CODEWITHSUNDEEP
raggregatevectorization
momo96
momo96

Reputation: 53

Aggregate rows under certain conditions using aggregate() function with R, without using dplyr

I want to aggregate rows in my table under certain conditions. For example I have :

x <- data.frame("id"=c("T","T","R","R"),"value"=c(10,-5,10,-5),"level"=c(3,2,1,2))
print(x)

My condition is : for the same "id" if the level of a negative value is lower than the level of the positive value, then I can aggregate through summing values. So I get :

x <- data.frame("id"=c("T","R","R"),"value"=c(5,10,-5))
print(x)

Can I do this using aggregate() fucntion ?

Upvotes: 1

Views: 59

Answers (2)

r.user.05apr
r.user.05apr

Reputation: 5456

Or: 

x <- data.frame("id"=c("T","T","R","R"),"value"=c(10,-5,10,-5),"level"=c(3,2,1,2))

lookup_vec <- setNames(x[sign(x$value) == 1, ]$level,
                       as.character(x[sign(x$value) == 1, ]$id))
x$level_plus <- lookup_vec[as.character(x$id)]
x$level_plus <- ifelse(x$level_plus >= x$level, x$level_plus, x$level)
aggregate(value ~ id + level_plus, x, sum)[c("id", "value")]
# id value
# 1  R    10
# 2  R    -5
# 3  T     5

Upvotes: 1

jay.sf
jay.sf

Reputation: 72593

You could use by.

do.call(rbind, by(x, x$id, function(x) {i <- cbind(x, d=c(1, diff(x[, 3]))); i[i$d > 0, 1:2]}))
#   id value
# 1  T     5
# 2  R    10
# 3  R    -5

Upvotes: 0

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