, 4.6, 3.4, 2.3, 2.8, 3.1],
...     }
... )
>>> Lifemap(d).layer_points(radius="value", fill="value", popup=True).show()

See also

aggregate_num : aggregation of a numeric variable.

aggregate_count : aggregation of the number of observations.