A good on line tutorial for data I/O is in https://www.datacamp.com/community/tutorials/r-data-import-tutorial.

Direct Data Entry

When the data set is not large, it can be typed in. Examples are

• x<-1.5 # assign 1.5to x
• ar<-c(1.2,2.8,5.3) #c is function creating a vector
• mx = matrix(c(2, 4, 3, 1, 5, 7),nrow=3,ncol=2) # mx[[2,1],[4,5],[3,7]]
• mx = matrix(c(2, 4, 3, 1, 5, 7),ncol=3,nrow=2) # mx[[2,3,5],[4,1,7]]

Output on the console

There are 2 options

• type the variable name and return will display the data
• print(x)

Input from Clipboard

Contents on the consol can be marked and copied to clipboard by ctrl+c, and contents in the clipboard can be copied to the console bu ctrl+v

However, to paste the content of the clipboard into a variable to be used in R, or to copy a set of results in a variable to the clipboard, is actually quite complicated for R, and I avoid using it. for those who wantsto use clipboard, advice is available on the www in https://www.dummies.com/programming/r/how-to-use-the-clipboard-to-copy-and-paste-data-in-r/

Directory

By default, R assumes the file is in the same directory as the program. Two commands allows you to find and set the directory

• getwd() #returns the current directory
• setwd("MyDirectory") # sets the directory to MyDirectory

Read from text files

• mx <- read.table("MyInputFile.txt",header = FALSE)
  The content from the file MyInputFile.txt will be read into the matrix ms
  The default setting for header is TRUE, meaning that the first row contains the names of the columns
  The columns are assumed to be separated by white spaces
• mx <- read.table("MyInputFile.txt", header = FALSE, sep=s)
  The content from the file MyInputFile.txt will be read into the matrix ms
  The default setting for header is TRUE, meaning that the first row contains the names of the columns
  The columns are separated by s any separator, common ones are "," or ";" or "\t" or " "
• mx <- read.csv("MyInputFile.txt", header = FALSE)
  the same as mx <- read.table("MyInputFile.txt", header = FALSE, sep=",")
• mx <- read.csv2("MyInputFile.txt", header = FALSE)
  the same as mx <- read.table("MyInputFile.txt", header = FALSE, sep=";")
• mx<- read.delim("MyInputFile.txt", header = FALSE, sep="#")
  this is used when the delimiter is other then "," or ";" or "\t" or " "

Write to text files

• write.table(mydata, "mydata.txt", sep="\t")
• write.table(mydata, "mydata.csv", sep=",")

Access excel resources

These must preceed any command using excel files

install.packages("XLConnect")
library('XLConnect')

Read from excel files to a variable in R

There are a number of commands and options. For simplicity I use the following

mydata = readWorksheetFromFile("MyInputExcelFile.xlsx", sheet="MySheet")
mydata = readWorksheetFromFile("MyInputExcelFile.xlsx", sheet=1)

MyInputExcelFile.xlsx is the excel file, the first row contains the names of the columns
if more than 1 sheet exists in the excel file, the sheet accessed can be chosen by the number or the name of the sheet. MyData is the matrix of data to be used in R.

Save contents of a variable in R to excel files

It takes 4 steps, create a workbook, any number of (create a worksheet, write to the worksheet), and save the workbook

MyWorkbook <- loadWorkbook("MyOutputExcelFile.xlsx", create = TRUE) # creates a workbook MyWorkbook
createSheet(MyWorkbook, name = "MySheet1") # creates a worksheet MySheet1 in MyWorkbook
writeWorksheet(MyWorkbook, Mycontent, sheet = "MySheet1", startRow = 1, startCol = 1) # put content in variable MyContent into MySheet1, starting in row 1 and col 1 (A)
saveWorkbook(MyWorkbook) # save MyWorkbook as an excelfile MyOutputExcelFile.xlsx

In some procedures, the input are more complexthan a single variable. For example, logistic regression required a matrix with headers (first row with names of columns). Also, the output can also be a procedure which looks like text, but is actually a subroutine that creates texts.

Codes to convert direct entry to a dataframe so it can be used for plotting are as follows

Input = "v1\tv2\n1\t2\n3\t4\n5\t6\n"
myplotData = read.table(textConnection(Input),header=TRUE)
plot(x   = myplotData$v1,
     y   = myplotData$v2,
     pch = 16,
     xlab = "v1",
     ylab = "v2")

Note: Input is a command to accept an input table and myplotData is the name created to represent the data

Codes to convert a function that outputs results into text that can be copied directly into a fileare as follows

fit <- a procedure such as logistic regression
capture.output(summary(fit), file = "MyOutputTextFile.txt")