Skip to main content
HomeRProgramming with dplyr

Programming with dplyr

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Start Course for Free
4 Hours15 Videos47 Exercises
2,420 LearnersTrophyStatement of Accomplishment

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies


Course Description

The tidyverse includes a tremendous set of packages that make working with data simple and fast. But have you ever tried to put dplyr functions inside functions and been stuck with strange errors or unexpected results? Those errors were likely due to tidy evaluation, which requires a little extra work to handle. In Programming with dplyr, you’ll be equipped with strategies for solving these errors via the rlang package. You’ll also learn other techniques for programming with dplyr using data from the World Bank and International Monetary Fund to analyze worldwide trends throughout. You’ll be a tidyverse function writing ninja by the end of the course!
  1. 1

    Hold Your Selected Leaders Accountable

    Free

    In this chapter, you'll revisit dplyr pipelines and enhance your column selection skills with helper functions and regular expressions.

    Play Chapter Now
    Be fruitful and dplyr
    50 xp
    select() vs. filter()
    50 xp
    A great selection
    100 xp
    Mutation necessary
    100 xp
    Lending a helper hand
    50 xp
    Don't get me started
    100 xp
    See how that ended up
    100 xp
    Finding our perfect match
    50 xp
    Contain-ted love
    100 xp
    Looking for matches
    100 xp

Datasets

International Monetary Fund (IMF)World Bank

Collaborators

Collaborator's avatar
Maggie Matsui
Collaborator's avatar
Amy Peterson
Collaborator's avatar
James Chapman
Dr. Chester Ismay HeadshotDr. Chester Ismay

Educator, Data Scientist, and R/Python Consultant

Chester enjoys helping others get into data science, figuring out how to best practice and improve on their skills, and working as a part-time consultant on R and Python programming projects. He is co-author of "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at moderndive.com and for purchase from CRC Press. He likes leading education and data science teams with the goal of improving best practices based on data from the learning sciences.
See More

What do other learners have to say?

Join over 13 million learners and start Programming with dplyr today!

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.