Filip is the passionate developer behind several of DataCamp's interactive courses, covering both R and Python. Under the motto 'Eat your own dog food', he has used the techniques DataCamp teaches its students to perform data analysis for DataCamp. Filip holds degrees in Electrical Engineering and Artificial Intelligence.
Importing data into R to start your analyses—it should be the easiest step. Unfortunately, this is almost never the case. Data come in all sorts of formats, ranging from CSV and text files and statistical software files to databases and HTML data. Knowing which approach to use is key to getting started with the actual analysis.
In this course, you will get started with learning how to read CSV and text files in R. You will then cover the readr and data.table packages to easily and efficiently import flat file data. After that you will learn how to read XLS files in R using readxl and gdata.
Lots of data comes in the form of flat files: simple tabular text files. Learn how to import all common formats of flat file data with base R functions.
Next to base R, there are also dedicated packages to easily and efficiently import flat file data. We'll talk about two such packages: readr and data.table.
Excel is a very widely used data analysis tool. If you prefer to do your analyses in R, though, you'll need an understanding of importing CSV data into R. This chapter will show you how to use readxl and gdata to do so.
Next to importing data from Excel, you can take things one step further with XLConnect. Learn all about it and bridge the gap between R and Excel!