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

Auteur
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.

Contenu

Chapter 1: Getting Started with Python and Jupyter Notebook

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