Lifemap.layer_lines
Lifemap.layer_lines(=None,
width=None,
width_col=None,
color_col=None,
scheme=0.8,
opacity=False,
popup=None,
label )
Add a lines layer.
This layer can be applied to data generated by aggregate_num
or aggregate_count
.
Parameters
Name | Type | Description | Default |
---|---|---|---|
width | float | None | Base line width, by default None | None |
width_col | str | None | Name of numeric DataFrame column to compute line width, by default None | None |
color_col | str | None | Name of numeric DataFrame column to determine line color, by default None | None |
scheme | str | None | Color scheme for points color. If color_col is defined, it is the name of an Observable Plot color scale. Otherwise, it is an hexadecimal color value, by default None |
None |
opacity | float | None | Line opacity as a floating number between 0 and 1, by default 0.8 | 0.8 |
popup | bool | None | TODO: doesn’t work for the moment. If True, display informations in a popup when a point is clicked, by default False | False |
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.