Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Pluralsight

Merging Data Sources with R

via Pluralsight

Overview

Learn how to merge data with R. How do you merge values into vectors? How do you merge vectors into data frames? How do you join data frames? See how to use base R and dplyr to do left, right, and full outer joins with plenty of examples.

In your R data science projects, you need very often to work with data which is spread out across multiple data sources. For example, given two separate data sets on products and their sales, how can you merge them into a new data set? In this course, Merging Data Sources with R, you will gain the ability to merge data from different sources in a controlled way that enables you to keep only the data you need. First, you will learn to merge vectors, which includes using the paste() and append() methods. Next, you will discover how to join data sets with the merge() function, which includes left, inner, right and full outer joins, on data frames that can have one-to-one, one-to-many, or many-to-many relationships. Finally, you will explore how to join data sets with the dplyr package, which covers the previous joins plus anti and semi joins. When you are finished with this course, you will have the skills and knowledge of merging data from different sources, needed to do data wrangling with R.

Syllabus

  • Course Overview 1min
  • Managing Vectors 31mins
  • Joining Data Sets with the Merge() Function 31mins
  • Joining Data Sets with dplyr 24mins

Taught by

Dan Tofan

Reviews

5 rating at Pluralsight based on 16 ratings

Start your review of Merging Data Sources with R

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.