by Benjamin Keller | Released October 2017 | ISBN: 9781787281998

Understand the basic fundamentals of plotting and data visualization using Matplotlib About This VideoCrisp and clear content that puts the theory into practice and delves into the core of MatplotlibLeverage the various aspects of data visualization and plotsExplore Matplotlib further using Pandas and Jupyter In DetailMatplotlib 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. Show and hide more

1. Chapter 1 : Diving into Matplotlib
   • The Course Overview 00:02:21
   • Understanding Data, Dimensionality, and Why We Plot 00:08:23
   • Setting Up Your Environment 00:07:11
   • Beginning with the Most Basic Plots 00:09:39
2. Chapter 2 : Basic Plotting Functions
   • Differentiating Line and Scatter Plots 00:14:07
   • Constructing Bar Plots and Histograms 00:15:39
   • Exploring Images and Contours 00:09:18
   • Working on Plots with Uncertainties 00:03:54
   • Looking at Other Useful Plot Types 00:06:16
   • Making Multiple Panel Plots 00:07:39
   • Using Color Bars and Legends 00:06:10
3. Chapter 3 : Axes and Figures – Plot Scaffolding
   • Workingwith the Components of a Matplotlib Plot 00:03:20
   • Figure and Axes – How Do They Work? 00:07:27
   • Working with Transformations 00:07:26
   • Controlling Axes and Ticks 00:09:37
   • Ticker Formatting 00:08:52
   • Working on Back Ends 00:06:57
4. Chapter 4 : Jupyter and Pandas – Matplotlib’s Best Friends
   • The Jupyter Notebook 00:09:19
   • Using Pandas to Manipulate Tabular Data 00:12:01
   • Slicing and Dicing Pandas Data 00:10:56
   • Pandas Built-in Plotting 00:09:37
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