Book Image

Python Data Visualization with Matplotlib 2.x [Video]

By : Allen Yu, Claire Chung, Aldrin Yim
Book Image

Python Data Visualization with Matplotlib 2.x [Video]

By: Allen Yu, Claire Chung, Aldrin Yim

Overview of this book

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.By the end of this video, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This video will help you prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents (8 chapters)
Chapter 7
A Practical Guide to Scientific Plotting
Content Locked
Section 3
Visualizing Statistical Data More Intuitively
Let’s revisit more variants of bar charts–stacked bar chart and layered histograms, which are commonly used in scientific publications to summarize and describe data and make it more interesting. - Make a stacked bar chart and convert it into a stacked percentage bar plot - Use pandas to create layered histograms - Replace bar charts with mean-and-error plots