94 of 100: Multi-level donut chart in matplotlib
At the beginning of the year I challenged myself to create all 100 visualizations using python and matplotlib from the 1 dataset,100 visualizations project and I am sharing with you the code for all the visualizations.
Note: Data Viz Project is copyright Ferdio and available under a Creative Commons Attribution – Non Commercial – No Derivatives 4.0 International license. I asked Ferdio and they told me they used a Design tool to create all the plots.
Collaborate
There are a ton of improvements that can be made on the code, so let me know in the comments any improvements you make and I will update the post accordingly!
To be improved: I wanted to do the background as wedges, but it took too long time to figure it out, so it has been made manually for now.
This is the original viz that we are trying to recreate in matplotlib:

Import the packages
We will need the following packages:
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import pandas as pd
from svgpathtools import svg2paths
from svgpath2mpl import parse_path
Generate the data
We could actually go from numpy to matplotlib, but most data projects use pandas to transform the data, so I am using a pandas dataframe as the starting point.
data = {
"year": [2004, 2022, 2004, 2022, 2004, 2022],
"countries" : [ "Denmark", "Denmark", "Norway", "Norway","Sweden", "Sweden",],
"sites": [4,10,5,8,13,15]
}
df= pd.DataFrame(data)
index | year | countries | sites |
---|---|---|---|
0 | 2004 | Sweden | 13 |
1 | 2022 | Sweden | 15 |
2 | 2004 | Denmark | 4 |
3 | 2022 | Denmark | 10 |
4 | 2004 | Norway | 5 |
5 | 2022 | Norway | 8 |
We need to create the subtotals for each year, the year labels and then sort the data. I also added a dummy row, for the first empty wedge of the pie. Ideally, this could have been done by splitting the pie. Will look into it later.
df['year_lbl'] ="'"+df['year'].astype(str).str[-2:].astype(str)
df['sub_total'] = df.groupby('year')['sites'].transform('sum')
df.loc[6] = [2004, "Dummy", 2, "", 22]
df.loc[7] = [2022, "Dummy", 2, "", 33]
df = df.sort_values(['year','sites' ], ascending=True ).reset_index(drop=True)
index | year | countries | sites | year_lbl | sub_total |
---|---|---|---|---|---|
0 | 2004 | Dummy | 2 | 22 | |
1 | 2004 | Denmark | 4 | ’04 | 22 |
2 | 2004 | Norway | 5 | ’04 | 22 |
3 | 2004 | Sweden | 13 | ’04 | 22 |
4 | 2022 | Dummy | 2 | 33 | |
5 | 2022 | Norway | 8 | ’22 | 33 |
6 | 2022 | Denmark | 10 | ’22 | 33 |
7 | 2022 | Sweden | 15 | ’22 | 33 |
Create the heritage symbol
icon_path, attributes = svg2paths('flags/Unesco_World_Heritage_logo_notext_transparent.svg')
#matplotlib path object of the icon
icon_marker = parse_path(attributes[0]['d'])
icon_marker.vertices -= icon_marker.vertices.mean(axis=0)
icon_marker = icon_marker.transformed(mpl.transforms.Affine2D().rotate_deg(180))
icon_marker = icon_marker.transformed(mpl.transforms.Affine2D().scale(-1,1))
Define the variables
sub_totals= df.sub_total.unique()
years= df.year.unique()
colors = [["w"]*1 + ["#2C324F"]*5 + ["#CC5A43"]*4 + ["#5375D4"]*13, ["w"]*1+ ["#2C324F"]*8 + ["#CC5A43"]*10 + ["#5375D4"]*15]
#variables for the bar axis
yposition = [0.31,0.215]
height = [0.4,0.6]
radius_end = [.7,.5]
Plot the chart
fig, ax = plt.subplots(figsize=(6, 6))
fig.tight_layout(pad=3.0)
for color, re, sub_total,ypos,h in zip( colors, radius_end,sub_totals,yposition, height):
ax_pie = fig.add_axes([0.22,ypos,0.6,h], polar=True)
angles = np.arange(0,2*np.pi,2*np.pi/sub_total)
ax_pie.plot([angles, angles],[0,re],lw=4,zorder = 0 )
ax_pie.set_rorigin(-2)
ax_pie.set_theta_zero_location("N")
ax_pie.set_theta_direction(-1)
ax_pie.set_axis_off()
for i, j in enumerate(ax_pie.lines):
j.set_color(color[i])
#add the wedges
ax_pie.axvline( -0.12, -1.75, 1.25, color="#D3D9DB", lw=1,clip_on= False )
ax_pie.axvline( 0.12, -1.75, 1.25, color="#D3D9DB", lw=1,clip_on= False )
ax_pie.axvline( 1.62, -1.9, 1.1, color="#D3D9DB", lw=1,clip_on= False )
ax_pie.axvline( 2.72, -1.75, -0.3, color="#D3D9DB", lw=1,clip_on= False )
ax_pie.axvline( 3.53, -0.25, 1.2, color="#D3D9DB", lw=1,clip_on= False )
#add the circles
outer_circle = plt.Circle((0, 0), ec= "#D3D9DB",color= "w",radius=0.043 )
ax.add_artist(outer_circle)
mid_circle = plt.Circle((0, 0), ec= "#D3D9DB",color= "w",radius=0.03 )
ax.add_artist(mid_circle)
inner_circle = plt.Circle((0, 0), ec= "#D3D9DB",color= "w",radius=0.017 )
ax.add_artist(inner_circle)
ax.set_axis_off()
#add the heritage symbol
ax.scatter(0,0,s=4000, marker=icon_marker, color = "#D3D9DB")
#add year labels
ax_pie.text(-0.1,-0.6,"'04", size = 10, color = "#848490", zorder = 2)
ax_pie.text(-0.06,0.2,"'22", size = 10, color = "#848490", zorder = 2)
The result:

Reader Interactions