Beginner’s Guide: Python for Analytics | Seaborn

Beginner’s Guide to Using Python with HR Data | Exploration Series

Part Three – Seaborn

In this first tutorial series, I’m exploring the IBM HR Attrition and Performance data set. This is a great data set used to demonstrate the possibilities from using machine learning and other data science techniques.

Now we’ll move on to using Seaborn for our visualizations. The benefit of Seaborn is it continues to abstract the complex, underlying calls to visualize your data – further allowing you to focus on your analysis task and not having to think about how to implement what you want to do. It goes even further and provides built-in functionality that would be incredibly complex to implement without the benefit of Seaborn.

Series Outline

0: basic operations & summary statistics

1: matplotlib

2: pandas visualization

3: seaborn

4: plotly

5: series summary

3: Seaborn

view on github

Credits
Photo: Photo by Randall Ruiz on Unsplash