Good Afternoon,
I believe that my to the problem, the R has a more effective solution.
in place the use the loop
I have the following set of data, and needs to extract some sections.
user pos communications source v_destine
7 1 109 22 22
7 2 100 22 22
7 3 214 22 22
7 4 322 22 22
7 5 69920 22 161
7 6 68 161 97
7 7 196 97 97
7 8 427 97 22
7 9 460 22 22
7 10 307 22 22
7 11 9582 22 22
7 12 55428 22 22
7 13 9192 22 22
7 14 19 22 22
my idea is to arise when a value greater than 1000 communications able to
extract some data.
In the example data set, is valued at over 1000 in the position 11,12,13.
my idea is to get results like this:
user, sector, source, destine, count, average
7 1 22 22 4 186.25 #
(109+100+214+322)
7 2 161 97 1 68
7 2 97 97 1 196
7 2 97 22 1 427
7 2 22 22 2 383
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R extract parts
3 messages · Rui Barradas, MSousa
Hello,
my idea is to get results like this: user, sector, source, destine, count, average 7 1 22 22 4 186.25 # (109+100+214+322) 7 2 161 97 1 68 7 2 97 97 1 196 7 2 97 22 1 427 7 2 22 22 2 383
Your second column, 'sector', comes from where? What is it?
Without it, try this.
text="
user pos communications source v_destine
7 1 109 22 22
7 2 100 22 22
7 3 214 22 22
7 4 322 22 22
7 5 69920 22 161
7 6 68 161 97
7 7 196 97 97
7 8 427 97 22
7 9 460 22 22
7 10 307 22 22
7 11 9582 22 22
7 12 55428 22 22
7 13 9192 22 22
7 14 19 22 22
"
df1 <- read.table(textConnection(text), header=TRUE)
inx <- df1$comm > 1000
comm1000 <- cumsum(inx)
result <- split(df1[!inx, ], list(comm1000[!inx], df1$source[!inx],
df1$v_destine[!inx]))
result <- sapply(result, function(x) c(x$user[1], x$source[1],
x$v_destine[1], nrow(x), mean(x$comm)))
result <- na.exclude(t(result))
rownames(result) <- 1:nrow(result)
colnames(result) <- c("user", "source", "v_destine", "count", "average")
attr(result, "na.action") <- NULL
attr(result, "class") <- NULL
result
Hope this helps,
Rui Barradas
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Thank you,
Works perfectly.
When the column sector, is the value of lines in the example has six
sectors
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