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!
This chapter will show you how to perform simple joins that will enable you to combine information spread across multiple tables.
In this chapter you will perform joins using the data.table syntax, set and view data.table keys, and perform anti-joins.
This chapter will discuss common problems and errors encountered when performing data.table joins and show you how to troubleshoot and avoid them.
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.
PrerequisitesData Manipulation with data.table in R
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