Excel

Save from Excel to disk as text

• clean the data sheet you want to export until you have a simple table
• save this sheet as Text (CSV) with some defined delimiter (e.g. “tab”" or “blank”“)

Load from disk into R

sets <- read.table("set1_set2.csv", header=TRUE)    # read from disk and store in variable "sets"
class(sets)

## [1] "data.frame"

dim(sets)

## [1] 300   2

head(sets)

##        set1     set2
## 1 1.8329159 3.730824
## 2 0.5397876 5.064780
## 3 1.2170686 5.958580
## 4 1.3883328 2.029921
## 5 1.7145705 2.378172
## 6 0.8423617 1.399623

Now you can run the analysis on that data:

colMeans(sets)  # mean value of each column

##      set1      set2 
## 0.8987499 3.9624399

t.test(sets[,1], sets[,2])

## 
##  Welch Two Sample t-test
## 
## data:  sets[, 1] and sets[, 2]
## t = -28.436, df = 527.39, p-value < 2.2e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.275339 -2.852041
## sample estimates:
## mean of x mean of y 
## 0.8987499 3.9624399

Export from R to Excel

If the data were changed, the data frame can be written to Excel

• install.packages(“WriteXLS”)
• “WriteXLS” package needs the Perl module “CSV_XS.pm” to be installed

library(WriteXLS)
WriteXLS("sets", ExcelFileName="new.xls", SheetNames=c("new.sheet"), row.names=TRUE)
file.exists("new.xls")

## [1] TRUE