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3 Awesome Visualization Techniques for every dataset

And Learn a little about Football while at it

Rahul Agarwal
Towards Data Science

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Visualizations are awesome. However, a good visualization is annoyingly hard to make.

Moreover, it takes time and effort when it comes to present these visualizations to a bigger audience.

We all know how to make Bar-Plots, Scatter Plots, and Histograms, yet we don’t pay much attention to beautify them.

This hurts us — our credibility with peers and managers. You won’t feel it now, but it happens.

Also, I find it essential to reuse my code. Every time I visit a new dataset do I need to start again? Some reusable ideas of graphs that can help us to find information about the data FAST.

In this post, I am also going to talk about 3 cool visual tools:

  • Categorical Correlation with Graphs,
  • Pairplots,
  • Swarmplots and Graph Annotations using Seaborn.

In short, this post is about useful and presentable graphs.

I will be using data from FIFA 19 complete player dataset on kaggle — Detailed attributes for every player registered in the latest edition of FIFA 19 database.

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