In the frame date below, I want the days that have no gain information to be repeated based on the last information collected. For example from day 2 to day 15 the gain will be 0.97 and day 79 to 86 of 0.45 How can I do this in R?
Dia Ganho
2 0.97
16 0.95
23 1.03
24 0.99
30 1.03
37 1.01
44 1.11
51 1.04
58 1.31
65 1.17
72 1.09
79 0.45
86 The zoo package contains the na.locf function that does exactly what you need. According to its description, it is a generic function that replaces every NA with the most recent non-NA previous. Follow the code using this function
df <- data.frame(
Dia = c(2,16,23,24,30,37,44,51,58,65,72,79,86),
Ganho = c(.97,.95,1.03,.99,1.03,1.01,1.11,1.04,1.31,1.17,1.09,.45,NA)
)
temp <- expand.grid(Dia = seq(from = min(df$Dia), to = max(df$Dia), by = 1))
df <- merge(df, temp, all = T)
library(zoo)
df <- na.locf(df)
Try the code below. I think that's what you want.
resultado <- lapply(seq_along(dados$Dia)[-nrow(dados)], function(i) {
data.frame(Dia = seq(dados$Dia[i], dados$Dia[i + 1] - 1), Ganho = dados$Ganho[i])
})
resultado <- do.call(rbind, resultado)
resultado <- rbind(resultado, data.frame(Dia = dados$Dia[nrow(dados)],
Ganho = resultado$Ganho[nrow(resultado)]))
resultado
DATA.
dados <-
structure(list(Dia = c(2L, 16L, 23L, 24L, 30L, 37L, 44L, 51L,
58L, 65L, 72L, 79L, 86L), Ganho = c(0.97, 0.95, 1.03, 0.99, 1.03,
1.01, 1.11, 1.04, 1.31, 1.17, 1.09, 0.45, NA)), .Names = c("Dia",
"Ganho"), class = "data.frame", row.names = c(NA, -13L))