Scatter plots#

Scatter markers#

Bokeh includes a large variety of markers for creating scatter plots. For example, to render circle scatter markers on a plot, use the scatter() method of figure() with the default marker “circle”.

from bokeh.plotting import figure, show

p = figure(width=400, height=400)

# add a scatter circle renderer with a size, color, and alpha
p.scatter([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)

# show the results
show(p)

Similarly, use the scatter() method of figure() with the marker “square” to scatter square markers on a plot.

from bokeh.plotting import figure, show

p = figure(width=400, height=400)

# add a square scatter renderer with a size, color, and alpha
p.scatter([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], marker="square",
          size=20, color="olive", alpha=0.5)

# show the results
show(p)

Bokeh’s built-in scatter markers consist of a set of base markers, most of which can be combined with different kinds of additional visual features. This is an overview of all available scatter markers:

All the supported makers are available as individual methods of figure(), too. But it is recommended to use the scatter() method as best practice. To see details and example plots for any of the available scatter markers, click on the corresponding glyph method in the following list:

All the markers have the same set of properties: x, y, size (in screen units), and angle (in radians by default). The circle() marker is an exception: this method accepts an additional radius property that you can use with data units. This exception is not available when using “circle” as a maker in a scatter() call.

Image URLs#

It is also possible to make scatter plots using arbitrary images for markers using the image_url() glyph method. The example below demonstrates using a single image, but it is possible to pass a column of differnet URLs for every point.