Python Data Visualization with Matplotlib 2.x: Design effective charts and info graphics with Matplotlib 2.x

Allen Yu

Aldrin Yim

Claire Chung

£112.99

Video Oct 2017 4hrs 12mins 1st Edition

Allen Yu

Aldrin Yim

Claire Chung

£112.99

Video Oct 2017 4hrs 12mins 1st Edition

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Key benefits

Create and customize appealing and live graphs, by adding style, colors, and fonts.
Learn to represent data in the right way to engage readers
Explore the power of Python packages to design excellent graphs
Create timestamp-based graphs in various formats, including 2D and 3D plots, histograms, bar charts, and scatter plots

Description

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.

Who is this book for?

This course will help anyone interested in data visualization get insights from big data with Python and Matplotlib 2.x. With this course you will be able to extend your knowledge and learn how to use Python code in order to visualize your data with Matplotlib. A basic knowledge of Python is expected.

What you will learn

Master with the latest features in Matplotlib 2.x
Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots, and many more.
Make clear and appealing figures for scientific publications.
Create interactive charts and animations.
Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.
Design intuitive infographics for effective storytelling.

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