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A population pyramid is a graph that shows the age and gender distribution of a given population. It’s useful for understanding the composition of a population and the trend in population growth.

This tutorial explains how to create the following population pyramid in Python:

Population Pyramid in Python

Suppose we have the following dataset that displays the total population of males and females by age group for a given country:

#import libraries 
import numpy as np
import pandas as pd 
import matplotlib.pyplot as plt

#create dataframe
df = pd.DataFrame({'Age': ['0-9','10-19','20-29','30-39','40-49','50-59','60-69','70-79','80-89','90+'], 
                    'Male': [9000, 14000, 22000, 26000, 34000, 32000, 29000, 22000, 14000, 3000], 
                    'Female': [8000, 15000, 19000, 28000, 35000, 34000, 28000, 24000, 17000, 5000]})
#view dataframe 
df

    Age  Male Female
0   0-9  9000   8000
1 10-19 14000  15000
2 20-29 22000  19000
3 30-39 26000  28000
4 40-49 34000  35000
5 50-59 32000  34000
6 60-69 29000  28000
7 70-79 22000  24000
8 80-89 14000  17000
9   90+  3000   5000

We can use the following code to create a population pyramid for the data:

#define x and y limits
y = range(0, len(df))
x_male = df['Male']
x_female = df['Female']

#define plot parameters
fig, axes = plt.subplots(ncols=2, sharey=True, figsize=(9, 6))

#specify background color and plot title
fig.patch.set_facecolor('xkcd:light grey')
plt.figtext(.5,.9,"Population Pyramid ", fontsize=15, ha='center')
    
#define male and female bars
axes[0].barh(y, x_male, align='center', color='royalblue')
axes[0].set(title='Males')
axes[1].barh(y, x_female, align='center', color='lightpink')
axes[1].set(title='Females')

#adjust grid parameters and specify labels for y-axis
axes[1].grid()
axes[0].set(yticks=y, yticklabels=df['Age'])
axes[0].invert_xaxis()
axes[0].grid()

#display plot
plt.show()

From the plot we can see that the distribution of males and females is fairly symmetrical, with most of the population falling in the middle-age brackets. By simply looking at this one plot, we can get a decent idea about the demographics of this particular country.

Note that you can adjust the colors of the plot background and the individual bars by specifying colors from the .

For example, we could specify ‘hotpink’ and ‘dodgerblue’ to be used with a ‘beige’ background:

fig.patch.set_facecolor('xkcd:beige')
    
axes[0].barh(y, x_male, align='center', color='dodgerblue')

axes[1].barh(y, x_female, align='center', color='hotpink')

plt.show()

Feel free to modify the color scheme based on what you think looks best.