1. DATA MANAGEMENT MODULE: Getting Data Into and Out of R
STAT 4030 – Programming in R
DATA MANAGEMENT MODULE:
Getting Data Into and Out of R
Jennifer Lewis Priestley, Ph.D.
Kennesaw State University 1

2. DATA MANAGEMENT MODULE
Importing and Exporting
Imputting data directly into R
Creating, Adding and Dropping Variables
Assigning objects
Subsetting and Formatting
Working with SAS Files
Using SQL in R 2 2 2

3. Importing and Exporting: Data types
Scalar – a single value
Vectors – a single column (or row )of data
Example – a numeric vector containing test scores of students
Matrix – a collection of vectors but must all be of the same data type
Data frame – a special matrix that can contain both numeric and character columns.

4. The easiest way to add data to R is to code it in…
Importing and Exporting: Inputting Data in R
The easiest way to add data to R is to code it in…
names <- c("Bob","Gene","Valerie")
age <- c(30, 40, 19)
hometown <- c("Dallas, TX", "Little Rock, AR", "Dayton, OH")
Note: How are the categorical values in the vector “names” coded?
How are the numeric values in the vector “age” coded?

5. Importing and Exporting: reading data into R
c() – creates a column vector (like creating a variable for analysis)
read.csv – reads in a CSV file.
read.table – more generic function that can read in files with any delimiter, such as tab delimited.
read.fwf – reads in fixed record formats. 5

6. Importing and Exporting: reading data into R
In order to import data into R, we need to know how the file was created:
Excel
SAS
SPSS
Delimited
Fixed field or record 6

7. Easiest to save Excel as a CSV (comma delimited) file.
Importing and Exporting: Excel
Easiest to save Excel as a CSV (comma delimited) file.
Click File > Save As
On the next GUI, select “CSV” from the “save as type” option.
Use the read.csv function to get the data into R. 7

8. Importing and Exporting: CSV7

9. Importing and Exporting: CSV Files
widge <- read.csv("C:\\Path here\\WidgeOne.csv")
head(widge) 8

10. Importing and Exporting: Exporting data
Depending on what kind of file format you want to export back to, there are several options – delimited, fixed field or record or proprietary formats like .sas7bdat or .sav
names <- c("Bob","Gene","Valerie")
age <- c(30, 40, 19)
hometown <- c("Dallas, TX", "Little Rock, AR", "Dayton, OH")
customers<- data.frame(names,age,hometown)
write.table(customers, “pathhere", sep=",", col.names=NA, row.names = TRUE) 9