The simplest way of loading data into R is probably using a comma-separated value (.csv) spreadsheet file, which can be downloaded from many data sources and loaded and saved in all spreadsheet software (such as Excel or LibreOffice). The read.table() command imports data of this type by specifying the separator as a comma, or there is a function specifically for .csv files, read.csv(), as shown in the following command:

> analyticsData <- read.table("~/example.csv", sep = ",")

Otherwise, you can use the following command:

> analyticsData <- read.csv("~/example.csv")

Note that unlike in other languages, R uses <- for assignment as well as =. Assignment can be made the other way using ->. The result of this is that y can be told to hold the value of 4 like this, y <- 4, or like this, 4 -> y. There are some other more advanced things that can be done with assignment in R, but don't worry about them now. Just write code using the assignment operator in the preceding example and you'll be just like the natives that you will come across on forums and blog posts.

Either of the preceding code examples will assign the contents of the Analytics.csv file to a dataframe named analyticsData, with the first row of the spreadsheet providing the variable names. A dataframe is a special type of object in R, which is designed to be useful for the storage and analysis of data.