Lifemap.layer_lines
Lifemap.layer_lines(
width=3,
width_range=(1, 30),
color=None,
scheme=None,
opacity=0.8,
popup=True,
hover=True,
label=None,
)Add a lines layer.
This layer can be applied to data generated by aggregate_num or aggregate_count.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| width | int | float | str | If numeric, the fixed width of the lines. If a string, the name of a numerical DataFrame column to compute line width from. | 3 |
| width_range | tuple | list | Min and max values for line widths, only used if width is a data column, by default (1, 30) | (1, 30) |
| color | str | None | Either the name of a numerical DataFrame column to determine line color, or a fixed CSS color for lines. | None |
| scheme | str | None | Color scheme for lines color. It is the name of an Observable Plot color scale. | None |
| opacity | float | Line 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 | If True, highlight points on mouse hovering. By default False. | True |
| label | str | None | Legend title for this layer if color_col is defined. If None, the value of color_col is used. |
None |
Returns
| Name | Type | Description |
|---|---|---|
| Lifemap | A Lifemap visualization object. |
Examples
>>> import polars as pl
>>> from pylifemap import Lifemap, aggregate_num
>>> 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],
... }
... )
>>> d = aggregate_num(d, column="value", fn="mean")
>>> Lifemap(d).layer_lines(width_col="value", color_col="value").show()See also
aggregate_num : aggregation of a numeric variable.
aggregate_count : aggregation of the number of observations.