Matplotlib for Python Developers (V): Data Visualization and Plotting for Python Developers

Benjamin Walter Keller

NZ$201.99

Video Oct 2017 2hrs 56mins 1st Edition

Benjamin Walter Keller

NZ$201.99

Video Oct 2017 2hrs 56mins 1st Edition

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Key benefits

Crisp and clear content that puts the theory into practice and delves into the core of Matplotlib
Leverage the various aspects of data visualization and plots
Explore Matplotlib further using Pandas and Jupyter

Description

Matplotlib is a multi-platform data visualization tool built upon the Numpy and Scipy framework. One of matplotlib's most important features is its ability to play well with many operating systems and graphics backends. In this course, we hit the ground running and quickly learn how to make beautiful, illuminating figures with Matplotlib and a handful of other Python tools. We understand data dimensionality and set up an environment by beginning with basic plots. We enter into the exciting world of data visualization and plotting. You'll work with line and scatter plots and construct bar plots and histograms. You'll also explore images, contours, and histograms in depth. Plot scaffolding is a very interesting topic wherein you'll be taken through axes and figures to help you design excellent plots. You'll learn how to control axes and ticks, and change fonts and colors. You'll work on backends and transformations. Then lastly you'll explore the most important companions for Matplotlib, Pandas and Jupyter, used widely for data manipulation, analysis, and visualization. By the end of this course you'll be able to construct effective and beautiful data plots using the Matplotlib library for the Python programming language.

Who is this book for?

If you want to visualize data in truly beautiful plots, this course is for you. A basic knowledge of Python is needed.

What you will learn

Use Matplotlib for data visualization with the Python programming language
Construct different types of plot such as lines and scatters, bar plots, and histograms
Make use of various aspects of data visualization with Matplotlib
Work on transformation and back-ends, and change fonts and colors
Use Pandas and Jupyter to manipulate your tabular data

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