pandas-alive 0.1.3

Animated plotting extension for Pandas with Matplotlib

Pandas-Alive

Animated plotting extension for Pandas with Matplotlib

Pandas-Alive is intended to provide a plotting backend for animated matplotlib charts for Pandas DataFrames, similar to the already existing Visualization feature of Pandas.

With Pandas-Alive, creating stunning, animated visualisations is as easy as calling:

df.plot_animated()

Installation

Install with pip install pandas-alive

Usage

As this package builds upon bar_chart_race, the example data set is sourced from there.

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.

Example Table

To produce the above visualisation:

• Check Requirements first to ensure you have the tooling installed!
• Call plot_animated() on the DataFrame
  • Either specify a file name to write to with df.plot_animated(filename='example.mp4') or use df.plot_animated().get_html5_video to return a HTML5 video
• Done!

import pandas_alive

df = pandas_alive.load_dataset()

df.plot_animated(filename='example-barh-chart.gif')

Currently Supported Chart Types

pandas-alive current supports:

• Horizontal Bar Charts
• Vertical Bar Charts
• Line Charts

Horizontal Bar Charts

import pandas_alive

df = pandas_alive.load_dataset()

df.plot_animated(filename='example-barh-chart.gif')

Vertical Bar Charts

import pandas_alive

df = pandas_alive.load_dataset()

df.plot_animated(filename='example-barv-chart.gif',orientation='v')

Line Charts

With as many lines as data columns in DataFrame.

import pandas_alive

df = pandas_alive.load_dataset()

df.diff().fillna(0).plot_animated(filename='example-line-chart.gif',kind='line')

Multiple Charts

pandas-alive supports multiple animated charts in a single visualisation.

• Create each chart type ensure to disable writing to file with write_to_file=False
• Create a list of all charts to include in animation
• Use animate_multiple_plots with a filename and the list of charts (this will use matplotlib.subplots)
• Done!

import pandas_alive

df = pandas_alive.load_dataset()

animated_line_chart = df.diff().fillna(0).plot_animated(kind='line',write_to_file=False,period_length=200)

animated_bar_chart = df.plot_animated(kind='barh',write_to_file=False,period_length=200)

pandas_alive.animate_multiple_plots('example-bar-and-line-chart.gif',[animated_bar_chart,animated_line_chart]

Inspiration

The inspiration for this project comes from:

• bar_chart_race by Ted Petrou
• Pandas-Bokeh by Patrik Hlobil

Requirements

If you get an error such as TypeError: 'MovieWriterRegistry' object is not an iterator, this signals there isn't a writer library installed on your machine.

This package utilises the matplotlib.animation function, thus requiring a writer library.

Ensure to have one of the supported tooling software installed prior to use!

• ffmpeg
• ImageMagick
• Pillow
• See more at https://matplotlib.org/3.2.1/api/animation_api.html#writer-classes

Contributing

Pull requests are welcome! Please help to cover more and more chart types!