category: "london"

title: "pandas visualisation"

level: "All"

time: "18:00"

rsvp_link: https://www.meetup.com/Python-Sprints/events/261730665/

project:

sponsor: jpmorgan

Plotting in `pandas` is very easy, mainly by using `Series.plot()` and `DataFrame.plot()` methods.

There is a plotting subsystem in `pandas` based in `matplotlib` that implement different types of

plots (e.g. lines, bars, boxplots, kde...).

In the last months, several new projects have been create to address new use cases for visualising

in `pandas`. For example, to generate interactive plots. Some of these projects are:

- https://hvplot.pyviz.org

- https://github.com/PatrikHlobil/Pandas-Bokeh

- https://github.com/altair-viz/pdvega/

Those libraries have been monkey patching `pandas` to be able to plot easily, so plotting can be

done by using `DataFrame.hvplot()`, `DataFrame.plot_bokeh()`...

But a better design would be to decouple the existing plotting code in pandas into an extension

registered with the `pandas` extension capabilities, and be able to select with an option with

plotting backend the user wants to use. The resulting code would be:

pandas.set_option('plotting.backend', 'hvplot')

df.plot()

With this architecture, there are several advantages:

- Developing new plotting backends for pandas becomes much simpler

- Plotting backends share a common API

- Users of pandas don't need to learn a new syntax for each plugin

- Migrating existing code becomes trivial, by just adding a single line of code setting the option for the backend

- Internal pandas code becomes cleaner, with the plotting code fully decoupled from the rest

Work on this is already going on, with a first PR that decoupled the current plotting code:

In this sprint we will continue the work, by working on different tasks:

- Adding the option to select the backend

- Defining and documenting the pandas plotting API

- Porting existing libraries to the new plotting API

- Document current pandas functionality

As usual, we will give priority to join the sprint to the next people:

- Experienced open source contributors

- People from underrepresented minorities in our sprints

Agenda

- 6pm: Food and networking

- 6:30pm: Presentation of the project and the sponsor

- 6:45pm: Coding

- 9pm: Retrospective presentations

The day of the sprint

- Bring your own laptop if you can

- Join the [Gitter channel](https://gitter.im/py-sprints/pandas-bokeh) of the sprint