Mastering Matplotlib: Part 5

EDA with Stacked and Unstacked Histograms

Lawrence Alaso Krukrubo
DataSeries

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Hello and welcome to Part Five of this mini-series on data visualization with the most popular Python visualization library called matplotlib.

The goal is to take you from beginner to expert in data visualization via matplotlib,without unnecessary details that you don’t need to know.

They say a picture is worth a thousand words, but when it comes to Data, a chart is worth a thousand lines…

This is a beginner-friendly roadmap that is designed for everyone interested in data visualization. The only requirement is basic programming experience with Python and some interaction with pandas or numpy.

In part one, we explored the matplotlib architecture, created plots with the three layers and 26 different plot styles. In part two we explored the matplotlib-pandas synergy via the plot() function. In part three we went deeper into intermediate pandas for data visualization. In part four we went deep into the most common plots:- Line and Area plots. We explored stacked and unstacked Area plots and played with colour-maps and the 148 colours of matplotlib.

Part 1. Part 2. Part 3.Part 4.

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Lawrence Alaso Krukrubo
DataSeries

Fair and Explainable AI | Data Science | Machine Learning | Deep Learning| Writer@towardsAI| AI-Nanodegree