Black Friday 2024: 25+ Ways to Save on Online Learning

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Codecademy

Exploratory Data Analysis in Python

via Codecademy

Go to class Write review

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Grab it
Learn about exploratory data analysis (EDA) techniques.

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.

Syllabus

  • Introduction to EDA: Learn about exploratory data analysis and what it is used for.
    • Article: What is EDA?
  • Inspect, Clean, and Validate a Dataset: Learn how to use exploratory data analysis (EDA) to inform data inspection, cleaning, and validation.
    • Article: EDA: Inspect, Clean, and Validate a Dataset
    • Project: EDA: Diagnosing Diabetes
  • Summarizing a Single Feature: Learn how to explore a single feature in a dataset using summary statistics and simple data visualizations.
    • Lesson: Data Summaries
    • Quiz: EDA: Data Summaries
    • Project: Exploring Student Data
  • Aggregates in Pandas: Learn how to use aggregate functions in pandas to calculate tables of summary statistics.
    • Lesson: Aggregates in Pandas
    • Quiz: Aggregates in Pandas
    • Project: A/B Testing for ShoeFly.com
  • Summarizing the Relationship between Two Features: Learn how to investigate whether there is an association between two variables.

    • Lesson: Associations: Quantitative and Categorical Variables
    • Lesson: Associations: Two Quantitative Variables
    • Lesson: Associations: Two Categorical Variables
    • Quiz: Associations between Variables
    • Project: NBA Trends
  • Advanced Data Visualization: Learn about advanced data visualization techniques for exploratory data analysis (EDA) in Python.
    • Article: Exploratory Data Analysis: Data Visualization
    • Article: Visualizing Multivariate Relationships
    • Article: Visualizing Time Series Data With Python
    • Article: Data Visualizations for Messy Data
    • Project: Airline Analysis
  • EDA for Machine Learning Models: Learn about exploratory data analysis techniques that are important prior to building a machine learning model.
    • Article: EDA Prior To Fitting a Regression Model
    • Article: EDA Prior to Fitting a Classification Model
    • Article: EDA Prior to Unsupervised Clustering

Taught by

Zoe Bachman

Reviews

4.5 rating at Codecademy based on 43 ratings

Start your review of Exploratory Data Analysis in Python

Go to class

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.