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Matplotlib 2.x By Example

You're reading from  Matplotlib 2.x By Example

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781788295260
Pages 334 pages
Edition 1st Edition
Languages
Authors (3):
Allen Yu Allen Yu
Profile icon Allen Yu
Claire Chung Claire Chung
Profile icon Claire Chung
Aldrin Yim Aldrin Yim
Profile icon Aldrin Yim
View More author details

Visualizing statistical data more intuitively


Science is based on statistics. We propose hypotheses from observations. We test and reject the null hypothesis when its probability, the value, is lower than a threshold, so that observed phenomena are not likely arisen from mere chance; that is, our proposed hypothesis is supported.

There are some specific plot types that can ease the visualization of descriptive and inferential statistics. We will first revisit more variants of bar charts–stacked bar chart and layered histograms, which are commonly used in scientific publications to summarize and describe data.

Stacked bar chart and layered histogram

In Chapter 4, Visualizing Online Data, we showed the procedures to create bar charts using Matplotlib and Seaborn. It is little known that the pandas package can be used for visualization, as most people only concentrate on its data analysis capabilities. Since the pandas visualization module was built on top of Matplotlib, we can exploit the powerful...

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