Waffle chart with custom style

This post explains how to reproduce a waffle chart and how to customize it. This post explains step-by-step how to replicate it with reproducible code and explanations

About

This page showcases the work of Benjamin Nowak who originally made the chart with R. This post is a translation to Python by Joseph Barbier. Thanks to him for accepting sharing his work here!

Let's see what the final picture will look like:

Libraries

First, you need to install the following librairies:

matplotlib is used for creating the chart and add customization features
pandas is used to put the data into a dataframe
datetime is used for dealing with the date format of our time variable

And that's it!

# Libraries
import matplotlib.pyplot as plt
import pandas as pd
from pywaffle import Waffle
from highlight_text import fig_text, ax_text
from pyfonts import load_font, load_exact_font

Dataset

For this reproduction, we're going to retrieve the data directly from the gallery's Github repo. This means we just need to give the right url as an argument to pandas' read_csv() function to retrieve the data.

Next, we use the melt() function to switch from one country per column to a single column with concatenated countries, while keeping the values in the original Time variable.

path = 'https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/share-cereals.csv'
df = pd.read_csv(path)


def remove_html_tag(s):
    return s.split('</b>')[0][3:]


df['lab'] = df['lab'].apply(remove_html_tag)
df = df[df['type'] == 'feed']
df.reset_index(inplace=True)
df

	index	lab	type	percent
0	0	Africa	feed	21
1	2	Americas	feed	53
2	4	Asia	feed	32
3	6	Europe	feed	66
4	8	Oceania	feed	59

Basic waffle chart

In order to create the following chart, we:

determine how many charts to create based on the number of rows in the DataFrame
set up a figure with multiple subplots, one for each row of data (5)
for each row in the DataFrame:
- It extracts the share.
- It creates a waffle chart showing this share.
each waffle chart uses a 4x25 grid (100 squares total) to represent the percentage.

number_of_bars = len(df)  # one bar per continent

# Init the whole figure and axes
fig, axs = plt.subplots(
   nrows=number_of_bars,
   ncols=1,
   figsize=(8, 8)
)

# Iterate over each bar and create it
for (i, row), ax in zip(df.iterrows(), axs):

    share = row['percent']
    values = [share, 100-share]

    Waffle.make_waffle(
        ax=ax,
        rows=4,
        columns=25,
        values=values
    )

plt.show()

Custom colors

The colors are changed thanks tot he colors argument in Waffle.make_waffle(), and the set_facecolor() for the background

Note: the colors used are slightly different from the original colors.

background_color = "#222725"
pink = "#f72585"
dark_pink = "#7a0325"

number_of_bars = len(df)  # one bar per continent

# Init the whole figure and axes
fig, axs = plt.subplots(
   nrows=number_of_bars,
   ncols=1,
   figsize=(8, 8)
)
fig.set_facecolor(background_color)


# Iterate over each bar and create it
for (i, row), ax in zip(df.iterrows(), axs):

    share = row['percent']
    values = [share, 100-share]

    Waffle.make_waffle(
        ax=ax,
        rows=4,
        columns=25,
        values=values,
        colors=[pink, dark_pink],
    )

plt.show()

Title and credit

In order to add annotation, we need 2 new tools:

pyfonts to load the fonts
highlight_text to custom the text style

highlight_text provides the fig_text() and ax_text() functions (you can learn in this post that extensively describes how they work.)

font_title = load_font("Staatliches")
font_credit = load_exact_font("https://github.com/impallari/Raleway/raw/master/fonts/v4020/Raleway-v4020-Light.otf")
bold_font_credit = load_exact_font("https://github.com/impallari/Raleway/raw/master/fonts/v4020/Raleway-v4020-Bold.otf")

background_color = "#222725"
pink = "#f72585"
dark_pink = "#7a0325"

number_of_bars = len(df)  # one bar per continent

# Init the whole figure and axes
fig, axs = plt.subplots(
   nrows=number_of_bars,
   ncols=1,
   figsize=(8, 8),
   dpi=300
)
fig.set_facecolor(background_color)
ax.set_facecolor('white')


# Iterate over each bar and create it
for (i, row), ax in zip(df.iterrows(), axs):

    share = row['percent']
    values = [share, 100-share]

    Waffle.make_waffle(
        ax=ax,
        rows=4,
        columns=25,
        values=values,
        colors=[pink, dark_pink],
    )

    text = f"{row['lab']}"
    ax.text(
        x=-0.4, y=0.5, s=text,
        font=bold_font_credit, color='white', rotation=90,
        ha='center', va='center', fontsize=13
    )
    text = f"{share}%"
    ax.text(
        x=-0.2, y=0.5, s=text,
        font=font_credit, color='white', rotation=90,
        ha='center', va='center', fontsize=13
    )

fig_text(
    x=0.05, y=0.95, s="SHARE OF CEREALS USED AS <ANIMAL FEEDS>",
    highlight_textprops=[{'color': pink}], color='white',
    fontsize=22, font=font_title
)
fig_text(
    x=0.05, y=0.05, s="<Data> OWID (year 2021) | <Plot> Benjamin Nowak",
    font=font_credit, color="white", fontsize=10,
    highlight_textprops=[{'font': bold_font_credit}]*2
)

plt.savefig('../../static/graph/web-waffle-chart-as-share.png', dpi=300)
plt.show()

Going further

This article explains how to reproduce a waffle chart with custom colors and fonts.

Contact & Edit

👋 This document is a work by Yan Holtz. You can contribute on github, send me a feedback on twitter or subscribe to the newsletter to know when new examples are published! 🔥

This page is just a jupyter notebook, you can edit it here. Please help me making this website better 🙏!