77 of 100: Tabular 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!
This is the original viz that we are trying to recreate in matplotlib:

Import the packages
We will need the following packages:
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
from matplotlib import pyplot as plt
import pandas as pd
Generate the data
We are hardcoding the data for now, so we jump straight to the code.
Plot the chart
fig, ax = plt.subplots(figsize=(8,6))
rows = 4
cols = 6
ylabel = ["Biggest % change","Biggest change","Most in 2022","Most in 2004"]
colors = [['w','r','w','r','#2B314D','w'],['w','r','w','r','#2B314D','w'],['w','r','#5375D4','w','w','#5375D4'],['#2B314D','w','#5375D4','w','w','#5375D4']]
positions = [ 0.5, 1.5, 2.5, 3.5,4.5,5.5]
img = [plt.imread("flags/no-sq.png"),plt.imread("flags/de-sq.png"), plt.imread("flags/sw-sq.png"),plt.imread("flags/de-sq.png"),plt.imread("flags/no-sq.png"),plt.imread("flags/sw-sq.png")]
# create a coordinate system based on the number of rows/columns
# adding a bit of padding on bottom (-1), top (1), right (0.5)
ax.set_ylim(-1, rows + 1)
ax.set_xlim(0, cols + .5)
for pos, im in zip(positions,img):
image_box = OffsetImage(im, zoom = 0.04) #container for the image
ab = AnnotationBbox(image_box, (pos,4.6 ), frameon = False)
ax.add_artist(ab)
# Add table's main text
for i, color in zip(range(rows), colors):
#print(color)
newaxes = []
for c, (j, column) , in zip( color,enumerate(range(cols))):
#print(j[::2])
ax.scatter( positions[j], i,s = 100, c= c)
# Add dividing lines
for vline in range(0, cols+2 ,2):
ax.axvline(x = vline, ymin = 0,ymax =1 , color = 'lightgrey')
for dotted_line in range(1, cols ,2):
ax.axvline(x = dotted_line, ymin = 0,ymax =0.85 , ls = "dotted" , color = 'lightgrey')
ax.annotate("VS.", xy =(dotted_line,4.5 ), ha = "center" )
ax.tick_params(axis='both', which='both',length=0, color = 'lightgrey',pad = 20)
ax.spines[['top', 'left','bottom', 'right']].set_visible(False)
ax.yaxis.set_ticks(range(rows), labels =ylabel)
ax.xaxis.set_ticks([])
The result:

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