/ Data Visualization

Make animated bar chart races with matplotlib

Make animated bar chart races with matplotlib

Bar Chart Race

Make animated bar chart races with matplotlib.

Bar-Chart-Race

Installation

Install with pip install bar_chart_race

Usage

Must begin with a pandas DataFrame containing 'wide' data where:

  • Every row represents a single period of time
  • Each column holds the value for a particular category
  • The index contains the time component (optional)

The data below is an example of properly formatted data. It shows total deaths from COVID-19 for the highest 20 countries by date.

wide_data

Main function - bar_chart_race

There is one main function, bar_chart_race, which we use to recreate the above video. All parameters are shown with their default value except for filename and title.

>>> import bar_chart_race as bcr
>>> df = bcr.load_dataset('covid19')
>>> bcr.bar_chart_race(
    df=df,
    filename='covid19_horiz_desc.mp4',
    orientation='h',
    sort='desc',
    label_bars=True,
    use_index=True,
    steps_per_period=10,
    period_length=500,
    figsize=(6.5, 3.5),
    cmap='dark24',
    title='COVID-19 Deaths by Country',
    bar_label_size=7,
    tick_label_size=7,
    period_label_size=16,
    fig=None)

Save animation to disk or return HTML

Leave the filename parameter as None to return the animation as HTML. You can subsequently embed the animation into a Jupyter Notebook with the following.

In [1]: bcr_html = bcr.bar_chart_race(df=df, filename=None)
In [2]: from IPython.display import HTML
In [3]: HTML(bcr_html)

Use vertical bars and limit to top n_bars

Make bars vertical by setting orientation to 'v'. Use n_bars if you want to limit the number of bars. The bars will transition on and off the graph.

>>> df = bcr.load_dataset('urban_pop')
>>> bcr.bar_chart_race(
    df=df,
    filename='videos/urban_vert_asc.gif',
    orientation='v',
    sort='asc',
    n_bars=8,
    title='Urban Population')

urban_vert_asc

GitHub

Comments