Introduction to Importing Data in R

You should be comfortable with the basics of R, such as working with variables, vectors, and functions. Introduction to R is the only listed prerequisite.

R users who regularly receive data from external sources and want a reliable, efficient approach to loading it before analysis. It is relevant for analysts and data scientists working with flat files, Excel workbooks, or mixed data sources.

You will be able to import CSV and tab-delimited text files using base R and the readr package, Excel workbooks using readxl, and perform more advanced Excel operations such as adding, renaming, and removing sheets using XLConnect.

Each package has different strengths. Base R functions work without additional dependencies, readr and data.table are faster and more consistent for large flat files, and readxl and XLConnect offer progressively more control over Excel workbooks. The course helps you choose the right tool for each situation.

readxl is focused on reading Excel files quickly and cleanly. XLConnect goes further, letting you write data back to workbooks, add and remove sheets, and manipulate Excel files directly from R — making it useful when Excel is part of a shared or reproducible workflow.

The course has four chapters. Chapter 1 covers importing flat files with base R functions. Chapter 2 introduces readr and data.table for more efficient flat file imports. Chapter 3 covers reading Excel files with readxl. Chapter 4 uses XLConnect to read, write, and manage Excel workbooks from R.