lets_plot.stat_ecdf

lets_plot.stat_ecdf(mapping=None, *, data=None, geom=None, position=None, show_legend=None, sampling=None, tooltips=None, orientation=None, n=None, pad=None, color_by=None, **other_args)

Display the empirical cumulative distribution function.

Parameters:

mappingFeatureSpec

Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.

datadict or Pandas or Polars DataFrame

The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.

geomstr, default=’step’

The geometry to display the ecdf stat for this layer, as a string.

positionstr or FeatureSpec, default=’identity’

Position adjustment. Either a position adjustment name: ‘dodge’, ‘dodgev’, ‘jitter’, ‘nudge’, ‘jitterdodge’, ‘fill’, ‘stack’ or ‘identity’, or the result of calling a position adjustment function (e.g., position_dodge() etc.).

show_legendbool, default=True

False - do not show legend for this layer.

samplingFeatureSpec

Result of the call to the sampling_xxx() function. To prevent any sampling for this layer pass value “none” (string “none”).

tooltipslayer_tooltips

Result of the call to the layer_tooltips() function. Specify appearance, style and content.

orientationstr, default=’x’

Specify the axis that the layer’s stat and geom should run along. Possible values: ‘x’, ‘y’.

nint

If None, do not interpolate. If not None, this is the number of points to interpolate with.

padbool, default=True

If geometry is ‘step’ and pad=True, then the points at the ends: (-inf, 0) and (inf, 1) are added to the ecdf.

color_by{‘fill’, ‘color’, ‘paint_a’, ‘paint_b’, ‘paint_c’}, default=’color’

Define the color aesthetic for the geometry.

other_args

Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.

Returns:

LayerSpec

Geom object specification.

Notes

stat_ecdf() understands the following aesthetics mappings:

• x : x-axis coordinates.

• y : y-axis coordinates.

In addition, you can use any aesthetics, available for the geometry defined by the geom parameter.

Examples

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 100
np.random.seed(42)
x = np.random.normal(size=n)
ggplot({'x': x}, aes(x='x')) + stat_ecdf()

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 100
np.random.seed(42)
x = np.concatenate([
    np.random.normal(size=n),
    np.random.uniform(size=n),
    np.random.poisson(size=n),
])
g = ["A"] * n + ["B"] * n + ["C"] * n
p = ggplot({'x': x, 'g': g}, aes(x='x', color='g'))
gggrid([
    p + stat_ecdf() + ggtitle("pad=True (default)"),
    p + stat_ecdf(pad=False) + ggtitle("pad=False")
])

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 500
np.random.seed(42)
x = np.random.normal(size=n)
ggplot() + \
    stat_ecdf(aes(x=x), geom='point', n=20, \
              shape=21, color="#f03b20", fill="#ffeda0")