pandas-alive 0.1.11

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

covid_df = pandas_alive.load_dataset()

covid_df.plot_animated(filename='examples/example-barh-chart.gif')

Currently Supported Chart Types

pandas_alive current supports:

• Horizontal Bar Charts
• Vertical Bar Charts
• Line Charts
• Scatter Charts

Horizontal Bar Charts

import pandas_alive

covid_df = pandas_alive.load_dataset()

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

import pandas as pd
import pandas_alive

elec_df = pd.read_csv("data/Aus_Elec_Gen_1980_2018.csv",index_col=0,parse_dates=[0],thousands=',')

elec_df.fillna(0).plot_animated('examples/example-electricity-generated-australia.gif',period_fmt="%Y",title='Australian Electricity Generation Sources 1980-2018')

Vertical Bar Charts

import pandas_alive

covid_df = pandas_alive.load_dataset()

covid_df.plot_animated(filename='examples/example-barv-chart.gif',orientation='v')

Line Charts

With as many lines as data columns in the DataFrame.

import pandas_alive

covid_df = pandas_alive.load_dataset()

covid_df.diff().fillna(0).plot_animated(filename='examples/example-line-chart.gif',kind='line',period_label={'x':0.1,'y':0.9})

Scatter Charts

import pandas as pd
import pandas_alive

max_temp_df = pd.read_csv(
    "data/Newcastle_Australia_Max_Temps.csv",
    parse_dates={"Timestamp": ["Year", "Month", "Day"]},
)
min_temp_df = pd.read_csv(
    "data/Newcastle_Australia_Min_Temps.csv",
    parse_dates={"Timestamp": ["Year", "Month", "Day"]},
)

merged_temp_df = pd.merge_asof(max_temp_df, min_temp_df, on="Timestamp")

merged_temp_df.index = pd.to_datetime(merged_temp_df["Timestamp"].dt.strftime('%Y/%m/%d'))

keep_columns = ["Minimum temperature (Degree C)", "Maximum temperature (Degree C)"]

merged_temp_df[keep_columns].resample("Y").mean().plot_animated(filename='examples/example-scatter-chart.gif',kind="scatter",title='Max & Min Temperature Newcastle, Australia')

Multiple Charts

pandas_alive supports multiple animated charts in a single visualisation.

• 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

covid_df = pandas_alive.load_dataset()

animated_line_chart = covid_df.diff().fillna(0).plot_animated(kind='line',period_label=False)

animated_bar_chart = covid_df.plot_animated(kind='barh',n_visible=10)

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

import pandas_alive

urban_df = pandas_alive.load_dataset("urban_pop")

animated_line_chart = (
    urban_df.sum(axis=1)
    .pct_change()
    .dropna()
    .mul(100)
    .plot_animated(kind="line", title="Total % Change in Population",period_label=False)
)

animated_bar_chart = urban_df.plot_animated(kind='barh',n_visible=10,title='Top 10 Populous Countries',period_fmt="%Y")

pandas_alive.animate_multiple_plots('examples/example-bar-and-line-urban-chart.gif',[animated_bar_chart,animated_line_chart],title='Urban Population 1977 - 2018',adjust_subplot_top=0.85)

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

Documentation

Documentation is provided at https://jackmckew.github.io/pandas_alive/

Contributing

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