Course

Handling Missing Data

Learn how and when to tackle missing data with deletion, single imputation, linear interpolation, and multiple imputation techniques.

4.29 out of 5 stars
2,553 learners enrolled
  • Skill level

    Beginner
  • Time to complete

    1 hour
  • Certificate of completion

    Included with paid plans
  • Prerequisites

    3 courses

About this course

Nearly every dataset you’ll come across has missing data. So what are you going to do about it? This course will help you identify different types of missing data and how to address each using techniques in Python.

Syllabus

The platform

Hands-on learning

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Handling Missing Data course ratings and reviews

4.29 out of 5 stars
133 ratings
  1. 5 stars
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  3. 3 stars
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  5. 1 star
  • The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.
    Chris
    Codecademy Learner @ USA
  • I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.
    Rodrigo
    Codecademy Learner @ UK
  • Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.
    John-Andrew
    Codecademy Learner @ USA

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Frequently asked questions about Handling Missing Data

  • Nothing is perfect, and computers are no exception. Sometimes the data we collect is missing values for a given variable, which can skew analysis and results if not properly addressed.

Join over 50 million learners and start Handling Missing Data today!

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