Animated bubble chart


This blogpost explains how to build an animated bubble chart using Python 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 and I've stored a copy on the gallery 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/holtzy/The-Python-Graph-Gallery/master/static/data/gapminderData.csv')

# Check the first 2 rows
data.head(2)
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

💭 Bubble chart

Let's build a bubble chart for the first year of the dataset (1952). If you're interested in how to make bubble charts with python, the gallery has a dedicated section for it.

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(0,50000)
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(0,100000)
    plt.xlim(30, 90)
    
    # Save it & close the figure
    filename='/Users/yan.holtz/Desktop/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 specified folder (/Users/yan.holtz/Desktop/ for me). 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

If you don't have brew installed, visit the image magick homepage for explanations.

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

# 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 title

Colors

Interactivity

Animation with python

Animation

Cheat sheets

Caveats

3D

Contact & Edit

👋 This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message onTwitter, or send an email pasting yan.holtz.data with gmail.com.

This page is just a jupyter notebook, you can edit it here. Please help me making this website better 🙏!

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Scatterplot

Heatmap

Correlogram

Bubble

Connected Scatter

2D Density

Barplot

Spider / Radar

Wordcloud

Parallel

Lollipop

Circular Barplot

Treemap

Venn Diagram

Donut

Pie Chart

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Circular Packing

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Stacked Area

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Map

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Hexbin

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Edge Bundling

Colors

Interactivity

Animation with python

Animation

Cheat sheets

Caveats

3D

Animation with python