Routines for plotting areaweighted two and threecircle venn diagrams.
Install the package as usual via pip
:
$ python m pip install matplotlibvenn
Since version 1.1.0 the package includes an extra "cost based" layout algorithm for venn3 diagrams, that relies on the shapely package, which is not installed as a default dependency. If you need the new algorithm (or just have nothing against installing shapely along the way), instead do:
$ python m pip install "matplotlibvenn[shapely]"
It is quite probable that shapely will become a required dependency eventually in one of the future versions.

numpy
, 
scipy
, 
matplotlib
, 
shapely
(optional).
The package provides four main functions: venn2
,
venn2_circles
, venn3
and venn3_circles
.
The functions venn2
and venn2_circles
accept as their only
required argument a 3element tuple (Ab, aB, AB)
of subset sizes,
and draw a twocircle venn diagram with respective region areas, e.g.:
venn2(subsets = (3, 2, 1))
In this example, the region, corresponding to subset A and not B
will
be three times larger in area than the region, corresponding to subset A and B
.
You can also provide a tuple of two set
or Counter
(i.e. multiset)
objects instead (new in version 0.7), e.g.:
venn2((set(['A', 'B', 'C', 'D']), set(['D', 'E', 'F'])))
Similarly, the functions venn3
and venn3_circles
take a
7element tuple of subset sizes (Abc, aBc, ABc, abC, AbC, aBC,
ABC)
, and draw a threecircle areaweighted Venn
diagram:
Alternatively, a tuple of three set
or Counter
objects may be provided.
The functions venn2
and venn3
draw the diagrams as a collection of colored
patches, annotated with text labels. The functions venn2_circles
and
venn3_circles
draw just the circles.
The functions venn2_circles
and venn3_circles
return the list of matplotlib.patch.Circle
objects that may be tuned further
to your liking. The functions venn2
and venn3
return an object of class VennDiagram
,
which gives access to constituent patches, text elements, and (since
version 0.7) the information about the centers and radii of the
circles.
Basic Example:
from matplotlib_venn import venn2 venn2(subsets = (3, 2, 1))
For the threecircle case:
from matplotlib_venn import venn3 venn3(subsets = (1, 1, 1, 2, 1, 2, 2), set_labels = ('Set1', 'Set2', 'Set3'))
A more elaborate example:
from matplotlib import pyplot as plt import numpy as np from matplotlib_venn import venn3, venn3_circles plt.figure(figsize=(4,4)) v = venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C')) v.get_patch_by_id('100').set_alpha(1.0) v.get_patch_by_id('100').set_color('white') v.get_label_by_id('100').set_text('Unknown') v.get_label_by_id('A').set_text('Set "A"') c = venn3_circles(subsets=(1, 1, 1, 1, 1, 1, 1), linestyle='dashed') c[0].set_lw(1.0) c[0].set_ls('dotted') plt.title("Sample Venn diagram") plt.annotate('Unknown set', xy=v.get_label_by_id('100').get_position()  np.array([0, 0.05]), xytext=(70,70), ha='center', textcoords='offset points', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1), arrowprops=dict(arrowstyle='>', connectionstyle='arc3,rad=0.5',color='gray')) plt.show()
An example with multiple subplots:
from matplotlib_venn import venn2, venn2_circles figure, axes = plt.subplots(2, 2) venn2(subsets={'10': 1, '01': 1, '11': 1}, set_labels = ('A', 'B'), ax=axes[0][0]) venn2_circles((1, 2, 3), ax=axes[0][1]) venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'), ax=axes[1][0]) venn3_circles({'001': 10, '100': 20, '010': 21, '110': 13, '011': 14}, ax=axes[1][1]) plt.show()
Perhaps the most common use case is generating a Venn diagram given three sets of objects:
set1 = set(['A', 'B', 'C', 'D']) set2 = set(['B', 'C', 'D', 'E']) set3 = set(['C', 'D',' E', 'F', 'G']) venn3([set1, set2, set3], ('Set1', 'Set2', 'Set3')) plt.show()
Note that for a threecircle venn diagram it is not in general possible to achieve exact correspondence between the required set sizes and region areas. The default layout algorithm aims to correctly represent:
 Relative areas of the full individual sets (A, B, C).
 Relative areas of pairwise intersections of sets (A&B, A&C, B&C, not to be confused with the regions A&B&~C, A&~B&C, ~A&B&C, on the diagram).
Sometimes the result is unsatisfactory and either the area weighting or the layout logic needs to be tuned.
The area weighing can be adjusted by providing a fixed_subset_sizes argument to the DefaultLayoutAlgorithm:
from matplotlib_venn.layout.venn2 import DefaultLayoutAlgorithm venn2((1,2,3), layout_algorithm=DefaultLayoutAlgorithm(fixed_subset_sizes=(1,1,1))) from matplotlib_venn.layout.venn3 import DefaultLayoutAlgorithm venn3((7,6,5,4,3,2,1), layout_algorithm=DefaultLayoutAlgorithm(fixed_subset_sizes=(1,1,1,1,1,1,1)))
In the above examples the diagram regions will be plotted as if venn2((1,1,1)) and venn3((1,1,1,1,1,1,1)) were invoked, yet the actual numbers will be (1,2,3) and (7,6,5,4,3,2,1) respectively.
The diagram can be tuned further by switching the layout algorithm to a different implementation. At the moment the package offers an alternative layout algorithm for venn3 diagrams that lays the circles out by optimizing a userprovided cost function. The following examples illustrate its usage:
from matplotlib_venn.layout.venn3 import cost_based subset_sizes = (100,200,10000,10,20,3,1) venn3(subset_sizes, layout_algorithm=cost_based.LayoutAlgorithm()) alg = cost_based.LayoutAlgorithm(cost_fn=cost_based.WeightedAggregateCost(transform_fn=lambda x: x)) venn3(subset_sizes, layout_algorithm=alg) alg = cost_based.LayoutAlgorithm(cost_fn=cost_based.WeightedAggregateCost(weights=(0,0,0,1,1,1,1))) venn3(subset_sizes, layout_algorithm=alg)
The default "pairwise" algorithm is, theoretically, a special case of the costbased method with the respective cost function:
alg = cost_based.LayoutAlgorithm(cost_fn=cost_based.pairwise_cost) venn3(subset_sizes, layout_algorithm=alg)
(The latter plot will be close, but not perfectly equal to the outcome of DefaultLayoutAlgorithm()).
Note that the import:
from matplotlib_venn.layout.venn3 import cost_based
will fail unless you have the optional shapely package installed (see "Installation" above).
 If you ask your questions at StackOverflow and tag them matplotlibvenn, chances are high you could get an answer from the maintainer of this package.

Report issues and submit fixes at Github: https://github.com/konstantint/matplotlibvenn
Check out the
DEVELOPERREADME.rst
for developmentrelated notes. 
Some alternative means of plotting a Venn diagram (as of October 2012) are reviewed in the blog post: http://fouryears.eu/2012/10/13/venndiagramsinpython/

The matplotlibsubsets package visualizes a hierarchy of sets as a tree of rectangles.

The matplotlib_set_diagrams package is a GPLlicensed alternative that offers a different layout algorithm, which supports more than three sets and provides a cool ability to incorporate wordclouds into your Venn (Euler) diagrams.