Area-weighted venn-diagrams for Python/matplotlib

Overview

Venn diagram plotting routines for Python/Matplotlib

https://travis-ci.org/konstantint/matplotlib-venn.png?branch=master

Routines for plotting area-weighted two- and three-circle venn diagrams.

Installation

The simplest way to install the package is via easy_install or pip:

$ easy_install matplotlib-venn

Dependencies

  • numpy,
  • scipy,
  • matplotlib.

Usage

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 3-element list (Ab, aB, AB) of subset sizes, e.g.:

venn2(subsets = (3, 2, 1))

and draw a two-circle venn diagram with respective region areas. In the particular 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. Alternatively, you can simply provide a list of two set or Counter (i.e. multi-set) 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 7-element list of subset sizes (Abc, aBc, ABc, abC, AbC, aBC, ABC), and draw a three-circle area-weighted venn diagram. Alternatively, you can provide a list of three set or Counter objects (rather than counting sizes for all 7 subsets).

The functions venn2_circles and venn3_circles draw just the circles, whereas the functions venn2 and venn3 draw the diagrams as a collection of colored patches, annotated with text labels. In addition (version 0.7+), functions venn2_unweighted and venn3_unweighted draw the Venn diagrams without area-weighting.

Note that for a three-circle venn diagram it is not in general possible to achieve exact correspondence between the required set sizes and region areas, however in most cases the picture will still provide a decent indication.

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 three-circle 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 (new in version 0.6):

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()

Questions

  • If you ask your questions at StackOverflow and tag them matplotlib-venn, chances are high you'll get an answer from the maintainer of this package.

See also

Owner
Konstantin Tretyakov
Konstantin Tretyakov
Material for dataviz course at university of Bordeaux

Material for dataviz course at university of Bordeaux

Nicolas P. Rougier 50 Jul 17, 2022
Pydrawer: The Python package for visualizing curves and linear transformations in a super simple way

pydrawer 📐 The Python package for visualizing curves and linear transformations in a super simple way. ✏️ Installation Install pydrawer package with

Dylan Tintenfich 56 Dec 30, 2022
A TileDB backend for xarray.

TileDB-xarray This library provides a backend engine to xarray using the TileDB Storage Engine. Example usage: import xarray as xr dataset = xr.open_d

TileDB, Inc. 14 Jun 02, 2021
Exploratory analysis and data visualization of aircraft accidents and incidents in Brazil.

Exploring aircraft accidents in Brazil Occurrencies with aircraft in Brazil are investigated by the Center for Investigation and Prevention of Aircraf

Augusto Herrmann 5 Dec 14, 2021
Type-safe YAML parser and validator.

StrictYAML StrictYAML is a type-safe YAML parser that parses and validates a restricted subset of the YAML specification. Priorities: Beautiful API Re

Colm O'Connor 1.2k Jan 04, 2023
paintable GitHub contribute table

githeart paintable github contribute table how to use: Functions key color select 1,2,3,4,5 clear c drawing mode mode on turn off e print paint matrix

Bahadır Araz 27 Nov 24, 2022
:small_red_triangle: Ternary plotting library for python with matplotlib

python-ternary This is a plotting library for use with matplotlib to make ternary plots plots in the two dimensional simplex projected onto a two dime

Marc 611 Dec 29, 2022
Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python

Petrel Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python. NOTE: The base Storm package provides storm.py, which

AirSage 247 Dec 18, 2021
3D rendered visualization of the austrian monuments registry

Visualization of the Austrian Monuments Visualization of the monument landscape of the austrian monuments registry (Bundesdenkmalamt Denkmalverzeichni

Nikolai Janakiev 3 Oct 24, 2019
Editor and Presenter for Manim Generated Content.

Editor and Presenter for Manim Generated Content. Take a look at the Working Example. More information can be found on the documentation. These Browse

Manim Community 149 Dec 29, 2022
Lime: Explaining the predictions of any machine learning classifier

lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict

Marco Tulio Correia Ribeiro 10.3k Dec 29, 2022
Data visualization electromagnetic spectrum

Datenvisualisierung-Elektromagnetischen-Spektrum Anhand des Moduls matplotlib sollen die Daten des elektromagnetischen Spektrums dargestellt werden. D

Pulsar 1 Sep 01, 2022
Small binja plugin to import header file to types

binja-import-header (v1.0.0) Author: matteyeux Import header file to Binary Ninja types view Description: Binary Ninja plugin to import types from C h

matteyeux 15 Dec 10, 2022
A grammar of graphics for Python

plotnine Latest Release License DOI Build Status Coverage Documentation plotnine is an implementation of a grammar of graphics in Python, it is based

Hassan Kibirige 3.3k Jan 01, 2023
2D maze path solver visualizer implemented with python

2D maze path solver visualizer implemented with python

SS 14 Dec 21, 2022
🎨 Python3 binding for `@AntV/G2Plot` Plotting Library .

PyG2Plot 🎨 Python3 binding for @AntV/G2Plot which an interactive and responsive charting library. Based on the grammar of graphics, you can easily ma

hustcc 990 Jan 05, 2023
Lightweight, extensible data validation library for Python

Cerberus Cerberus is a lightweight and extensible data validation library for Python. v = Validator({'name': {'type': 'string'}}) v.validate({

eve 2.9k Dec 27, 2022
Collection of scripts for making high quality beautiful math-related posters.

Poster Collection of scripts for making high quality beautiful math-related posters. The poster can have as large printing size as 3x2 square feet wit

Nattawut Phetmak 3 Jun 09, 2022
Small project to recursively calculate and plot each successive order of the Hilbert Curve

hilbert-curve Small project to recursively calculate and plot each successive order of the Hilbert Curve. After watching 3Blue1Brown's video on Hilber

Stefan Mejlgaard 2 Nov 15, 2021
A deceptively simple plotting library for Streamlit

🍅 Plost A deceptively simple plotting library for Streamlit. Because you've been writing plots wrong all this time. Getting started pip install plost

Thiago Teixeira 192 Dec 29, 2022