Chapter 2

Data Exploration and Visualization

Learning Objectives

By the end of this chapter, you will be able to:

  • Create summaries, aggregations, and descriptive statistics from your data
  • Reshape pandas DataFrames to detect relationships in data
  • Build pivot tables and perform comparative analysis and tests
  • Create effective visualizations through Matplotlib and seaborn

This chapter explains how to derive various descriptive statistics and generate insights and visualizations from your data.


In the previous chapter, we saw how to transform data and attributes obtained from raw sources into expected attributes and values through pandas. After structuring data into a tabular form, with each field containing the expected (correct ...

Get Data Science for Marketing Analytics now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.