lets_plot.geom_freqpoly

lets_plot.geom_freqpoly(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, orientation=None, color_by=None, **other_args)

Display a line chart which makes the y value proportional to the number of observed variable values, mapped to x axis.

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.

statstr, default=’bin’

The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).

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’.

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

geom_freqpoly() connects the top points in geom_bar().

Computed variables:

• ..count.. : number of points with x-axis coordinate in the same bin.

geom_freqpoly() understands the following aesthetics mappings:

• x : x-axis value.

• y : y-axis value.

• alpha : transparency level of a layer. Accept values between 0 and 1.

• color (colour) : color of the geometry lines. String in the following formats: RGB/RGBA (e.g. “rgb(0, 0, 255)”); HEX (e.g. “#0000FF”); color name (e.g. “red”); role name (“pen”, “paper” or “brush”).

• size : lines width.

• linetype : type of the line of border. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.

Examples

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
np.random.seed(42)
data = {'x': np.random.normal(size=1000)}
ggplot(data, aes(x='x')) + geom_freqpoly()

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 1000
np.random.seed(42)
x = np.random.gamma(2.0, size=n)
c = np.random.choice(['a', 'b', 'c'], size=n)
ggplot({'x': x, 'c': c}, aes(x='x')) + \
    geom_freqpoly(aes(color='c'), size=1) + \
    geom_point(aes(color='c'), stat='bin', \
               shape=21, fill='white', size=3) + \
    facet_grid(x='c')