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Tidy Messy Data using tidyr in R
Coursera Project Network

Tidy Messy Data using tidyr in R

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Gain insight into a topic and learn the fundamentals.
4.6

(10 reviews)

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.6

(10 reviews)

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Tidy messy data using different tidyr functions

  • Create plots of tidy data using ggplot()

Details to know

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Assessments

1 assignment

Taught in English
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There is 1 module in this course

As data enthusiasts and professionals, our work often requires dealing with data in different forms. In particular, messy data can be a big challenge because the quality of your analysis largely depends on the quality of the data. This project-based course, "Tidy Messy Data using tidyr in R," is intended for beginner and intermediate R users with related experiences who are willing to advance their knowledge and skills. In this course, you will learn practical ways for data cleaning, reshaping, and transformation using R. You will learn how to use different tidyr functions like pivot_longer(), pivot_wider(), separate_rows(), separate(), and others to achieve the tidy data principles. By the end of this 2-hour-long project, you will get hands-on massaging data to put in the proper format. By extension, you will learn to create plots using ggplot(). This project-based course is a beginner to an intermediate-level course in R. Therefore, to get the most out of this project, it is essential to have a basic understanding of using R. Specifically, you should be able to load data into R and understand how the pipe function works. It will be helpful to complete my previous project titled "Data Manipulation with dplyr in R."

What's included

3 readings1 assignment1 ungraded lab1 plugin

Instructor

Arimoro Olayinka Imisioluwa
Coursera Project Network
26 Courses53,336 learners

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Recommended if you're interested in Data Analysis

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4.6

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Reviewed on Aug 20, 2023

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