Exploratory Data Analysis in Python
Learn how to use exploratory data analysis (EDA) techniques in Python to evaluate, summarize, and visualize your data.
Skill level
BeginnerTime to complete
Approx. 10 hoursCertificate of completion
Included with paid plansPrerequisites
None
About this course
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
5 lessons • 5 projects • 3 quizzesHands-on learning
Don’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this course
- Project
EDA: Diagnosing Diabetes
Inspect, clean, and validate a dataset on diabetes prevalence among females of Pima Indian heritage. - Project
Exploring Student Data
Summarize the features of a dataset about student performance at two different schools. - Project
A/B Testing for ShoeFly.com
Analyst the A/B test data from ShoeFly.com using aggregate measures.
Reviews from learners
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.
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Frequently asked questions about Exploratory Data Analysis in Python
You need to understand your data before you can put it to good use. Exploratory data analysis (or EDA) involves familiarizing yourself with a new dataset. Generally you’re just looking for a broad understanding and insights into possible patterns and relationships within the data.