Practical Python Data Visualization - A Fast Track Approach To Learning Data Visualization With Python - Pajankar Ashwin

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Résumé :
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. You will : - 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

Sommaire:

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

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

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

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

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