Python- Matplotlib visualization (7) - multi-faceted custom statistical graph drawing
foreword
In the series of blog posts, we have learned how to customize the color and style of the drawing to make the drawing more exquisite and meet the aesthetic requirements. Matplotlib can be used to draw complex and exquisite statistical graphs, and the usage of annotations is also explained to make the statistical graphs clear and concise. But these are just the tip of the iceberg of the powerful capabilities of the Matplotlib plotting package.
When we use a drawing package, we need it to cover extremely diverse content: on the one hand, we want to be able to create any type of graphics with a minimum of code and skills; on the other hand, we also want to be able to flexibly customize all graphics aspect. These are two diametrically opposed goals, between which Matplotlib provides an excellent balance. next