While SAS language has a beautifully designed ODS (Output Delivery System) for saving output from certain analysis in excel files (and html and others), in R one can simply use the object, put it in a write.table and save it a csv file using the file parameter within write.table.
As a business analytics consultant, the output from a Proc Means, Proc Freq (SAS) or a summary/describe/table command (in R) is to be presented as a final report. Copying and pasting is not feasible especially for large amounts of text, or remote computers.
Using the following we can simple save the output in R
> getwd()
[1] “C:/Users/KUs/Desktop/Ajay”
> setwd(“C:\Users\KUs\Desktop”)
#We shifted the directory, so we can save output without putting the entire path again and again for each step.
#I have found the summary command most useful for initial analysis and final display (particularly during the data munging step)
nams=summary(ajay)
# I assigned a new object to the analysis step (summary), it could also be summary,names, describe (HMisc) or table (for frequency analysis),
> write.table(nams,sep=”,”,file=”output.csv”)
Note: This is for basic beginners in R using it for business analytics dealing with large number of variables.
pps: Note
If you have a large number of files in a local directory to be read in R, you can avoid typing the entire path again and again by modifying the file parameter in the read.table and changing the working directory to that folder
setwd(“C:/Users/KUs/Desktop/”)
ajayt1=read.table(file=”test1.csv”,sep=”,”,header=T)
ajayt2=read.table(file=”test2.csv”,sep=”,”,header=T)
and so on…
maybe there is a better approach somewhere on Stack Overflow or R help, but this will work just as well.
you can then merge the objects created ajayt1 and ajayt2… (to be continued)
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