class plotnine.stats.stat_sina(mapping: Aes | None = None, data: DataLike | None = None, **kwargs: Any)[source]

Compute Sina plot values


stat_sina(mapping=None, data=None, geom='sina', position='dodge', na_rm=False,
          random_state=None, maxwidth=None, bin_limit=1, binwidth=None,
          bw='nrd0', bins=None, method='density', adjust=1, scale='area',

Only the mapping and data can be positional, the rest must be keyword arguments. **kwargs can be aesthetics (or parameters) used by the geom.

mappingaes, optional

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.


Default value



The bold aesthetics are required.

Options for computed aesthetics

'quantile'  # quantile
'group'     # group identifier

Calculated aesthetics are accessed using the after_stat function. e.g. after_stat('quantile').

datadataframe, optional

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

geomstr or geom, optional (default: geom_sina)

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.

positionstr or position, optional (default: position_dodge)

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rmbool, optional (default: False)

If False, removes missing values with a warning. If True silently removes missing values.


The width of the bins. The default is to use 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.

binsint (default: 50)

Number of bins. Overridden by binwidth.

method'density' or 'counts'

Choose the method to spread the samples within the same bin along the x-axis. Available methods: "density", "counts" (can be abbreviated, e.g. "d"). See Details.


Control the maximum width the points can spread into. Values should be in the range (0, 1).

adjustfloat, optional (default: 1)

Adjusts the bandwidth of the density kernel when method='density' (see density).

bwstr or float, optional (default: 'nrd0')

The bandwidth to use, If a float is given, it is the bandwidth. The str choices are:


nrd0 is a port of stats::bw.nrd0 in R; it is eqiuvalent to silverman when there is more than 1 value in a group.

bin_limitint (default: 1)

If the samples within the same y-axis bin are more than bin_limit, the samples's X coordinates will be adjusted. This parameter is effective only when method='counts'

random_stateint or RandomState, optional

Seed or Random number generator to use. If None, then numpy global generator numpy.random is used.

scalestr (default: area)

How to scale the sina groups. The options are:

'area'   # Scale by the largest density/bin amoung the different
         # sinas

'count'  # areas are scaled proportionally to the number of points

'width'  # Only scale according to the maxwidth parameter.