plotnine.stat_bin_2d
stat_bin_2d(=None,
mapping=None,
data*,
="rect",
geom="identity",
position=False,
na_rm=30,
bins=None,
breaks=None,
binwidth=True,
drop**kwargs
)
2 Dimensional bin counts
Parameters
mapping : aes = None

Aesthetic mappings created with aes. If specified and
inherit_aes=True
, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.Aesthetic Default value x y fill after_stat('count')
weight None
The bold aesthetics are required.
Options for computed aesthetics
"xmin" # x lower bound for the bin "xmax" # x upper bound for the bin "ymin" # y lower bound for the bin "ymax" # y upper bound for the bin "count" # number of points in bin "density" # density of points in bin, scaled to integrate to 1
data : DataFrame = None

The data to be displayed in this layer. If
None
, the data from from theggplot()
call is used. If specified, it overrides the data from theggplot()
call. geom : str  geom = "rect"

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.
position : str  position = "identity"

Position adjustment. If it is a string, it must be registered and known to Plotnine.
na_rm : bool = False

If
False
, removes missing values with a warning. IfTrue
silently removes missing values. bins : int = 30

Number of bins. Overridden by binwidth.
breaks : array_like  tuple[array_like, array_like] = None

Bin boundaries. This supercedes the
binwidth
,bins
,center
andboundary
. It can be an array_like or a list of two array_likes to provide distinct breaks for thex
andy
axes. binwidth : float = None

The width of the bins. The default is to use bins bins that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.
drop : bool = False

If
True
, removes all cells with zero counts. **kwargs : Any = {}

Aesthetics or parameters used by the
geom
.