Working with Data in the Tidyverse

Learn to work with data using tools from the tidyverse, and master the important skills of taming and tidying your data.

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4 Hours17 Videos56 Exercises24,208 Learners
4500 XP

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Course Description

In this course, you'll learn to work with data using tools from the tidyverse in R. By data, we mean your own data, other people's data, messy data, big data, small data - any data with rows and columns that comes your way! By work, we mean doing most of the things that sound hard to do with R, and that need to happen before you can analyze or visualize your data. But work doesn't mean that it is not fun - you will see why so many people love working in the tidyverse as you learn how to explore, tame, tidy, and transform your data. Throughout this course, you'll work with data from a popular television baking competition called "The Great British Bake Off."

  1. 1

    Explore your data

    Free

    You will start this course by learning how to read data into R. We'll begin with the readr package, and use it to read in data files organized in rows and columns. In the rest of the chapter, you'll learn how to explore your data using tools to help you view, summarize, and count values effectively. You'll see how each of these steps gives you more insights into your data.

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    Import your data
    50 xp
    Read a CSV file
    100 xp
    Assign missing values
    100 xp
    Know your data
    50 xp
    Arrange and glimpse
    50 xp
    Summarize your data
    100 xp
    Know your variable types
    50 xp
    Count with your data
    50 xp
    Distinct and count
    100 xp
    Count episodes
    100 xp
    Count bakers
    100 xp
    Plot counts
    100 xp

In the following tracks

Importing & Cleaning Data

Collaborators

Yashas RoyChester IsmayBenjamin Feder
Alison Hill Headshot

Alison Hill

Professor and Data Scientist

Alison is an Associate Professor of Pediatrics at Oregon Health & Science University (OHSU) in Portland, Oregon, and the Assistant Director of OHSU’s Center for Spoken Language Understanding, home to the Computer Science graduate education program. She has studied health-related applications of Natural Language Processing-based methods, with a focus on pediatric populations with developmental disabilities like Autism Spectrum Disorders. Alison is also an experienced educator, with peer- and student-nominated awards for teaching. She teaches graduate-level data science courses on Statistics and Data Visualization using R.
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Decision Science Analytics, USAA