Practical Python data visualization : a fast track approach to learning data visualization with Python
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Bibliographic Information
Practical Python data visualization : a fast track approach to learning data visualization with Python
（Books for professionals by professionals）
Apress, c2021
- : pbk
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Includes index
Description and Table of Contents
Description
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
Chapter 1: Data Visualization with Leather
Chapter Goal: Introduce readers to the data visualization with a simple library leather
No of pages: 15
Sub - Topics:
1. Introduction to leather
2. Installation to leather
3. Various types of graphs with leather
Chapter 2: Introduction to the Scientific Python Ecosystem and NumPy
Chapter Goal: Explore Scientific Python 3 ecosystem and constituent member libraries. We will also learn basics of the NumPy multidimensional data structure Ndarrays.
No of pages: 15
Sub - Topics:
1. Scientific Python 3 Ecosystem
2. Member libraries
3. Installation of NumPy
4. NumPy basics
5. Ndarrays
Chapter 3: NumPy Routines and Visualization with Matplotlib
Chapter goal - Learn to visualize data with Matplotlib. Readers working in the data science and scientific domains will be thrilled to get started with this.
No of pages: 15
Sub - Topics:
1. NumPy Ndarray creation Routines
2. Installation of Matplotlib
3. Visualization with Matplotlib
4. Multiple graphs
5. Axis, colors, and markers
Chapter 4 : Visualizing images and 3D Shapes
Chapter goal - Learn to visualize greyscale and color images. We will explore basic image processing operations. We will also learn to visualize 3D shapes and wireframes.
No of pages: 20
Sub - Topics:
1. Visualize images with Matplotlib
2. Basic Operations on images
3. 3D visualizations
Chapter 5 : Visualize Networks and Graphs
Chapter goal - Network and Graph Data structures. We will learn to install network library and visualize network.
No of pages: 15
Sub - Topics:
1. Networks and Graphs
2. Installation of network library
3. Visualize graphs
Chapter 6 : Getting Started with Pandas
Chapter goal - Learn to work with Pandas Series and Dataframe data structures.
No of pages: 15
Sub - Topics:
1. Pandas library and installation
2. Series
3. Dataframes
4. Reading data from a URL
Chapter 7: Processing and Visualizing COVID-19 Data
Chapter goal - Learn to work with COVID-19 Data. Visualize the number of COVID-19.
No of pages: 20
Sub - Topics:
1. COVID-19 Pandemic
2. COVID 19 data sources
3. COVID 19 python libraries
4. Visualization of data
Appendix:
by "Nielsen BookData"
