plotnine.stat_sina

stat_sina(mapping=None, data=None, **kwargs)

Compute Sina plot values

{usage}

Parameters

binwidth : float = None

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.

bins : int = 50

Number of bins. Overridden by binwidth.

method : Literal[density, counts] = "density"

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.

maxwidth : float = None

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

adjust : float = 1

Adjusts the bandwidth of the density kernel when method="density". see stat_density.

bw : str | float = "nrd0"

The bandwidth to use, If a float is given, it is the bandwidth. The str choices are: "nrd0", "normal_reference", "scott", "silverman"

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_limit : int = 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_state : int | RandomState = None

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

scale : Literal[area, count, width] = "area"

How to scale the sina groups.

area - Scale by the largest density/bin among the different sinas
count - areas are scaled proportionally to the number of points
width - Only scale according to the maxwidth parameter.

style

Type of sina plot to draw. The options are

'full'        # Regular (2 sided)
'left'        # Left-sided half
'right'       # Right-sided half
'left-right'  # Alternate (left first) half by the group
'right-left'  # Alternate (right first) half by the group

Parameters

See Also