lets_plot.geom_density2df(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, kernel=None, adjust=None, bw=None, n=None, bins=None, binwidth=None, **other_args)

Fill density function contour.


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 DataFrame 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=’density2df’

The statistical transformation to use on the data for this layer, as a string.

positionstr or FeatureSpec

Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.

show_legendbool, default=True

False - do not show legend for this layer.


Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.


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

kernelstr, default=’gaussian’

The kernel we use to calculate the density function. Choose among ‘gaussian’, ‘cosine’, ‘optcosine’, ‘rectangular’ (or ‘uniform’), ‘triangular’, ‘biweight’ (or ‘quartic’), ‘epanechikov’ (or ‘parabolic’).

bwstr or list of float

The method (or exact value) of bandwidth. Either a string (choose among ‘nrd0’ and ‘nrd’), or a float array of length 2.


Adjust the value of bandwidth by multiplying it. Changes how smooth the frequency curve is.

nlist of int

The number of sampled points for plotting the function (on x and y direction correspondingly).


Number of levels.


Distance between levels.


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_density2df() fills density contours.

Computed variables:

  • ..group.. : number of density estimate contour line.

geom_density2df() understands the following aesthetics mappings:

  • x : x-axis coordinates.

  • alpha : transparency level of a layer. Understands numbers between 0 and 1.

  • fill : color of geometry filling.

‘density2df’ statistical transformation combined with parameter value contour=False could be used to draw heatmaps (see the example below).


1import numpy as np
2from lets_plot import *
4n = 1000
6x = np.random.normal(size=n)
7y = np.random.normal(size=n)
8ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \
9    geom_density2df()