lets_plot.geom_lollipop(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, orientation=None, dir=None, fatten=None, slope=None, intercept=None, color_by=None, fill_by=None, **other_args)#

Draw lollipop chart.


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=’identity’

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.


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


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


Specify the axis that the layer’s stat and geom should run along. The default value (None) automatically determines the orientation based on the aesthetic mapping. If the automatic detection doesn’t work, it can be set explicitly by specifying the ‘x’ or ‘y’ orientation.

dir{‘v’, ‘h’, ‘s’}, default=’v’

Direction of the lollipop stick. ‘v’ for vertical, ‘h’ for horizontal, ‘s’ for orthogonal to the baseline.

fattenfloat, default=2.5

A multiplicative factor applied to size of the point.


The baseline slope.


The value of y at the point where the baseline crosses the y axis.

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

Define the color aesthetic for the geometry.

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

Define the fill 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_lollipop() understands the following aesthetics mappings:

  • x : x-axis value.

  • y : y-axis value.

  • alpha : transparency level of the point. 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”).

  • fill : fill color. Is applied only to the points of shapes having inner area. 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”).

  • shape : shape of the point, an integer from 0 to 25.

  • size : size of the point.

  • stroke : width of the shape border. Applied only to the shapes having border.

  • linewidth : stick width.

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

When slope=0, the baseline cannot be parallel to the lollipop sticks. So, in this case, if dir=’h’, the baseline will becomes vertical, as for infinity slope.


1from lets_plot import *
3data = {
4    'x': [-3, -2, -1, 0, 1, 2, 3],
5    'y': [2, 3, -2, 3, -1, 0, 4],
7ggplot(data, aes('x', 'y')) + geom_lollipop()

1import numpy as np
2from lets_plot import *
5data = {'v': np.random.randint(5, size=20)}
6ggplot(data, aes(y='v')) + \
7    geom_vline(xintercept=10) + \
8    geom_lollipop(stat='count', orientation='y', intercept=10, \
9                  fatten=5, linewidth=2)

 1from lets_plot import *
 3data = {
 4    'x': [-3, -2, -1, 0, 1, 2, 3],
 5    'y': [-1, -3, -2, 3, -1, 2, -1],
 6    'g': ['a', 'a', 'b', 'b', 'b', 'a', 'a'],
 8ggplot(data, aes('x', 'y')) + \
 9    geom_abline(slope=1, size=1.5, color="black") + \
10    geom_lollipop(aes(fill='g'), slope=1, shape=22, \
11                  size=5, stroke=2, color="black") + \
12    coord_fixed()