Animating China’s 500+ Million Population Cities with Python & Geopandas

Excluding Hong Kong, Macau and Taiwan, China has 337 prefecture‑level cities. By considering population size and economic development, these cities are grouped into first‑tier, new‑first‑tier, second‑tier, third‑tier, fourth‑tier and fifth‑tier categories.

According to the latest census data, 88 of these cities have populations exceeding five million. The following Python script dynamically visualizes these megacities on a map, drawing provincial boundaries, the nine‑dash line, and animated bubbles whose size reflects population.

Key steps include loading GeoJSON files for provinces, the South China Sea line, and city points, converting coordinates, and preparing a DataFrame with x, y, and population values. The bubble_map_dance function creates a Matplotlib figure, draws base layers, plots scatter points with a color map, annotates selected cities, and animates the growth of bubbles across frames.

import numpy as
import pandas as
import geopandas as gpd
import shapely
from shapely import geometry as geo
from shapely import wkt
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import contextily as ctx
import imageio
import os
from PIL import Image

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
plt.rcParams['animation.writer'] = 'html'
plt.rcParams['animation.embed_limit'] = 100

# ... (full code as provided in the source) ...

html_file = "中国超500万人口城市.html"
bubble_map_dance(df, filename=html_file)

gif_file = html_file.replace('.html', '.gif')
html_to_gif(html_file, gif_file, duration=0.5)

The script generates an interactive HTML animation and converts it to a GIF, enabling a clear visual comparison of the most populous Chinese cities.