Stropharia wrote:
# ----------------------------------------START
R-CODE-----------------------------------
filenames <- Sys.glob("/Users/Desktop/Test/*.csv") # get names of files to
process # use * to get all
variables <- data.frame(1:length(filenames)) # preallocate assuming multiple
values from each file # creates a dataframe with the same length of rows as
the number of .csv files to process
for (i in seq_along(filenames)){
input <- read.csv(filenames[i], header=TRUE, na.strings="NA")
data.frame("input")
attach(input)
result.A <- x[2]*y[1]
result.B <- y[2]-x[1]
result.C <- x[3]+y[1]
results <- c(result.A, result.B, result.C) # concatenate result vectors
variables[i] <- results
}
variables <- as.data.frame(t(as.matrix(variables))) # turn result vectors
into a matrix, then transpose it and output as a data frame
# add column and row names
c.names <- c("ResultA", "ResultB", "ResultC") # set names for result vectors
colnames(variables) <- c.names
rownames(variables) <- filenames
# export to csv file
write.csv(variables, file="/Users/Desktop/Test.csv")
# ----------------------------------------END
R-CODE-----------------------------------
I think something like this should work better:
docalc <- function(thisfile){
input <- read.csv(filenames[i], header=TRUE, na.strings="NA")
attach(input)
result.A <- x[2]*y[1]
result.B <- y[2]-x[1]
result.C <- x[3]+y[1]
results <- c(result.A, result.B, result.C) # concatenate result vectors
names(results) <- c("ResultA", "ResultB", "ResultC") return(results)
}
variables <- sapply(filenames,docalc)
--
Levi Waldron
post-doctoral fellow
Jurisica Lab, Ontario Cancer Institute
Division of Signaling Biology
IBM Life Sciences Discovery Centre
TMDT 9-304D
101 College Street
Toronto, Ontario M5G 1L7
(416)581-7453
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