In this lesson, you will learn how to visually explore a data set/ This lesson will build on the results of lesson 1, where you constructed a data subset of the airline flight data and stored this data in a compact HDF format. First, you will read this data into your IPython Notebook, after which you will generate different visual representations from the data, including pair plots, grouped scatter pots, box plots, violin plots, histograms, joint plots, and heat maps.
###Objectives ### By the end of this lesson, you will be able to:
- Understand the different types of visualizations that can be used to gain insight into a data set.
- Understand how to make and interpret a pari plot.
- Understand how to use box plots, violin plots, and histograms to understand large data sets.
- Understand how to use summary visualizations like a heat map to understand large data sets.
Approximately 2 hours.
- Course IPython Notebook on Python data visual exploration
- Relevant sections from the Seaborn tutorial(corresponding to the plot type being used in the course IPython Notebook).
When you have completed and worked through the above readings, please take the Week 12 Lesson 2 Assessment.