Chapter Goal: Introduce the reader to the basics of Python programming language, philosophy, and installation. We will also learn how to install it on various platforms. This chapter also introduces the readers to Python programming with Jupyter notebook. In the end, we will also have a brief overview of the constituent libraries of SciPy stack.

No of pages - 26

Sub -Topics

• Python Programming Language

• Installing Python on various platforms

• Python Modes

• Python IDEs

• Scientific Python Ecosystem

• Overview of Jupyter Notebook

• Setting up Jupyter Notebook

• Running Code in Jupyter Notebook

Chapter 2: Getting Started with NumPy

Chapter Goal: Get started with NumPy Ndarrays and basics of NumPy library. The chapter covers the instructions for installation and basic usage of NumPy.

No of pages: 9

Sub - Topics:

· Introduction to the NumPy Ndarrays

· Ndarray Properties

· NumPy Constants

Chapter 3 : NumPy Routines and Getting started with Matplotlib

Chapter goal – In this chapter, we will discuss the various Ndarray creation routines available in NumPy. We will also get started with visualizations with Matplotlib. We will learn how to visualize the various numerical ranges with Matplotlib.

No of pages: 15

Sub - Topics:

· Routines for creating Ndarrays

· Matplotlib

· Visualization with NumPy and Matplotlib

Chapter 4 : Revisiting Matplotlib Visualizations

Chapter goal – This chapter is focused on learning the details of Matplotlib styles for visualizing NumPy Ndarrays.

No of pages: 24

Sub - Topics:

• Single Line Plots

• Multiline plots

• Grid, Axes, and Labels

• Colors, Lines, and Markers

• Subplots

• Object Oriented Style

• Working with the text

Chapter 5 : Styles and Layouts

Chapter goal – This chapter is focused on learning the details of Matplotlib styles and layouts.

No of pages: 12

Sub - Topics:

1. Styles

2. layouts

Chapter 6 : Line, Bar, and Scatter Plots

Chapter goal – In this chapter, we will learn how to create nice visualizations with lines, bars, and scatter.

No of pages: 14

Sub - Topics:

· Lines and Logs

· Errorbar

· Bar Graphs

· Scatter Plot

Chapter 7 : Histograms, Contours, and Streamplots

Chapter goal – In this chapter, we will learn how to create nice visualizations histograms, contours, and streamplots.

No of pages: 15

Sub - Topics:

• Histograms

• Contours

• Plot vector entities with streamplots

Chapter 8 : Image and Audio Visualization

Chapter goal – Learn to work with Image Processing using NumPy and Matplotlib. Also learn how to process and visualize audio data as waveforms.

No of pages: 15

Sub - Topics:

• Visualizing images

• Interpolation Methods

• Audio Visualization

• Audio Processing

Chapter 9 : Pie and Polar Charts

Chapter goal – Learn to work with Pie and Polar charts.

No of pages: 12

Sub - Topics:

1. Pie charts

2. Polar charts

Chapter 10 : PColor, Pcolormesh, and Colorbar

Chapter goal – In this chapter, we will learn Pcolor, Pcolormesh, and colorbar.

No of pages: 10

Sub - Topics:

1. PColor

2. Pcolormesh

3. Colorbar

Chapter 11 : 3D Visualizations in Matplotlib

Chapter goal – In this chapter, we will learn how to create 3D visualizations.

No of pages: 17

Sub - Topics:

• Getting Ready

• Plotting 3D Line

• 3D Scatter plot

• 3D Contours

• Wireframe, Surface, and Sample Data

• Bar graphs

• Quiver and Stemplot

• 3D Volumes

Chapter 12 : Animations with Matplotlib

Chapter goal – In this chapter, we will learn how to create simple animations with Matplotlib.

No of pages: 8

Sub - Topics:

• Animation Basics

• Celluloid library

Chapter 13 : More Recipes of Visualizations with Matplotlib

Chapter goal – In this chapter, we will learn more types of visualizations with Matplotlib.

No of pages: 14

Sub - Topics:

· Visualizing Function as an image and a contour

· 3D Vignette

· Decorated Scatter Plots

· Time plots and Signals

· Filled Plots

· Step Plots

· Hexbins

· XKCD Style

Chapter 14 : Introduction to Pandas

Chapter goal – Get started with Pandas data structures

No of pages: 10

Sub - Topics:

• Introduction to Pandas

• Series in Pandas

• Dataframe in Pandas

Chapter 15 : Data Acquisition

Chapter goal – Read the data from various sources

No of pages: 18

Sub - Topics:

• Plain Text File Handling

• Handling CSV 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

• Reading data from JSON

• Reading data from Pickle

• Reading data from Web

• Reading data from Relation databases

• Reading Data from the clipboard

Chapter 16 : Visualizing Data with Pandas and Matplotlib

Chapter goal – Get started with Data Visualization with Matplotlib

No of pages: 25

• Simple Plots

• Bar Graphs

• Histogram

• Box Plot

• Area Plots

• Scatter Plot

• Hexagonal Bin Plot

• Pie Charts

Chapter 17 : Introduction to Data Visualization with Seaborn

Chapter goal – Get started with Pandas and seaborn

No of pages: 20

Sub - Topics:

• What is Seaborn?

• Plotting statistical Relationships

• Plotting Lines

• Visualizing the distribution of data

Chapter 18 : Visualizing real-life Data with Matplotlib and Seaborn

Chapter goal – Get started with COVID and Animal disease datasets and Visualize them

No of pages: 20

Sub - Topics:

• COVID-19 Pandemic Data

• Fetching the Pandemic Data Programmatically

• Preparing the data for visualization

• Visualization with Matplotlib and Seaborn

• Visualization of Animal Disease Data

Ashwin Pajankar holds a Master of Technology from IIIT Hyderabad, and has over 25 years of programming experience. He started his journey in programming and electronics with BASIC programming language and is now proficient in Assembly programming, C, C++, Java, Shell Scripting, and Python. Other technical experience includes single board computers such as Raspberry Pi and Banana Pro, and Arduino.

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.

You will:

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

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