🧇 Make Waffle Charts in Python.

Overview

PyWaffle

PyPI version ReadTheDocs Binder

PyWaffle is an open source, MIT-licensed Python package for plotting waffle charts.

It provides a Figure constructor class Waffle, which could be passed to matplotlib.pyplot.figure and generates a matplotlib Figure object.

PyPI Page: https://pypi.org/project/pywaffle/

Documentation: http://pywaffle.readthedocs.io/

Installation

pip install pywaffle

Requirements

  • Python 3.5+
  • Matplotlib

Examples

1. Value Scaling

import matplotlib.pyplot as plt
from pywaffle import Waffle
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    columns=10, 
    values=[48, 46, 6],
    figsize=(5, 3)
)
plt.show()

basic

The values are automatically scaled to 24, 23 and 3 to fit 5 * 10 chart size.

2. Values in dict & Auto-sizing

data = {'Democratic': 48, 'Republican': 46, 'Libertarian': 3}
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    values=data, 
    legend={'loc': 'upper left', 'bbox_to_anchor': (1.1, 1)}
)
plt.show()

Use values in dictionary; use absolute value as block number, without defining columns

In this example, since only rows is specified and columns is empty, absolute values in values are used as block numbers. Similarly, rows could also be optional if columns is specified.

If values is a dict, its keys are used as labels.

3. Title, Legend, Colors, Background Color, Block Color, Direction and Style

data = {'Democratic': 48, 'Republican': 46, 'Libertarian': 3}
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    values=data, 
    colors=["#232066", "#983D3D", "#DCB732"],
    title={'label': 'Vote Percentage in 2016 US Presidential Election', 'loc': 'left'},
    labels=[f"{k} ({v}%)" for k, v in data.items()],
    legend={'loc': 'lower left', 'bbox_to_anchor': (0, -0.4), 'ncol': len(data), 'framealpha': 0},
    starting_location='NW',
    block_arranging_style='snake'
)
fig.set_facecolor('#EEEEEE')
plt.show()

Add title, legend and background color; customize the block color

Many parameters, like title and legend, accept the same parameters as in Matplotlib.

4. Plot with Icons - Pictogram Chart

data = {'Democratic': 48, 'Republican': 46, 'Libertarian': 3}
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    values=data, 
    colors=["#232066", "#983D3D", "#DCB732"],
    legend={'loc': 'upper left', 'bbox_to_anchor': (1, 1)},
    icons='child', 
    font_size=12, 
    icon_legend=True
)
plt.show()

Use Font Awesome icons

PyWaffle supports Font Awesome icons in the chart.

5. Multiple Plots in One Chart

import pandas as pd
data = pd.DataFrame(
    {
        'labels': ['Hillary Clinton', 'Donald Trump', 'Others'],
        'Virginia': [1981473, 1769443, 233715],
        'Maryland': [1677928, 943169, 160349],
        'West Virginia': [188794, 489371, 36258],
    },
).set_index('labels')

# A glance of the data:
#                  Maryland  Virginia  West Virginia
# labels                                            
# Hillary Clinton   1677928   1981473         188794
# Donald Trump       943169   1769443         489371
# Others             160349    233715          36258


fig = plt.figure(
    FigureClass=Waffle,
    plots={
        '311': {
            'values': data['Virginia'] / 30000,
            'labels': [f"{k} ({v})" for k, v in data['Virginia'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8},
            'title': {'label': '2016 Virginia Presidential Election Results', 'loc': 'left'}
        },
        '312': {
            'values': data['Maryland'] / 30000,
            'labels': [f"{k} ({v})" for k, v in data['Maryland'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.2, 1), 'fontsize': 8},
            'title': {'label': '2016 Maryland Presidential Election Results', 'loc': 'left'}
        },
        '313': {
            'values': data['West Virginia'] / 30000,
            'labels': [f"{k} ({v})" for k, v in data['West Virginia'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.3, 1), 'fontsize': 8},
            'title': {'label': '2016 West Virginia Presidential Election Results', 'loc': 'left'}
        },
    },
    rows=5,  # outside parameter applied to all subplots
    colors=["#2196f3", "#ff5252", "#999999"],  # outside parameter applied to all subplots
    figsize=(9, 5)
)
plt.show()

Multiple plots

In this chart, 1 block = 30000 votes.

Data source https://en.wikipedia.org/wiki/United_States_presidential_election,_2016.

Demo

Wanna try it yourself? There is Online Demo!

What's New

See CHANGELOG

License

  • PyWaffle is under MIT license, see LICENSE file for the details.
  • The Font Awesome font is licensed under the SIL OFL 1.1: http://scripts.sil.org/OFL
Owner
Guangyang Li
Guangyang Li
Moscow DEG 2021 elections plots

Построение графиков на основе публичных данных о ДЭГ в Москве в 2021г. Описание Скрипты в данном репозитории позволяют собственноручно построить графи

9 Jul 15, 2022
NW 2022 Hackathon Project by Angelique Clara Hanzel, Aryan Sonik, Damien Fung, Ramit Brata Biswas

Spiral-Data-Visualizer NW 2022 Hackathon Project by Angelique Clara Hanzell, Aryan Sonik, Damien Fung, Ramit Brata Biswas Description This project vis

Damien Fung 2 Jan 16, 2022
Color maps for POV-Ray v3.7 from the Plasma, Inferno, Magma and Viridis color maps in Python's Matplotlib

POV-Ray-color-maps Color maps for POV-Ray v3.7 from the Plasma, Inferno, Magma and Viridis color maps in Python's Matplotlib. The include file Color_M

Tor Olav Kristensen 1 Apr 05, 2022
A Jupyter - Leaflet.js bridge

ipyleaflet A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook. Usage Selecting a basemap for a leaflet map: Loading a geojso

Jupyter Widgets 1.3k Dec 27, 2022
Plot, scatter plots and histograms in the terminal using braille dots

Plot, scatter plots and histograms in the terminal using braille dots, with (almost) no dependancies. Plot with color or make complex figures - similar to a very small sibling to matplotlib. Or use t

Tammo Ippen 207 Dec 30, 2022
Domain Connectivity Analysis Tools to analyze aggregate connectivity patterns across a set of domains during security investigations

DomainCAT (Domain Connectivity Analysis Tool) Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of dom

DomainTools 34 Dec 09, 2022
Interactive Dashboard for Visualizing OSM Data Change

Dashboard and intuitive data downloader for more interactive experience with interpreting osm change data.

1 Feb 20, 2022
CONTRIBUTIONS ONLY: Voluptuous, despite the name, is a Python data validation library.

CONTRIBUTIONS ONLY What does this mean? I do not have time to fix issues myself. The only way fixes or new features will be added is by people submitt

Alec Thomas 1.8k Dec 31, 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
HW 02 for CS40 - matplotlib practice

HW 02 for CS40 - matplotlib practice project instructions https://github.com/mikeizbicki/cmc-csci040/tree/2021fall/hw_02 Drake Lyric Analysis Bar Char

13 Oct 27, 2021
Visualize and compare datasets, target values and associations, with one line of code.

In-depth EDA (target analysis, comparison, feature analysis, correlation) in two lines of code! Sweetviz is an open-source Python library that generat

Francois Bertrand 2.3k Jan 05, 2023
BrowZen correlates your emotional states with the web sites you visit to give you actionable insights about how you spend your time browsing the web.

BrowZen BrowZen correlates your emotional states with the web sites you visit to give you actionable insights about how you spend your time browsing t

Nick Bild 36 Sep 28, 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
nvitop, an interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

Xuehai Pan 1.3k Jan 02, 2023
patchwork for matplotlib

patchworklib patchwork for matplotlib test code Preparation of example plots import seaborn as sns import numpy as np import pandas as pd #Bri

Mori Hideto 185 Jan 06, 2023
Tools for exploratory data analysis in Python

Dora Exploratory data analysis toolkit for Python. Contents Summary Setup Usage Reading Data & Configuration Cleaning Feature Selection & Extraction V

Nathan Epstein 599 Dec 25, 2022
LinkedIn connections analyzer

LinkedIn Connections Analyzer 🔗 https://linkedin-analzyer.herokuapp.com Hey hey 👋 , welcome to my LinkedIn connections analyzer. I recently found ou

Okkar Min 5 Sep 13, 2022
Show Data: Show your dataset in web browser!

Show Data is to generate html tables for large scale image dataset, especially for the dataset in remote server. It provides some useful commond line tools and fully customizeble API reference to gen

Dechao Meng 83 Nov 26, 2022
Advanced hot reloading for Python

The missing element of Python - Advanced Hot Reloading Details Reloadium adds hot reloading also called "edit and continue" functionality to any Pytho

Reloadware 1.9k Jan 04, 2023
This is my favourite function - the Rastrigin function.

This is my favourite function - the Rastrigin function. What sparked my curiosity and interest in the function was its complexity in terms of many local optimum points, which makes it particularly in

1 Dec 27, 2021