In this lesson, you will learn to make and interpret more advanced data visualizations like histograms by using MatPlotLib. Next you will learn about improving the appearance of data visualizations to better convey information, which we can easily do by using the Seaborn library. Finally, you will learn how to use Seaborn to make visually more appealing plots, how to use Kernel Density Estimation to improve histograms, and how to make box plots and violin plots.
###Objectives ### By the end of this lesson, you will be able to:
- Understand how to use Matplotlib to make and use Histograms.
- Understand the importance of Beautiful Visualizations.
- Understand how to use Seaborn to improve the appearance of a plot.
- Understand how to make and use Box and Violin plots.
- Understand how to use KDE to improve a Box plot.
Approximately 3 hours.
- IPython Notebook introducing MatPlotLib Histograms
- The Beauty of Data Visualization
- Seaborn Plotting
- Demonstration of improving a single visualization
- Seaborn Aesthetics
- Color Palettes
- IPython Notebook introducing MatPlotLib and Seaborn
- Discussion of Histograms
- Imaginative Visualizations
When you have completed and worked through the above readings, please take the Week 5 Lesson 3 Assessment.