Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python, and most importantly, helps you make your storytelling more intuitive and persuasive.

• Cover
• FM
• Copyright
• Table of Contents
• Preface
• Chapter 1: Introduction to Visualization with Python – Basic and Customized Plotting
  • Introduction
  • Handling Data with pandas DataFrame
    • Reading Data from Files
    • Exercise 1: Reading Data from Files
    • Observing and Describing Data
    • Exercise 2: Observing and Describing Data
    • Selecting Columns from a DataFrame
    • Adding New Columns to a DataFrame
    • Exercise 3: Adding New Columns to the DataFrame
    • Applying Functions on DataFrame Columns
    • Exercise 4: Applying Functions on DataFrame columns
    • Exercise 5: Applying Functions on Multiple Columns
    • Deleting Columns from a DataFrame
    • Exercise 6: Deleting Columns from a DataFrame
    • Writing a DataFrame to a File
    • Exercise 7: Writing a DataFrame to a File
  • Plotting with pandas and seaborn
    • Creating Simple Plots to Visualize a Distribution of Variables
    • Exercise 8: Plotting and Analyzing a Histogram
    • Bar Plots
    • Exercise 9: Creating a Bar Plot and Calculating the Mean Price Distribution
    • Exercise 10: Creating Bar Plots Grouped by a Specific Feature
  • Tweaking Plot Parameters
    • Exercise 11: Tweaking the Plot Parameters of a Grouped Bar Plot
    • Annotations
    • Exercise 12: Annotating a Bar Plot
    • Activity 1: Analyzing Different Scenarios and Generating the Appropriate Visualization
  • Summary
• Chapter 2: Static Visualization – Global Patterns and Summary Statistics
  • Introduction
  • Creating Plots that Present Global Patterns in Data
    • Scatter Plots
    • Exercise 13: Creating a Static Scatter Plot
    • Hexagonal Binning Plots
    • Exercise 14: Creating a Static Hexagonal Binning Plot
    • Contour Plots
    • Exercise 15: Creating a Static Contour Plot
    • Line Plots
    • Exercise 16: Creating a Static Line Plot
    • Exercise 17: Presenting Data across Time with multiple Line Plots
    • Heatmaps
    • Exercise 18: Creating and Exploring a Static Heatmap
    • The Concept of Linkage in Heatmaps
    • Exercise 19: Creating Linkage in Static Heatmaps
  • Creating Plots That Present Summary Statistics of Your Data
    • Histogram Revisited
    • Example 1: Histogram Revisited
    • Box Plots
    • Exercise 20: Creating and Exploring a Static Box Plot
    • Violin Plots
    • Exercise 21: Creating a Static Violin Plot
    • Activity 2: Design Static Visualization to Present Global Patterns and Summary Statistics
  • Summary
• Chapter 3: From Static to Interactive Visualization
  • Introduction
  • Static versus Interactive Visualization
  • Applications of Interactive Data Visualizations
  • Getting Started with Interactive Data Visualizations
    • Interactive Data Visualization with Bokeh
    • Exercise 22: Preparing Our Dataset
    • Exercise 23: Creating the Base Static Plot for an Interactive Data Visualization
    • Exercise 24: Adding a Slider to the Static Plot
    • Exercise 25: Adding a Hover Tool
    • Interactive Data Visualization with Plotly Express
    • Exercise 26: Creating an Interactive Scatter Plot
    • Activity 3: Creating Different Interactive Visualizations Using Plotly Express
  • Summary
• Chapter 4: Interactive Visualization of Data across Strata
  • Introduction
  • Interactive Scatter Plots
    • Exercise 27: Adding Zoom-In and Zoom-Out to a Static Scatter Plot
    • Exercise 28: Adding Hover and Tooltip Functionality to a Scatter Plot
    • Exercise 29: Exploring Select and Highlight Functionality on a Scatter Plot
    • Exercise 30: Generating a Plot with Selection, Zoom, and Hover/Tooltip Functions
    • Selection across Multiple Plots
    • Exercise 31: Selection across Multiple Plots
    • Selection Based on the Values of a Feature
    • Exercise 32: Selection Based on the Values of a Feature
  • Other Interactive Plots in altair
    • Exercise 33: Adding a Zoom-In and Zoom-Out Feature and Calculating the Mean on a Static Bar Plot
    • Exercise 34: An Alternative Shortcut for Representing the Mean on a Bar Plot
    • Exercise 35: Adding a Zoom Feature on a Static Heatmap
    • Exercise 36: Creating a Bar Plot and a Heatmap Next to Each Other
    • Exercise 37: Dynamically Linking a Bar Plot and a Heatmap
    • Activity 4: Generate a Bar Plot and a Heatmap to Represent Content Rating Types in the Google Play Store Apps Dataset
  • Summary
• Chapter 5: Interactive Visualization of Data across Time
  • Introduction
  • Temporal Data
  • Types of Temporal Data
    • Why Study Temporal Visualization?
  • Understanding the Relation between Temporal Data and Time‑Series Data
  • Examples of Domains That Use Temporal Data
  • Visualization of Temporal Data
    • How Time-Series Data Is Manipulated and Visualized
    • Date/Time Manipulation in pandas
    • Building a DateTime Index
  • Choosing the Right Aggregation Level for Temporal Data
    • Exercise 38: Creating a Static Bar Plot and Calculating the Mean and Standard Deviation in Temporal Data
    • Exercise 39: Calculating zscore to Find Outliers in Temporal Data
  • Resampling in Temporal Data
    • Common Pitfalls of Upsampling and Downsampling
    • Exercise 40: Upsampling and Downsampling in Temporal Data
    • Using shift and tshift to Introduce a Lag in Time-Series Data
    • Exercise 41: Using shift and tshift to Shift Time in Data
    • Autocorrelation in Time Series
  • Interactive Temporal Visualization
    • Bokeh Basics
    • Advantages of Using Bokeh
    • Exercise 42: Adding Interactivity to Static Line Plots Using Bokeh
    • Exercise 43: Changing the Line Color and Width on a Line Plot
    • Exercise 44: Adding Box Annotations to Find Anomalies in a Dataset
    • Interactivity in Bokeh
    • Activity 5: Create an Interactive Temporal Visualization
  • Summary
• Chapter 6: Interactive Visualization of Geographical Data
  • Introduction
  • Choropleth Maps
    • Worldwide Choropleth Maps
    • Exercise 45: Creating a Worldwide Choropleth Map
    • Exercise 46: Tweaking a Worldwide Choropleth Map
    • Exercise 47: Adding Animation to a Choropleth Map
    • USA State Maps
    • Exercise 48: Creating a USA State Choropleth Map
  • Plots on Geographical Maps
    • Scatter Plots
    • Exercise 49: Creating a Scatter Plot on a Geographical Map
    • Bubble Plots
    • Exercise 50: Creating a Bubble Plot on a Geographical Map
    • Line Plots on Geographical Maps
    • Exercise 51: Creating Line Plots on a Geographical Map
    • Activity 6: Creating a Choropleth Map to Represent Total Renewable Energy Production and Consumption across the World
  • Summary
• Chapter 7: Avoiding Common Pitfalls to Create Interactive Visualizations
  • Introduction
  • Data Formatting and Interpretation
    • Avoiding Common Pitfalls while Dealing with Dirty Data
    • Outliers
    • Exercise 52: Visualizing Outliers in a Dataset with a Box Plot
    • Exercise 53: Dealing with Outliers
    • Missing Data
    • Exercise 54: Dealing with Missing Values
    • Duplicate Instances and/or Features
    • Bad Feature Selection
    • Activity 7: Determining Which Features to Visualize on a Scatter Plot
  • Data Visualization
    • Choosing a Visualization
    • Common Pitfalls While Visualizing Data
    • Exercise 55: Creating a Confusing Visualization
    • Activity 8: Creating a Bar Graph for Improving a Visualization
  • Cheat Sheet for the Visualization Process
  • Summary
• Appendix
• Index