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23 of 100: Stacked bar chart on a map 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.

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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: The black box rounding the grand totals is not correct and the text legend needs to be on top of the lines.

This is the original viz that we are trying to recreate in matplotlib:

Import the packages

We will need the following packages:

import geopandas as gpd
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D

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.

color_dict = {2022: "#5375D4", 2004: "#CC5A43", }

xy_ticklabel_color,color_map ='#101628','#D3D3D3'

data = {
    "year": [2004, 2022, 2004, 2022, 2004, 2022],
    "countries" : ["Sweden", "Sweden", "Denmark", "Denmark", "Norway", "Norway"],
    "sites": [13,15,4,10,5,8]
}

df= pd.DataFrame(data)
indexyearcountriessites
02004Sweden13
12022Sweden15
22004Denmark4
32022Denmark10
42004Norway5
52022Norway8

We need to create the subtotals for each year, the difference between sites by year, the country codes and then sort the data.

df['diff']=df.groupby('countries')['sites'].diff().fillna(df.sites).astype(int)

df['sub_total'] = df.groupby('countries')['diff'].transform('sum')
df = df.sort_values([ 'year', 'sub_total'], ascending=True ).reset_index(drop=True)
df['ctry_code'] = df.countries.astype(str).str[:2].astype(str).str.upper()
df['color']= df.year.map(color_dict)
indexyearcountriessitesdiffsub_totalctry_codecolor
02004Norway558NO#CC5A43
12004Denmark4410DE#CC5A43
22004Sweden131315SW#CC5A43
32022Norway838NO#5375D4
42022Denmark10610DE#5375D4
52022Sweden15215SW#5375D4

Load map data

#load the map
map_df = gpd.read_file("https://raw.githubusercontent.com/eurostat/Nuts2json/master/pub/v2/2021/3035/20M/0.json")

# add a country column
map_df['country'] = map_df['id'].astype(str).str[:2]

#filter by nordic countries
map_df = map_df[map_df.country.isin(['NO','SE', 'DK']) ]
indexidnageometrycountry
11DKDanmarkMULTIPOLYGON (((4649929.995 3564341.094, 46459…DK
21SESverigeMULTIPOLYGON (((4968534.919 4802763.317, 49724…SE
26NONorgeMULTIPOLYGON (((5002725.191 5305903.887, 49921…NO

Define the variables

lat= [0.42,0.48,0.54]
lon =[0.24,0.14,0.28]
x = len(df.year.unique())
countries = df.countries.unique()
totals = df.sub_total.unique()
codes = df.ctry_code.unique()
colors = df.color.unique()

Plot the chart

fig = plt.figure(figsize=(15,10))
ax_map = fig.add_axes([0, 0, 1, 1])
map_df.plot(color='#D3D3D3',ax=ax_map)
ax_map.set_axis_off()



for lt,ln,country, total, code in zip(lat,lon,countries, totals, codes):
    print(lat, lon)
    ax_bar = fig.add_axes([lt ,ln , 0.03, 0.2])  
    data = df[df["countries"] == country]
    years= data.year  

    #add grand totals
    ax_bar.text(0, total+1, total, ha= "center", color = "white",
                bbox=dict(facecolor='black', edgecolor='black', boxstyle='round,pad=0.3'))
    #add x label
    ax_bar.set_xlabel(code, color =xy_ticklabel_color, size =14, weight= "bold")
    bottom = np.zeros(x)
    for year, color  in zip(years, colors):
        y = data[data.year == year].sort_values("sub_total", ascending = True)["diff"].values   
        ax_bar.bar(range(1), y, bottom = bottom, width= 0.2, color=color)
        bottom +=y
        ax_bar.set_ylim(0,15)
        ax_bar.set_yticklabels([])
        ax_bar.set_xticklabels([])
        ax_bar.grid(False)
        ax_bar.set_frame_on(False)
        ax_bar.tick_params(axis='both', which='both',length = 0)

        
    offset_text = 0.3
    for bar,c in zip(ax_bar.patches,  color):
        ax_bar.text(
            bar.get_x() + bar.get_width() / 2,            # Put the text in the middle of each bar. get_x returns the start, so we add half the width to get to the middle.
            bar.get_height()/2 + bar.get_y(),              # Vertically, add the height of the bar to the start of the bar,  along with the offset.   
            round(bar.get_height()),                          # This is actual value we'll show.
            ha='center', color='w',  size=8 )
        
#################
# add legend
##################

text_legends = ["Before 2004", "After 2004", "Total"]
colors = ["#5475D6","r", "black"]
lines = [Line2D([0], [0], color=c, linestyle='-', ) for c in colors]
labels  = [f'{text_legend}' for  text_legend in text_legends]
plt.figlegend( lines,labels,   
                  labelcolor=xy_ticklabel_color,
            bbox_to_anchor=(0.8, -0.05), loc="lower center",
                ncols = 3,frameon=False, fontsize= 12)

The result:

23 of 100: Stacked bar chart on a map in matplotlib
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