Easy methods to use the total capabilities of Matplotlib to inform a extra compelling story
Telling a compelling story with information will get method simpler when the charts supporting this very story are clear, self-explanatory and visually pleasing to the viewers.
In lots of circumstances, substance and kind are simply equally necessary.Nice information poorly introduced is not going to catch the eye it deserves whereas poor information introduced in a slick method will simply be discredited.
I hope this can 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 straightforward to plot information with off-the-shelf capabilities however the high quality tuning steps take extra effort.I spent fairly a while researching finest practices to construct compelling charts with Matplotlib, so that you don’t must.
On this article I give attention to stacked space charts and clarify how I sewed collectively the bits of information I discovered right here and there to go from this…
… to that:
All photographs, except in any other case famous, are by the writer.
As an instance the methodology, I used a public dataset containing particulars about how the US are producing their electrical energy and which might be discovered right here — https://ourworldindata.org/electricity-mix.
On prime of being a terrific dataset as an example stacked space charts, I additionally discovered it very insightful.
Supply: Ember — Yearly Electrical energy Knowledge (2023); Ember — European Electrical energy Assessment (2022); Power Institute — Statistical Assessment of World Power (2023)License URL: https://creativecommons.org/licenses/by/4.0/License Sort: CC BY-4.0