Practical Python Data Visualization

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
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