PyWaffle is an open source, MIT-licensed Python package for plotting waffle charts — also known as square pie charts, and, when drawn with icons, pictogram 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/
pip install pywaffleTo draw pictogram charts with Font Awesome icons, install the optional extra:
pip install "pywaffle[icons]"- Python 3.9+
- Matplotlib
- Font Awesome, optional, for
iconsonly —pip install "pywaffle[icons]"
A waffle chart is a grid of blocks where one block stands for a fixed quantity, so a proportion is something the reader can count rather than estimate from the angle of a pie slice.
These are the people aboard the Titanic. 2,201 of them in a grid of 100 blocks, so one block is about 22 people.
import matplotlib.pyplot as plt
from pywaffle import waffle_chart
aboard = {"First class": 325, "Second class": 285, "Third class": 706, "Crew": 885}
class_colors = ["#c9a227", "#5f8a8b", "#b5653f", "#3d4f5d"]
aside = {"loc": "upper left", "bbox_to_anchor": (1.02, 1), "frameon": False}
fig, ax = waffle_chart(
aboard,
rows=10,
columns=10,
colors=class_colors,
title={"label": "Who was aboard the Titanic: 2,201 people", "loc": "left"},
legend=aside,
show_values=True,
figsize=(6.5, 4),
)
Swap the rectangles for Font Awesome icons and it becomes a pictogram chart, where one figure stands for a number of people:
by_group = {"Men": 1667, "Women": 425, "Children": 109}
fig, ax = waffle_chart(
by_group,
rows=5,
columns=10,
colors=["#3d4f5d", "#c9a227", "#b5653f"],
icons=["person", "person-dress", "child"],
font_size=22,
icon_legend=True,
background_color="#f4f2ee",
title={"label": "One figure = 44 people aboard", "loc": "left"},
legend=aside,
show_values=True,
figsize=(6.5, 2.8),
)
waffle_chart() returns the matplotlib (figure, axes) pair, so everything you already know about
matplotlib still applies. Pass ax to draw into a layout you have already built.
PyWaffle is also a matplotlib Figure constructor class, which is the form used throughout the examples below and is fully supported:
fig = plt.figure(FigureClass=Waffle, rows=10, columns=10, values=aboard)Both build the same chart. Use whichever reads better in your code.
Read the full quickstart for partial blocks that lose nothing to rounding, continuous tiled grids, sorting, subplots, and drawing into an existing layout.
Figures from the British Board of Trade inquiry of 1912: 2,201 aboard, 710 saved, 1,491 lost. Tabulated at Sinking of the Titanic.
Every example below uses the same dataset as the quickstart: the people aboard the Titanic.
import matplotlib.pyplot as plt
from pywaffle import Wafflefig = plt.figure(
FigureClass=Waffle,
rows=5,
columns=10,
values=[325, 285, 706, 885],
figsize=(5, 3)
)
plt.show()
Those are the first class, second class, third class and crew counts, 2,201 people in all. They are automatically scaled to 7, 6, 16 and 20 to fit the 5 * 10 chart size, so one block stands for about 22 people.
FigureClass and figsize are parameters of matplotlib.pyplot.figure, you may find the full parameter list on matplotlib.pyplot.figure function reference.
Other parameters, including rows, columns, and values in this example, are from Waffle, and see PyWaffle's API Reference for details.
data = {'First class': 6, 'Second class': 24, 'Third class': 79}
fig = plt.figure(
FigureClass=Waffle,
rows=5,
values=data,
legend={'loc': 'upper left', 'bbox_to_anchor': (1.05, 1)},
)
plt.show()
These are the children aboard, so here one block really is one child.
In this example, 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, the keys will be used as labels in the legend.
data = {'First class': 325, 'Second class': 285, 'Third class': 706, 'Crew': 885}
fig = plt.figure(
FigureClass=Waffle,
rows=5,
columns=10,
values=data,
colors=["#c9a227", "#5f8a8b", "#b5653f", "#3d4f5d"],
title={'label': 'Who was aboard the Titanic', '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',
vertical=True
)
fig.set_facecolor('#EEEEEE')
plt.show()
Parameter colors allows you to change the block color, and it accepts a list of colors that matplotlib can recognize, including hex, RGB in tuple, single character notation, etc. See Matplotlib Colors for details.
Parameter title and legend accept the same parameters as in Matplotlib, matplotlib.pyplot.title and matplotlib.pyplot.legend.
Parameter starting_location and vertical control Where to Start First Block and Plotting Direction. Together they fill from the top left along each row, so the four groups read in order, the way a line of text does.
There is also block_arranging_style, which can start each category on a new line or lay the blocks out in a snake. See Where to Start Each Category.
You may find more details under Examples section in PyWaffle Documentation.
data = {'Men': 1667, 'Women': 425, 'Children': 109}
fig = plt.figure(
FigureClass=Waffle,
rows=5,
columns=10,
values=data,
colors=["#3d4f5d", "#c9a227", "#b5653f"],
legend={'loc': 'upper left', 'bbox_to_anchor': (1, 1)},
icons=['person', 'person-dress', 'child'],
font_size=18,
icon_legend=True
)
plt.show()
The same 2,201 people, cut by group instead of by class. One figure stands for about 44 of them.
PyWaffle supports Font Awesome icons in the chart. Font Awesome is an optional dependency, installed with pip install "pywaffle[icons]". See Plot with Characters or Icons for details.
fig = plt.figure()
ax = fig.add_subplot(111)
# Modify existed axis
ax.set_title("Axis Title")
ax.set_aspect(aspect="equal")
Waffle.make_waffle(
ax=ax, # pass axis to make_waffle
rows=5,
columns=10,
values=[710, 1491],
title={"label": "Survived and lost", "loc": "left"}
)
710 of the 2,201 aboard survived.
import pandas as pd
data = pd.DataFrame(
{
'labels': ['Men', 'Women', 'Children'],
'First class': [175, 144, 6],
'Second class': [168, 93, 24],
'Third class': [462, 165, 79],
},
).set_index('labels')
# A glance of the data:
# First class Second class Third class
# labels
# Men 175 168 462
# Women 144 93 165
# Children 6 24 79
fig = plt.figure(
FigureClass=Waffle,
plots={
311: {
'values': data['First class'] / 10, # Convert actual number to a reasonable block number
'labels': [f"{k} ({v})" for k, v in data['First class'].items()],
'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8},
'title': {'label': 'First class', 'loc': 'left', 'fontsize': 12}
},
312: {
'values': data['Second class'] / 10,
'labels': [f"{k} ({v})" for k, v in data['Second class'].items()],
'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8},
'title': {'label': 'Second class', 'loc': 'left', 'fontsize': 12}
},
313: {
'values': data['Third class'] / 10,
'labels': [f"{k} ({v})" for k, v in data['Third class'].items()],
'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8},
'title': {'label': 'Third class', 'loc': 'left', 'fontsize': 12}
},
},
rows=5, # Outside parameter applied to all subplots, same as below
cmap_name="Accent", # Change color with cmap
rounding_rule='ceil', # Change rounding rule, so a value under 10 still gets at least 1 block
figsize=(6, 5)
)
fig.suptitle('Titanic passengers by class', fontsize=14, fontweight='bold')
fig.supxlabel('1 block = 10 people', fontsize=8, x=0.14)
fig.set_facecolor('#EEEDE7')
plt.show()
Each subplot is sized by its own class, so the widths show at a glance that third class carried more people than first and second combined.
Figures throughout from the British Board of Trade inquiry of 1912: 2,201 aboard, 710 saved, 1,491 lost. Tabulated at Sinking of the Titanic.
Wanna try it yourself? There is Online Demo!
See CHANGELOG
- PyWaffle is under MIT license, see
LICENSEfile for the details. - The Font Awesome font is licensed under the SIL OFL 1.1: http://scripts.sil.org/OFL