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Data Visualization with Python for Beginners

Release Date: 2021/03/01
ISBN: 9781801814003
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This book works as a guide to present fundamental Python libraries and basics related to data visualization using Python

Key Features

  • Detailed introductions to several data visualization libraries such as Matplotlib and Seaborn
  • Guided instructions to more advanced data visualization skills such as 3D plotting or interactive visualization
  • Hands-on projects for interactive practice designed to cement your new skills in practical memory

Book Description

Data science and data visualization are two different but interrelated concepts. Data science refers to the science of extracting and exploring data to find patterns that can be used for decision making at different levels. Data visualization can be considered a subdomain of data science. You visualize data with graphs and tables to find out which data is most significant and help identify meaningful patterns.

This book is dedicated to data visualization and explains how to perform data visualization on different datasets using various data visualization libraries written in the Python programming language. It is suggested that you use this book for data visualization purposes only and not for decision making. For decision making and pattern identification, read this book in conjunction with a dedicated book on machine learning and data science.

We will start by digging into Python programming as all the projects are developed using it, and it is currently the most used programming language in the world. We will also explore some of the most famous libraries for data visualization, such as Pandas, NumPy, Matplotlib, and Seaborn.

You will learn all about Python in three modules—plotting with Matplotlib, plotting with Seaborn, and a final one, Pandas for data visualization. All three modules will contain hands-on projects using real-world datasets and a lot of exercises. By the end of this course, you will have the knowledge and skills required to visualize data with Python all on your own.

The code bundle for this course is available at https://www.aispublishing.net/book-data-visualization

What you will learn

  • Begin visualizing data with Matplotlib
  • Explore the Python Seaborn library for advanced plotting
  • Analyze data with the Pandas library
  • Expand your visualization skills with Pandas
  • Plot in three dimensions with Matplotlib
  • Practice interactive data visualization with Bokeh and Plotly
  • Complete several hands-on projects

Who this book is for

This book is written with one goal in mind—to help beginners overcome their initial obstacles in learning data visualization using Python. This book aims to isolate the different concepts so that beginners can gradually gain competency in the fundamentals of Python before working on a project. As such, no prior experience is required.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. How to contact us
  5. About the Publisher
  6. AI Publishing is searching for author like you
  7. Table of Contents
  8. Preface
  9. Chapter 1: Introduction
    1. 1.1. What is Data Visualization
    2. 1.2. Environment Setup
    3. 1.3. Python Crash Course
    4. 1.4. Data Visualization Libraries
    5. Exercise 1.1
    6. Exercise 1.2
  10. Chapter 2: Basic Plotting with Matplotlib
    1. 2.1. Introduction
    2. 2.2. Line Plots
    3. 2.3. Titles, Labels, and Legends
    4. 2.4. Plotting Using CSV Data Source
    5. 2.5. Plotting Using TSV Data Source
    6. 2.6. Scatter Plot
    7. 2.7. Bar Plots
    8. 2.8. Histograms
    9. 2.9. Pie Charts
    10. 2.10. Stack Plot
    11. Exercise 2.1
    12. Exercise 2.2
  11. Chapter 3: Advanced Plotting with Matplotlib
    1. 3.1. Introduction
    2. 3.2. Plotting Multiple Plots
    3. 3.3. Plotting in Object-Oriented Way
    4. 3.4. Using Subplots Function to Create Multiple Plots
    5. 3.5. Saving a Matplotlib Plot
    6. Exercise 3.1
    7. Exercise 3.2
  12. Chapter 4: Introduction to the Python Seaborn Library
    1. 4.1. Introduction
    2. 4.2. The Dist Plots
    3. 4.3. Joint Plot
    4. 4.4. Pair Plot
    5. 4.5. Rug Plot
    6. 4.6. Bar Plot
    7. 4.7. Count Plot
    8. 4.8. Box Plot
    9. 4.9. Violin Plot
    10. 4.10. Strip Plot
    11. 4.11. Swarm Plot
    12. Exercise 4.1
    13. Exercise 4.2
  13. Chapter 5: Advanced Plotting with Seaborn
    1. 5.1. Scatter Plot
    2. 5.2. Styling Seaborn Plots
    3. 5.3. Heat Maps
    4. 5.4. Cluster Maps
    5. 5.5. Pair Grids
    6. 5.6. Facet Grids
    7. 5.7. Regression Plots
    8. Exercise 5.1
    9. Exercise 5.2
  14. Chapter 6: Introduction to Pandas Library for Data Analysis
    1. 6.1. Introduction
    2. 6.2. Reading Data into the Pandas Dataframe
    3. 6.3. Filtering Rows
    4. 6.4. Filtering Columns
    5. 6.5. Concatenating Dataframes
    6. 6.6. Sorting Dataframes
    7. 6.7. Apply Function
    8. 6.8. Pivot & Crosstab
    9. 6.9. Arithmetic Operations with Where
    10. Exercise 6.1
    11. Exercise 6.2
  15. Chapter 7: Pandas for Data Visualization
    1. 7.1. Introduction
    2. 7.2. Loading Datasets with Pandas
    3. 7.3. Plotting Histograms with Pandas
    4. 7.4. Pandas Line Plots
    5. 7.5. Pandas Scatter Plots
    6. 7.6. Pandas Bar Plots
    7. 7.7. Pandas Box Plots
    8. 7.8. Pandas Hexagonal Plots
    9. 7.9. Pandas Kernel Density Plots
    10. 7.10. Pandas for Time Series Data Visualization
    11. Exercise 7.1
    12. Exercise 7.2
  16. Chapter 8: 3D Plotting with Matplotlib
    1. 8.1. 3D Line Plot
    2. 8.2. 3D Scatter Plot
    3. 8.3. 3D Bar Plot
    4. Exercise 8.1
  17. Chapter 9: Interactive Data Visualization with Bokeh
    1. 9.1. Installation
    2. 9.2. Line Plots
    3. 9.3. Bar Plots
    4. 9.4. Scatter Plots
    5. Exercise 9.1
    6. Exercise 9.2
  18. Chapter 10: Interactive Data Visualization with Plotly
    1. 10.1. Installation
    2. 10.2. Line Plot
    3. 10.3. Bar Plot
    4. 10.4. Scatter Plot
    5. 10.5. Box Plot
    6. 10.6. Histogram
    7. Exercise 10.1
    8. Exercise 10.2
  19. Hands-on Project
  20. Exercise Solutions
    1. Exercise 1.1
    2. Exercise 1.2
    3. Exercise 2.1
    4. Exercise 2.2
    5. Exercise 3.1
    6. Exercise 3.2
    7. Exercise 4.1
    8. Exercise 4.2
    9. Exercise 5.1
    10. Exercise 5.2
    11. Exercise 6.1
    12. Exercise 6.2
    13. Exercise 7.1
    14. Exercise 7.2
    15. Exercise 8.1
    16. Exercise 9.1
    17. Exercise 9.2
    18. Exercise 10.1
    19. Exercise 10.2
  21. Back Cover
18.222.10.9