Course overview

Data cleaning is a necessary skill for anyone who wants to work in a data-related field.

You’ll start this course by learning how to identify data cleaning needs prior to analysis, how to use functionals for data cleaning, how to practice string manipulation, how to work with relational data, and how to reshape data using tools from the tidyverse. You’ll create correlation matrices to identify trends in your data, and then you’ll then learn how to deal with missing values in your dataset.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. At the end of the course, you’ll work on a guided project to analyze parents’, students’, and teachers’ perceptions of NYC schools. You’ll learn to work with survey data — specifically how to import, simplify, and reshape the data. You’ll also learn about R Notebooks and how you can use them to showcase your work.

Key skills

    • Manipulating DataFrames with new tools
    • Resolving missing data
    • Joining DataFrames
    • Reshaping data using the tidyr package

Course outline

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Projects in this course

The Dataquest guarantee

  • Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our course, you'll master data skills and grow your career.

  • We believe so strongly in our courses that we offer a full satisfaction guarantee. If you complete a career course on Dataquest and aren't satisfied with your outcome, we'll give you a refund.

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Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your course certification

Impress employers by completing a capstone project and certifying it with an expert review.

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