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2021 | Book

Introduction to Python Read chapter Read first chapter

Practical Python Data Visualization

A Fast Track Approach To Learning Data Visualization With Python

Author: Ashwin Pajankar

Publisher: Apress

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book’s programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations.

You’ll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python’s popular data visualization charting library. You’ll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You’ll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets.

The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. With Practical Python Data Visualization you’ll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.

What You'll Learn

Review practical aspects of Python Data Visualization with programming-friendly abstractions Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu Visualize COVID-19 data sets with Pandas

Who This Book Is For

Data Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers.

Table of Contents

Frontmatter
Chapter 1. Introduction to Python
Abstract
I welcome you all to the exciting journey of learning data visualization with Python 3. This chapter provides details to get you started with the Python programming language, including its history, features, and applications. This chapter is focused on general information about Python 3 and its installation on various popular operating system (OS) platforms, such as Microsoft Windows, Ubuntu, and Raspberry Pi Raspbian. We will be writing a few basic Python programs and learn how to execute them on various platforms. Here is the list of topics that we will cover in this chapter.
Ashwin Pajankar
Chapter 2. Exploring Jupyter Notebook
Abstract
In Chapter 1, we acquainted ourselves with Python and learned how to write a very simple program with Python. We also saw how to use Python in both interactive mode and script mode. In this chapter, we explore Jupyter Notebook. In Chapter 1 we saw that interactive mode offers us the immediate feedback of Python statements. We will continue using the interactive mode of Python throughout the book almost all of the demonstrations. However, rather than using Python’s built-in interactive mode with an interpreter, we will use another and much better tool known as the Jupyter tool. This entire chapter is dedicated to this topic.
Ashwin Pajankar
Chapter 3. Data Visualization with Leather
Abstract
In Chapter 2, we acquainted ourselves with Python programming using Jupyter Notebook. You should now be comfortable writing interactive Python programs with Jupyter Notebook.
Ashwin Pajankar
Chapter 4. Scientific Python Ecosystem and NumPy
Abstract
In Chapter 3, you learned how to create simple visualizations with Python 3 and the leather data visualization library. You also learned that only primitive visualizations can be prepared using the leather data visualization library. For more complex and elaborate visualizations, we need to use libraries with the advanced data handling and visualization capabilities.
Ashwin Pajankar
Chapter 5. Data Visualization with NumPy and Matplotlib
Abstract
Chapter 4 introduced the basics of NumPy. You learned how to install it and how to create ndarrays. In this chapter, we continue working with NumPy by looking at a few ndarray creation routines. We will also get started with the data visualization library of the scientific computing ecosystem, Matplotlib. We will use the NumPy ndarray creation routines to demonstrate visualizations with Matplotlib. This is a detailed chapter with emphasis on coding and visualizations. The following topics are covered in this chapter:
Ashwin Pajankar
Chapter 6. Visualizing Images and 3D Shapes
Abstract
In Chapter 5, we got started with visualization using the Matplotlib library in Python 3. In this chapter, we will continue our adventures with Matplotlib and NumPy to visualize images and 3D shapes. Let’s continue our exploration of data visualization with the following topics:
Ashwin Pajankar
Chapter 7. Visualizing Graphs and Networks
Abstract
In Chapter 6, we demonstrated the visualization of images and 3D objects with Python 3 and Matplotlib. We also learned a bit of image processing.
Ashwin Pajankar
Chapter 8. Getting Started with Pandas
Abstract
Chapter 7 covered the visualization of graphs using the Python library networkx. This chapter focuses on the basics of the data science and analytics library of SciPy, pandas. First, we will explore the data structures in this library. You will also learn how to read the data from a .csv data set. Finally, you will learn how to create simple demonstrations of visualizations. These are the topics that are covered in the chapter:
Ashwin Pajankar
Chapter 9. Working with COVID-19 Data
Abstract
Chapter 8 covered the basics of the data science library of SciPy, pandas. You learned the basics of the series and dataframe data structures and how to visualize the data in the dataframes and series.
Ashwin Pajankar
Backmatter
Metadata
Title
Practical Python Data Visualization
Author
Ashwin Pajankar
Copyright Year
2021
Publisher
Apress
Electronic ISBN
978-1-4842-6455-3
Print ISBN
978-1-4842-6454-6
DOI
https://doi.org/10.1007/978-1-4842-6455-3

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