Joining Data with data.table in R
This course will show you how to combine and merge datasets with data.table.
- 4 hours
- 13 Videos
- 47 Exercises
- 4,384 Participants
- 3,950 XP
Create Your Free Account
By pressing Continue you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.
Loved by learners at thousands of top companies:
Course Description
In the real world, data sets typically come split across many tables while most data analysis functions in R are designed to work with single tables of data. In this course, you'll learn how to effectively combine data sets into single tables using data.table. You'll learn how to add columns from one table to another table, how to filter a table based on observations in another table, and how to identify records across multiple tables matching complex criteria. Along the way, you'll learn how to troubleshoot failed join operations and best practices for working with complex data sets. After completing this course you'll be well on your way to be a data.table master!
-
1
Joining Multiple data.tables
FreeThis chapter will show you how to perform simple joins that will enable you to combine information spread across multiple tables.
-
Diagnosing and Fixing Common Join Problems
This chapter will discuss common problems and errors encountered when performing data.table joins and show you how to troubleshoot and avoid them.
-
Joins Using data.table Syntax
In this chapter you will perform joins using the data.table syntax, set and view data.table keys, and perform anti-joins.
-
Concatenating and Reshaping data.tables
In the last chapter of this course you'll learn how to concatenate observations from multiple tables together, how to identify observations present in one table but not another, and how to reshape tables between long and wide formats.
-
1
Joining Multiple data.tables
FreeThis chapter will show you how to perform simple joins that will enable you to combine information spread across multiple tables.
-
Joins Using data.table Syntax
In this chapter you will perform joins using the data.table syntax, set and view data.table keys, and perform anti-joins.
-
Diagnosing and Fixing Common Join Problems
This chapter will discuss common problems and errors encountered when performing data.table joins and show you how to troubleshoot and avoid them.
-
Concatenating and Reshaping data.tables
In the last chapter of this course you'll learn how to concatenate observations from multiple tables together, how to identify observations present in one table but not another, and how to reshape tables between long and wide formats.
What do other learners have to say?
“I've used other sites, but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyd's Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics @ USAA
Scott Ritchie
Postdoctoral Researcher in Systems Genomics
Scott Ritchie is a Post-doctoral Researcher in the field of systems genomics. He applies and develops tools to analyse genetic and molecular data in population studies of common diseases. He is a daily user of R and the data.table package. He has contributed to development of the data.table package and to course material used by Software Carpentry. He holds an MSc in Bioinformatics and a PhD in systems biology.
See MoreCollaborators
-
Sumedh Panchadhar
-
Eunkyung Park
-
Richie Cotton