Oftentimes, you would import data into R from a previously saved file.
Importing data files using the Script Editor:
When importing data into R, save it as an object and give it a name using the <- assignment operator.
To import a tab delimited file, write the code: tab_data <- read.table("filelocation/Intro To R/datafile.txt", sep = "")
To import a comma delimited file, write the code: csv_data <- read.csv("filelocation/Intro To R/datafile.csv", sep = ",")
Codes for other file types and functions/packages to ‘read’ in the data, ordered by usage popularity:
Type of Data | File Extension | R Code/Packages |
Tabular data | .CSV | read_csv() function from the readr package |
Tabular data | .TSV | read.table() function from the readr package |
Text | .TXT |
readLines() function OR read_lines() function from the readr package |
Excel | .XLSX | read.xlsx() from the xlsx package |
Google sheets | Google URL or Sheet ID | read_sheet() from the googlesheets4 package |
SPSS statistical program file | .SAS7BDAT or .SAS7BCAT | read_sas() from the haven package |
SAS statistical program file | .SAV | read_sav() from the haven package |
Stata statistical program file | .DTA | read_dta() from the haven package |
MySQL database | MySQL database files | dbConnect() from the RMySQL package |
Fixed-width text file | .TXT | read.fwf() from the utils package |
Importing data files using RStudio functions:
To load data into Posit Cloud, first upload the data set in the ‘Files’ pane. Upload the file into your ‘cloud/project’ folder.
In RStudio, click ‘Import Dataset’ in the top right Environment pane in your working session. Select options to import from Text, Excel, SPSS, SAS, or Stata files. Assign a short descriptive 'Name' to the data set.