Chapter 2. Creating Attractive Data Visualizations

In this chapter, we will cover:

• Graphing Anscombe's quartet
• Choosing seaborn color palettes
• Choosing matplotlib color maps
• Interacting with IPython notebook widgets
• Viewing a matrix of scatterplots
• Visualizing with d3.js via mpld3
• Creating heatmaps
• Combining box plots and kernel density plots with violin plots
• Visualizing network graphs with hive plots
• Displaying geographical maps
• Using ggplot2-like plots
• Highlighting data points with influence plots