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5 Steps to Lovely Stacked Space Charts in Python

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The best way to use the total capabilities of Matplotlib to inform a extra compelling story

Electrical energy Manufacturing by Supply within the US — Picture by Writer

Telling a compelling story with knowledge will get manner simpler when the charts supporting this very story are clear, self-explanatory and visually pleasing to the viewers.

In lots of instances, substance and type are simply equally necessary.
Nice knowledge poorly offered won’t catch the eye it deserves whereas poor knowledge offered in a slick manner will simply be discredited.

I hope this may resonate with many Knowledge Analysts, or anybody who needed to current a chart in entrance an viewers as soon as of their lifetime.

Matplotlib makes it fast and simple to plot knowledge with off-the-shelf capabilities however the superb tuning steps take extra effort.
I spent fairly a while researching greatest practices to construct compelling charts with Matplotlib, so that you don’t should.

On this article I give attention to stacked space charts and clarify how I sewed collectively the bits of data I discovered right here and there to go from this…

… to that:

All photos, except in any other case famous, are by the creator.

For example the methodology, I used a public dataset containing particulars about how the US are producing their electrical energy and which will be discovered right here — https://ourworldindata.org/electricity-mix.

On prime of being an incredible dataset as an example stacked space charts, I additionally discovered it very insightful.

Supply: Ember — Yearly Electrical energy Knowledge (2023); Ember — European Electrical energy Overview (2022); Vitality Institute — Statistical Overview of World Vitality (2023)
License URL:
https://creativecommons.org/licenses/by/4.0/
License Sort: CC BY-4.0

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