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corr.R
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source("dataloader.R")
corr <- function(directory, threshold = 0) {
## 'directory' is a character vector of length 1 indicating
## the location of the CSV files
## 'threshold' is a numeric vector of length 1 indicating the
## number of completely observed observations (on all
## variables) required to compute the correlation between
## nitrate and sulfate; the default is 0
## Return a numeric vector of correlations
n.files = length(list.files(directory))
df = complete(directory,
id=1:n.files)
df.subset = df[df$nobs > threshold,]
files = sprintf("%s/%03d.csv", directory, df.subset$id)
data.list = lapply(files, read.csv)
data.df = do.call(rbind.data.frame, data.list)
require(plyr)
data.corr = ddply(data.df,
"ID",
summarize,
corr=cor(sulfate,
nitrate,
use="complete.obs"))
data.corr$corr
}