seaborn.objects.Agg#
- class seaborn.objects.Agg(func='mean')#
Aggregate data along the value axis using given method.
- Parameters:
- funcstr or callable
Name of a
pandas.Series
method or a vector -> scalar function.
See also
objects.Est
Aggregation with error bars.
Examples
The default behavior is to aggregate by taking a mean over each group:
p = so.Plot(diamonds, "clarity", "carat") p.add(so.Bar(), so.Agg())
Other aggregation functions can be selected by name if they are pandas methods:
p.add(so.Bar(), so.Agg("median"))
It’s also possible to pass an arbitrary aggregation function:
p.add(so.Bar(), so.Agg(lambda x: x.quantile(.75) - x.quantile(.25)))
When other mapping variables are assigned, they’ll be used to define aggregation groups. With some marks, it may be helpful to use additional transforms, such as
Dodge
:p.add(so.Bar(), so.Agg(), so.Dodge(), color="cut")
The variable that gets aggregated depends on the orientation of the layer, which is usually inferred from the coordinate variable types (but may also be specified with the
orient
parameter inPlot.add()
):so.Plot(diamonds, "carat", "clarity").add(so.Bar(), so.Agg())