File:Pyramide des âges, Belgique. 2001-2013.svg

#!/usr/bin/env python3
# coding: utf-8
"""
Load population data from a json file and outputs a pyramid
of ages. 
Source: https://visuals.economie.fgov.be/visuals/data/population_age_gender.json
"""

import json
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter 
with open('population_age_gender.json') as data_file:
    json_data = json.load(data_file)

NIS = '01000'       # NIS code for country, see https://statbel.fgov.be/nl/open-data/refnis-code
w_color = '#ff9999' # color of bars for women
m_color = '#9999ff' # and for men

# build a dictionary: integer in [4,9,14..100] -> string as "0-4","5-9"..."100+"    
classes = dict()
for v in json_data['dimensions']['C']['values']:
    for w in v.items():
        classes[int(w[0])] = w[1]['FR']
# then a sorted list of the labels of age-classes as strings 
labels = [classes[k] for k in sorted(classes.keys())]

def getdata(json_data, NIS='01000', year = 2013):
    """
    returns a 21x2 array of integers representing the number of persons in
    each age-class, with men in 1rst column and women in 2d.
    """
    values = dict()
    for f in json_data['facts']:
        if f['g'] == NIS and f['y'] == year:
            if f['C'] in values:
                values[f['C']][f['s']] = f['M']
            else:
                values[f['C']] = {f['s']:f['M']}

    data = np.empty((len(values),3),dtype='int')
    i = 0
    for k in sorted(values.keys()):
        data[i] = [k,values[k]['M'],values[k]['F']]
        i += 1
    return data[:,1:3]

# function to assign positive values in X-axis
# https://matplotlib.org/devdocs/gallery/ticks_and_spines/tick_labels_from_values.html
def format_fn(tick_val, tick_pos):
    return int(abs(tick_val))

d_2001 = getdata(json_data,NIS,2001)
d_2013 = getdata(json_data,NIS,2013)

print('total hommes 2001:', np.sum(d_2001[:,0]))
print('total femmes 2001:', np.sum(d_2001[:,1]))
print('total 2001:', np.sum(d_2001[:,0:2])) 
print('total hommes 2013:', np.sum(d_2013[:,0]))
print('total femmes 2013:', np.sum(d_2013[:,1]))
print('total 2013:', np.sum(d_2013[:,0:2])) 

max_x = np.concatenate((d_2001,d_2013)).max() # used to get a symmetrical plot

fig, ax = plt.subplots(figsize=(10,6))

Xm_2013 = d_2013[:,0]  
Xw_2013 = d_2013[:,1]
Y = np.array(range(d_2013.shape[0]))

ax.barh(Y, -Xm_2013, color=m_color, align='center', label='Hommes 2013')
ax.barh(Y,  Xw_2013, color=w_color, align='center', label='Femmes 2013')

Xm_2001 = d_2001[:,0]
Xw_2001 = d_2001[:,1]

ax.set_xlim(-max_x*1.1,max_x*1.1) 
ax.step(-Xm_2001, Y-0.5, where='pre', color='#4444ff', label='Hommes 2001')
ax.step( Xw_2001, Y-0.5, where='pre', color='#ff4444', label='Femmes 2001')

ax.set_yticks(Y)
ax.set_yticklabels(labels)
ax.xaxis.set_major_formatter(FuncFormatter(format_fn))
ax.xaxis.set_major_locator(plt.MultipleLocator(100000))
ax.xaxis.set_minor_locator(plt.MultipleLocator(10000))
ax.grid(which='major', axis='x', linewidth=0.75, linestyle='-', color='0.75')
ax.grid(which='minor', axis='x', linewidth=0.25, linestyle='-', color='0.75')
ax.grid(axis='y', linewidth=0.25, linestyle='-', color='0.75')
plt.legend()
plt.title('Pyramide des âges, Belgique - 2001-2013')
plt.xlabel('Effectifs en unités')
plt.show()