lets_plot.geom_function(mapping=None, *, data=None, stat=None, geom=None, position=None, show_legend=None, tooltips=None, fun=None, xlim=None, n=None, color_by=None, **other_args)#

Compute and draw a function.


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 used in this layer. Specify to describe the definition area of a function. If None, the default, the data will not be used at all.

statstr, default=’identity’

The statistical transformation to use on the data generated by the function. Supported transformations: ‘identity’ (leaves the data unchanged), ‘smooth’ (performs smoothing - linear default), ‘density2d’ (computes and draws 2D kernel density estimate).

geomstr, default=’line’

The geometry to display the function, 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.


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


A function of one variable in Python syntax.

xlimlist of float, default=[0.0, 1.0]

Range of the function. Float array of length 2.

nint, default=512

Number of points to interpolate along the x axis.

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

Define the color aesthetic for the geometry.


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.


Geom object specification.


geom_function() understands the following aesthetics mappings:

  • x : x-axis value.

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

  • color (colour) : color of the geometry. 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”).

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

  • size : line width.


1import numpy as np
2from scipy.stats import norm
3from lets_plot import *
6x = np.random.normal(size=500)
7ggplot() + \
8    geom_density(aes(x='x'), data={'x': x}) + \
9    geom_function(fun=norm.pdf, xlim=[-4, 4], color="red")

1from lets_plot import *
3data = {'x': list(range(-5, 6))}
4ggplot() + \
5    geom_function(aes(x='x', color='y', size='y'), \
6                  data=data, fun=lambda t: t**2, show_legend=False) + \
7    scale_color_gradient(low="red", high="green") + \
8    scale_size(range=[1, 4], trans='reverse')

 1from math import sqrt
 2from lets_plot import *
 4fun_layer = lambda fun: geom_function(fun=fun, xlim=[-2, 2], n=9, \
 5                                      stat='density2d', geom='density2d')
 7    ggplot() + fun_layer(lambda t: t),
 8    ggplot() + fun_layer(lambda t: t**2),
 9    ggplot() + fun_layer(lambda t: 2**t),
10    ggplot() + fun_layer(lambda t: sqrt(4 - t**2)) + coord_fixed(ratio=2),
11], ncol=2)