Overview Section
So far in our lessons, we've mostly entered our data direclty into R or used built-in data sets that are part of R. This won't take us very far for real work; to really use R for data analysis we must get data into R! We'll use Chapter 8 in Essential R.
Objectives
Upon completion of this lesson, you should be able to:
- Prepare a text file (.txt or .csv) for import into R
- Import the data using the function
read.table() - Recognize and fix the most common problems that cause errors when importing data
Data and R Code Files Section
The R code file and data files for this lesson can be found on the Essential R - Notes on learning R page.
The following data files should be in the "Data" folder in your "Essential R" folder; or you can save them to your working directory.
W101-2010.xls (Excel file) and W101-2010.csv (text file made from the Excel file). The example text files are: Ex1.txt, Ex2.txt, Ex3.txt, and Ex3.csv. The data file required for Exercise 2 is here: StatesData.xls.
Note! The videos don't cover the use of the "Import Dataset" dialog in the Environment browser pane in RStudio, but it is discussed in Chapter 8 of EssentialR. Do note that the current version of RStudio have updated the import data dialog to use the package
readr. This replaces read.csv() with read_csv(). This will read in your data but may convert some of the variables differently than read.csv() would do. (read_csv() will create a "tibble", which is subtly different from a data.frame). My suggestion to avoid the confusion is to edit the code that rstudio wrote in your console - replace read_csv() with read.csv and rerun the code - you should be fine.