Exploratory Data Analysis in Pythonpro-logo


In this course, you will learn about exploratory data analysis techniques in Python, including:

  • EDA for data preparation
  • Summary statistics
  • Data visualization techniques
  • EDA prior to building a machine learning model

Prior to taking this course, you should have some knowledge of base Python and experience with pandas DataFrames.

Exploratory data analysis is an important part of any Data Scientist or Analyst’s workflow, so we highly recommend this course for anyone who is interested in working with data.

Codecademy courses have been taken by employees at

Google LogoFacebook LogoNASA LogoIBM LogoDropbox Logo
  1. 1
    Learn about exploratory data analysis and what it is used for.
  2. 2
    Learn how to use exploratory data analysis (EDA) to inform data inspection, cleaning, and validation.
  3. 3
    Learn how to explore a single feature in a dataset using summary statistics and simple data visualizations.
  4. 4
    Learn how to use aggregate functions in pandas to calculate tables of summary statistics.
  5. 5
    Learn how to investigate whether there is an association between two variables.

What you'll create

Portfolio projects that showcase your new skills

Pro Logo

How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory

Pro Logo
Madelyn from Pinterest
I know from first-hand experience that you can go in knowing zero, nothing, and just get a grasp on everything as you go and start building right away.
— Madelyn, Pinterest