animated-bubble-chart

Animated Bubble Chart

Animated Bubble Chart using Python, Matplotlib, and Image Magick. Matplotlib is used to produce several images, Image Magick to concatenate them as a gif.

📍 Dataset

This example is based on the famous gapminder dataset. It provides the average life expectancy, gdp per capita and population size for more than 100 countries. It is available online here or github repo

Let's load it in python and have a look to the 3 first rows.

## Libraries
import pandas as pd

## read the data (on the web)
data = pd.read_csv('https://raw.githubusercontent.com/nnthanh101/Machine-Learning/main/analytics/data/gapminderData.csv')

## Check the first 3 rows
data.head(3)

	country	year	pop	continent	lifeExp	gdpPercap
0	Afghanistan	1952	8425333.0	Asia	28.801	779.445314
1	Afghanistan	1957	9240934.0	Asia	30.332	820.853030
2	Afghanistan	1962	10267083.0	Asia	31.997	853.100710

💭 Bubble chart

Let's build a bubble chart for the first year of the dataset (1952). Let's build one using the scatter() function of matplotlib:

# import matplotlib
import matplotlib.pyplot as plt

# And I need to transform my categorical column (continent) in a numerical value group1->1, group2->2...
data['continent']=pd.Categorical(data['continent'])

# Set the figure size
plt.figure(figsize=(10, 10))

# Subset of the data for year 1952
data1952 = data[ data.year == 1952 ]

# Scatterplot
plt.scatter(
    x = data1952['lifeExp'], 
    y = data1952['gdpPercap'], 
    s=data1952['pop']/50000, 
    c=data1952['continent'].cat.codes, 
    cmap="Accent", 
    alpha=0.6, 
    edgecolors="white", 
    linewidth=2);
 
# Add titles (main and on axis)
plt.yscale('log')
plt.xlabel("Life Expectancy")
plt.ylabel("GDP per Capita")
plt.title("Year 1952")
plt.ylim(1,50000)
plt.xlim(30, 75);

🎥 Animation

An animation is basically a set of static images visualized one after the other. The strategy here is to build on png file for each year of the dataset, and then concatenated them as a gif.

Let's build a loop that will output one png file per year of the dataset:

# image resolution
dpi=96

# For each year:
for i in data.year.unique():
 
    # Turn interactive plotting off
    plt.ioff()

    # initialize a figure
    fig = plt.figure(figsize=(680/dpi, 480/dpi), dpi=dpi)
    
    # Find the subset of the dataset for the current year
    subsetData = data[ data.year == i ]

    # Build the scatterplot
    plt.scatter(
        x=subsetData['lifeExp'], 
        y=subsetData['gdpPercap'], 
        s=subsetData['pop']/200000 , 
        c=subsetData['continent'].cat.codes, 
        cmap="Accent", alpha=0.6, edgecolors="white", linewidth=2)
    
    # Add titles (main and on axis)
    plt.yscale('log')
    plt.xlabel("Life Expectancy")
    plt.ylabel("GDP per Capita")
    plt.title("Year: "+str(i) )
    plt.ylim(1, 100000)
    plt.xlim(30, 90)
    
    # Save it & close the figure
    filename='animated-bubble-chart/Gapminder_step'+str(i)+'.png'
    plt.savefig(fname=filename, dpi=96)
    plt.gca()
    plt.close(fig)

Now, you should have a set of 12 images in the animated-bubble-chart folder. Image magick is a command line tool that allows to concatenate those images in a gif file.

Install ImageMagick with this line of bash: brew install imagemagick

Once the tool is installed, you can concatenate the 12 images using the following command:

## Invoke imagemagick to terminal (Bash)
# convert -delay 80 Gapminder*.png animated_gapminder.gif

Note: the above line of code is written in bash, not in python. You have to execute it in a terminal, not in your python environment.

And here is the final result

Animated Bubble Chart