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

Displays kernel density estimate, which is a smoothed version of the histogram.

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

  • data (dict or 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.

  • stat (str, default=’density’) – 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).

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

  • show_legend (bool, default=True) – False - do not show legend for this layer.

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

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

  • kernel (str, 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’).

  • bw (str or float) – The method (or exact value) of bandwidth. Either a string (choose among ‘nrd0’ and ‘nrd’), or a float.

  • adjust (float) – Adjust the value of bandwidth my multiplying it. Changes how smooth the frequency curve is.

  • n (int, default=512) – The number of sampled points for plotting the function.

  • fs_max (int, default=500) – Maximum size of data to use density computation with ‘full scan’. For bigger data, less accurate but more efficient density computation is applied.

  • 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.


Geom object specification.

Return type



Computed variables:

  • ..density.. : density estimate (mapped by default).

  • ..count.. : density * number of points.

  • ..scaled.. : density estimate, scaled to maximum of 1.

geom_density() understands the following aesthetics mappings:

  • x : x-axis coordinates.

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

  • color (colour) : color of a geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

  • fill : color of geometry filling.

  • size : lines width. Defines line width.

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

  • weight : used by ‘density’ stat to compute weighted density.


1import numpy as np
2from lets_plot import *
5x = np.random.normal(size=1000)
6ggplot({'x': x}, aes(x='x')) + geom_density()