geom_count ¶
geom_count(
mapping: FeatureSpec | None = None,
*,
data: PlotData | None = None,
stat: str | None = None,
position: Position | None = None,
show_legend: bool | None = None,
inherit_aes: bool | None = None,
manual_key: ManualKey | None = None,
sampling: Sampling | None = None,
tooltips: Tooltips | None = None,
color_by: str | None = None,
fill_by: str | None = None,
na_rm: bool | None = None,
**other_args: Any,
) -> LayerSpec
Points at each distinct (x, y), sized by the number of rows there (stat="sum").
The stat computes ..n.. (rows, or summed weight, at the location),
..prop.. (n over the group's total) and ..proppct.. (the same in
percent); size is mapped to ..n.. by default.
Parameters:
-
mapping(FeatureSpec, default:None) –Aesthetic mapping from
aes():x,y(required),color,fill,size,shape,alpha,stroke,weight. -
data(DataFrame or dict, default:None) –Layer data; inherits the plot data when None.
-
stat(str, default:None) –Statistical transformation, by name;
"sum"when None. -
position(str or FeatureSpec, default:None) –Position adjustment: a name such as
"jitter"or aposition_*()spec. -
show_legend(bool, default:None) –False hides this layer from the legend.
-
inherit_aes(bool, default:None) –False ignores the plot's default mapping for this layer.
-
manual_key(str or FeatureSpec, default:None) –This layer's key in a manual legend: a label, or
layer_key(). -
sampling(str or FeatureSpec, default:None) –lets_plot sampling; accepted and ignored, as ggrust draws every row.
-
tooltips(FeatureSpec or list of str, default:None) –Tooltip content:
layer_tooltips(), a list of column names, or"none"to disable tooltips (HTML output). -
color_by(str, default:None) –Aesthetic the
colorscale applies to ("color"or"fill"). -
fill_by(str, default:None) –Aesthetic the
fillscale applies to ("color"or"fill"). -
na_rm(bool, default:None) –True removes rows with missing values silently; otherwise they are removed with a warning.
-
**other_args(Any) –Constant aesthetics such as
color="red"oralpha=0.5.
Returns:
-
LayerSpec–The layer.
Examples:
>>> from ggrust import *
>>> data = {"cylinders": [4, 4, 6, 8, 4, 6, 8, 8], "gears": [4, 4, 4, 3, 5, 4, 3, 3]}
>>> plot = ggplot(data, aes("cylinders", "gears")) + geom_count()