Spring Cleaning Data: 6 of 6- Saving the Data

April 13, 2013
By

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With all the cleaning done, the only thing left to do is save the data to be analyzed, for future use, and I hope by others. The data I thought would be simple, but there were a few interesting twist, like the Primary Credit*, and using ifelse() to edit the districts.

I have included the product as well as the R-code in a single file for people to use and learn from. I would like to thanks all those who made comments, I find all of them helpful. Below are the links to the files generated and used in the series, and the r-code used to exporting and reloading the data.

List of files used and their links

#Export the data, csv and RData
setwd("C:/Users Defined/")
write.csv(dw, file='DiscountWindow.csv')
save(dw, file='DiscountWindow.RData')
 
#note when loading the data the envir= needs to be defined
#with larger files the RData is definately the way to go
#this file is small enough it does not matter
load('DiscountWindow.RData', envir=.GlobalEnv)
dw<-read.csv(file.choose(), header=T)

Previous Posts (Part 1Part 2Part 3Part 4, Part 5)

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