I need to calculate the maximum consumption value based on the previous values every time I loop the consumption data. For example on day 4, the maximum consumption would be calculated from day 1 to 4.
Follow the code I thought, but I do not know how it can be calculated
Maxconsumo<-c()
for (i in 1:length(Consumo)) {
Maxconsumo <- .........
}
Dia Consumo
1 245
2 256
3 300
4 450
5 245
6 256
7 300
8 450
Maxconsumo<-c()
Dia = 1:8
Consumo = c(245, 256, 300, 450, 245, 256, 300, 450)
data <- data.frame(Dia, Consumo)
for (i in 1:length(Consumo)) {
Maxconsumo[i] <- max(data$Consumo[1:i])
}
Maxconsumo
# [1] 245 256 300 450 450 450 450 450
If you want a function similar to cumsum , but calculating the cumulative maximum, here it goes, but I used a different name than yours to be consistent with% base%.
cummax <- function(x){
x[is.na(x)] <- -Inf
m <- numeric(length(x))
m[1] <- x[1]
for(i in seq_along(x)[-1]){
m[i] <- if(x[i] > m[i - 1]) x[i] else m[i - 1]
}
m
}
cummax(dados$Consumo)
#[1] 245 256 300 450 450 450 450 450
DATA.
dados <-
structure(list(Dia = 1:8, Consumo = c(245, 256, 300, 450, 245,
256, 300, 450)), .Names = c("Dia", "Consumo"), row.names = c(NA,
-8L), class = "data.frame")
EDITIONS.
After seeing the answer from Willian Vieira I edited my answer with a new R table. I do not know why, when I read the OP table I did not read it well.