在不使用回圈的情況下替換資料幀的Na值

我有這個資料框：

我想創建一個包含設備列資料的新列，并將NA值替換為上面的框。我寫了這段代碼

DC<-df[order(df$MASK,df$TIMESTAMP),]
Equipement_Correct <- df$EQUIPMENT

Equipement_Correct <-ifelse(is.na(as.character(Equipement_Correct [2:nrow(DC)]))&as.character(DC$MASK[2:nrow(DC)])==as.character(DC$MASK[1:nrow(DC)-1])  & (as.character(DC$EVENT[2:nrow(DC)])=='decouple' | as.character(DC$EVENT[2:nrow(DC)])=='stateChange' |,
                                           as.character(Equipement_Correct [1:nrow(DC)-1]),
                                           as.character(Equipement_Correct [2:nrow(DC)]))
Equipement_Correct <-c(NA,Equipement_Correct )


dfOut<-data.frame(DC,Equipement_Correct)

我得到：

我想得到：

通過在我的代碼上使用回圈，我設法獲得了想要的結果，但我不想使用回圈，因為我處理了數百萬行，

for (i in 1:5) {
Equipement_Correct <-ifelse(is.na(as.character(Equipement_Correct [2:nrow(DC)]))&as.character(DC$MASK[2:nrow(DC)])==as.character(DC$MASK[1:nrow(DC)-1])  & (as.character(DC$EVENT[2:nrow(DC)])=='decouple' | as.character(DC$EVENT[2:nrow(DC)])=='stateChange' |,
                                           as.character(Equipement_Correct [1:nrow(DC)-1]),
                                           as.character(Equipement_Correct [2:nrow(DC)]))
Equipement_Correct <-c(NA,Equipement_Correct )
}

有沒有辦法不使用回圈？

uj5u.com熱心網友回復：

假設在資料庫中的事件條目是有序和完整如圖所示，你可以強制對factor和背部as.integer，在這種情況下，給出了EVENT_N與c(1, 2, 3, 4)重復的“永遠”。現在，您可以利用cumsum我們在 modulo 的零值上計算的%% 4，即結果 的累積和TRUE。我們需要減去- 1以獲得正確的滯后。

lv <- c("enterEquipment", "Decouple", "stateChange", "leaveEquipment")

dat <- within(dat, {
  EVENT_N <- as.integer(factor(EVENT, levels=lv))
  Equipement_Correct <- paste0('L', cumsum(EVENT_N %% 4 - 1 == 0))
  rm(EVENT_N)  ## removes temporary column
})
dat
#         DATE          EVENT EQUIPMENT MASK Equipement_Correct
# 1 2021/12/08 enterEquipment        L1    a                 L1
# 2 2021/12/09       Decouple      <NA>    a                 L1
# 3 2021/12/09    stateChange      <NA>    a                 L1
# 4 2021/12/10 leaveEquipment        L1    a                 L1
# 5 2021/12/10 enterEquipment        L2    b                 L2
# 6 2021/12/11       Decouple      <NA>    b                 L2
# 7 2021/12/11    stateChange      <NA>    b                 L2
# 8 2021/12/11 leaveEquipment        L1    b                 L2

也許使用Key 資料框而不是factor.

K <- data.frame(matrix(c("enterEquipment", "Decouple", "stateChange", 
                         "leaveEquipment", 1:4), ncol=2)) |> 
  type.convert(as.is=TRUE)

within(dat, {
  Equipement_Correct <- 
    paste0('L', cumsum(K[match(EVENT, K[, 1]), 2] %% 4 - 1 == 0))
})

資料：

dat <- structure(list(DATE = c("2021/12/08", "2021/12/09", "2021/12/09", 
"2021/12/10", "2021/12/10", "2021/12/11", "2021/12/11", "2021/12/11"
), EVENT = c("enterEquipment", "Decouple", "stateChange", "leaveEquipment", 
"enterEquipment", "Decouple", "stateChange", "leaveEquipment"
), EQUIPMENT = c("L1", NA, NA, "L1", "L2", NA, NA, "L1"), MASK = c("a", 
"a", "a", "a", "b", "b", "b", "b"), Equipement_Correct = c("L1", 
"L1", NA, "L1", "L1", "L2", NA, "L2")), class = "data.frame", row.names = c(NA, 
-8L))

uj5u.com熱心網友回復：

使用這個包'zoo'，你可以獲得函式na.locf（最后一次觀察結轉）

install.packages(zoo)
library(zoo)

data$EQUIPMENT <- na.locf(data$EQUIPMENT)

eg: > library(zoo)
> data <- data.frame(New= c("L1",NA,NA,"L2",NA,"L3",NA,NA), old = 1:8)
> data
   New old
1   L1   1
2 <NA>   2
3 <NA>   3
4   L2   4
5 <NA>   5
6   L3   6
7 <NA>   7
8 <NA>   8
> data$New <- na.locf(data$New)
> data
  New old
1  L1   1
2  L1   2
3  L1   3
4  L2   4
5  L2   5
6  L3   6
7  L3   7
8  L3   8

uj5u.com熱心網友回復：

您也可以tidyr::fill為此目的使用：

library(tidyr)

df %>%
  fill(Equipement_Correct, .direction = "down")

        DATE          EVENT EQUIPMENT MASK Equipement_Correct
1 2021/12/08 enterEquipment        L1    a                 L1
2 2021/12/09       Decouple      <NA>    a                 L1
3 2021/12/09    stateChange      <NA>    a                 L1
4 2021/12/10 leaveEquipment        L1    a                 L1
5 2021/12/10 enterEquipment        L2    b                 L1
6 2021/12/11       Decouple      <NA>    b                 L2
7 2021/12/11    stateChange      <NA>    b                 L2
8 2021/12/11 leaveEquipment        L1    b                 L2

標籤：r

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