Description
Book SynopsisLearn 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 Matpl
Table of ContentsChapter 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
• Object Oriented Style
• Working with the text
Chapter 5 : Styles and Layouts
Chapter goal – This chapter is focused on learning the details of Matplotlib styles and layouts.
No of pages: 12
Sub - Topics:
1. Styles
2. layouts
Chapter 6 : Line, Bar, and Scatter Plots
Chapter goal – In this chapter, we will learn how to create nice visualizations with lines, bars, and scatter.
No of pages: 14
Sub - Topics:
· Lines and Logs
· Errorbar
· Bar Graphs
· Scatter Plot
Chapter 7 : Histograms, Contours, and Streamplots
Chapter goal – In this chapter, we will learn how to create nice visualizations histograms, contours, and streamplots.
No of pages: 15
Sub - Topics:
• Histograms
• Contours
• Plot vector entities with streamplots
Chapter 8 : Image and Audio Visualization
Chapter goal – Learn to work with Image Processing using NumPy and Matplotlib. Also learn how to process and visualize audio data as waveforms.
No of pages: 15
Sub - Topics:
• Visualizing images
• Interpolation Methods
• Audio Visualization
• Audio Processing
Chapter 9 : Pie and Polar Charts
Chapter goal – Learn to work with Pie and Polar charts.
No of pages: 12
Sub - Topics:
1. Pie charts
2. Polar charts
Chapter 10 : PColor, Pcolormesh, and Colorbar
Chapter goal – In this chapter, we will learn Pcolor, Pcolormesh, and colorbar.
No of pages: 10
Sub - Topics:
1. PColor
2. Pcolormesh
3. Colorbar
Chapter 11 : 3D Visualizations in Matplotlib
Chapter goal – In this chapter, we will learn how to create 3D visualizations.
No of pages: 17
Sub - Topics:
• Getting Ready
• Plotting 3D Line
• 3D Scatter plot
• 3D Contours
• Wireframe, Surface, and Sample Data
• Bar graphs
• Quiver and Stemplot
• 3D Volumes
Chapter 12 : Animations with Matplotlib
Chapter goal – In this chapter, we will learn how to create simple animations with Matplotlib.
No of pages: 8
Sub - Topics:
• Animation Basics
• Celluloid library
Chapter 13 : More Recipes of Visualizations with Matplotlib
Chapter goal – In this chapter, we will learn more types of visualizations with Matplotlib.
No of pages: 14
Sub - Topics:
· Visualizing Function as an image and a contour
· 3D Vignette
· Decorated Scatter Plots
· Time plots and Signals
· Filled Plots
· Step Plots
· Hexbins
· XKCD Style
Chapter 14 : Introduction to Pandas
Chapter goal – Get started with Pandas data structures
No of pages: 10
Sub - Topics:
• Introduction to Pandas
• Series in Pandas
• Dataframe in Pandas
Chapter 15 : Data Acquisition
Chapter goal – Read the data from various sources
No of pages: 18
Sub - Topics:
• Plain Text File Handling
• Handling CSV with Python
• Python and Excel
• Writing and reading files with NumPy
• Reading the data from a CSV file with NumPy
• Matplotlib CBook
• Reading data from a CSV
• Reading data from an Excel
• Reading data from JSON
• Reading data from Pickle
• Reading data from Web
• Reading data from Relation databases
• Reading Data from the clipboard
Chapter 16 : Visualizing Data with Pandas and Matplotlib
Chapter goal – Get started with Data Visualization with Matplotlib
No of pages: 25
• Simple Plots
• Bar Graphs
• Histogram
• Box Plot
• Area Plots
• Scatter Plot
• Hexagonal Bin Plot
• Pie Charts
Chapter 17 : Introduction to Data Visualization with Seaborn
Chapter goal – Get started with Pandas and seaborn
No of pages: 20
Sub - Topics:
• What is Seaborn?
• Plotting statistical Relationships
• Plotting Lines
• Visualizing the distribution of data
Chapter 18 : Visualizing real-life Data with Matplotlib and Seaborn
Chapter goal – Get started with COVID and Animal disease datasets and Visualize them
No of pages: 20
Sub - Topics:
• COVID-19 Pandemic Data
• Fetching the Pandemic Data Programmatically
• Preparing the data for visualization
• Visualization with Matplotlib and Seaborn
• Visualization of Animal Disease Data
