Hands-on Matplotlib : Learn Plotting and Visualizations with Python 3

Learn the core aspects of NumPy, Matplotlib, and Pandas, and use them to write programs with Python 3. This book focuses heavily on various data visualization techniques and will help you acquire expert-level knowledge of working with Matplotlib, a MATLAB-style plotting library for Python programming language that provides an object-oriented API for embedding plots into applications. You'll begin with an introduction to Python 3 and the scientific Python ecosystem. Next, you'll explore NumPy and ndarray data structures, creation routines, and data visualization. You'll examine useful concepts related to style sheets, legends, and layouts, followed by line, bar, and scatter plots. Chapters then cover recipes of histograms, contours, streamplots, and heatmaps, and how to visualize images and audio with pie and polar charts. Moving forward, you'll learn how to visualize with pcolor, pcolormesh, and colorbar, and how to visualize in 3D in Matplotlib, create simple animations, and embed Matplotlib with different frameworks. The concluding chapters cover how to visualize data with Pandas and Matplotlib, Seaborn, and how to work with the real-life data and visualize it. After reading Hands-on Matplotlib you'll be proficient with Matplotlib and able to comfortably work with ndarrays in NumPy and data frames in Pandas. What You'll Learn Understand Data Visualization and Python using Matplotlib Review the fundamental data structures in NumPy and Pandas Work with 3D plotting, visualizations, and animations Visualize images and audio data Who This Book Is For Data scientists, machine learning engineers and software professionals with basic programming skills. -- Provided by publisher Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: Introduction to Python 3 Introducing the Python 3 Programming Language History of the Python Programming Language Python Enhancement Proposals Philosophy of the Python Programming Language Applications of Python Installing Python on Various Platforms Installing on a Windows Computer Installing on Ubuntu/Debian Derivatives Using Python Modes Interactive Mode Script Mode Using Python IDEs Exploring the Scientific Python Ecosystem Introducing Jupyter Notebook Setting Up Jupyter Notebook Running Code in Jupyter Notebook Anaconda Summary Chapter 2: Getting Started with NumPy NumPy and Ndarrays Indexing in Ndarrays Indexing in Ndarrays of More Than One Dimension Ndarray Properties NumPy Constants Slicing Ndarrays Summary Chapter 3: NumPy Routines and Getting Started with Matplotlib Routines for Creating Ndarrays Matplotlib Visualization with NumPy and Matplotlib Running the Matplotlib Program as a Script Summary Chapter 4: Revisiting Matplotlib Visualizations Single-Line Plots Multiline Plots Grid, Axes, and Labels Colors, Styles, and Markers Object-Oriented Plotting Subplots Summary Chapter 5: Styles and Layouts Styles Layouts Summary Chapter 6: Lines, Bars, and Scatter Plots Lines and Logs Error Bars Bar Graphs Scatter Plot Summary Chapter 7: Histograms, Contours, and Stream Plots Histograms Contours Visualizing Vectors with Stream Plots Summary Chapter 8: Image and Audio Visualization Visualizing Images Image Masking Interpolation Methods Audio Visualization Audio Processing Summary Chapter 9: Pie and Polar Charts Pie Charts Polar Charts Summary Chapter 10: Working with Colors pcolor() pcolormesh() colorbar() Summary Chapter 11: 3D Visualizations in Matplotlib Getting Ready Plotting 3D Lines 3D Scatter Plots 3D Contours Wireframes, Surfaces, and Sample Data Bar Graphs Quiver and Stem Plots 3D Volumes Summary Chapter 12: Animations with Matplotlib Animation Basics Celluloid Library Summary Chapter 13: More Visualizations with Matplotlib Visualizing a Function as an Image and a Contour 3D Vignettes Decorated Scatter Plots Time Plots and Signals Filled Plots Step Plots Hexbins XKCD Style Summary Chapter 14: Introduction to Pandas Introduction to Pandas Series in Pandas Basic Operations on Series Dataframe in Pandas Summary Chapter 15: Data Acquisition Plain-Text File Handling Handling CSV Files with Python Python and Excel Writing and Reading Files with NumPy Reading the Data from a CSV File with NumPy Matplotlib CBook Reading Data from a CSV Reading Data from an Excel File Reading Data from JSON Reading Data from a Pickle File Reading Data from the Web Interacting with the Web API Reading Data from a Relational Database Table Reading Data from the Clipboard Summary Chapter 16: Visualizing Data with Pandas and Matplotlib Simple Plots Bar Graphs Histograms Box Plots Area Plots Scatter Plots Hexagonal Bin Plots Pie Charts Summary Chapter 17: Introduction to Data Visualization with Seaborn What Is Seaborn? Plotting Statistical Relationships Plotting Lines Visualizing the Distribution of Data Summary Chapter 18: Visualizing Real-Life Data with Matplotlib and Seaborn COVID-19 Pandemic Data Fetching the Pandemic Data Programmatically Preparing the Data for Visualization Creating Visualizations with Matplotlib and Seaborn Creating Visualizations of Animal Disease Data Summary Index