基于因子条件在R中插入行

我正在尝试对值列运行变化率计算，但由于以下原因无法运行：

由于“重置”，每次换油后都会丢失一行

我缺乏根据条件插入行的R知识

这是我的实际数据帧

Before <- data.frame(
  Engine_ID = as.factor(c(1006,1006,1006,1006,1006,1006,1006)),
  Oil_Change = as.factor(c(1,0,1,1,0,0,0)),
  Value = c(5,6,3,7,9,11,12)
)

---

Before
df
Before$order如果您了解您需要做什么，我认为可能有很多方法。下面是一个方法，我可以根据我理解你需要做什么的方式来做。这可能是完成任务最低效的方式：

 library(dplyr); library(reshape2)
            newChange  <- mutate(Before, no = c(1:nrow(Before)), 
                                 changeRate = ifelse(as.numeric(as.character(Oil_Change)) > 0, 0,NA)) %>%
                          melt(., id=c('no', 'Engine_ID')) %>%
                          mutate(., no = ifelse(variable =='changeRate', no+0.5,no),
                                 variable = ifelse(variable =='changeRate', 'Value', as.character(variable))) %>%
                          reshape(., direction ='wide', idvar = c('no', 'Engine_ID'), timevar = 'variable') %>%
                          arrange(no) %>% subset(., !(is.na(value.Oil_Change) & is.na(value.Value)))
            names(newChange) <- gsub('value.', '', names(newChange)) 
newChange$no <- NULL 

库（dplyr）；图书馆（E2）
新更改（0,0,NA））%>%
熔体（，id=c（'no'，'Engine_id'））%>%
变异（，no=ifelse（变量=='changeRate'，no+0.5，no），
变量=ifelse（变量=='changeRate'，'Value'，as.character（变量）））%>%
重塑（，direction='wide'，idvar=c（'no'，'Engine_ID'），timevar='variable'）%>%
排列（否）%>%子集（，！（is.na（value.Oil_Change）和is.na（value.value）））
名称（换油）我不明白你是如何从之前和之后得到的，你用什么条件来决定在哪里插入这些新行？条件是：换油中的1表示将注入新油。所以数据显示，这个值从3到7。实际上是3比0比7。它只是没有在数据中正确地表示出来。因此，在每次换油后，我想直接插入一行额外的零。
df <- Before

# create a helper column
# which gives number of Oil_Change occurrence before the actual row
df$helper <- cumsum(as.integer(as.character(df$Oil_Change)))
# shift it, so that number changes AFTER the oilchange row
df$helper <- c(0, df$helper[1:(length(df$helper)-1)])

# split data frame by the helper row
dfl <- split(df, df$helper) # look at `dfl` content!

# construct to be added horizontal data row
to.be.added <- t(as.data.frame(c(1006, NA, 0, 0)))
# name it correctly
colnames(to.be.added) <- colnames(df)
rownames(to.be.added) <- 1

# add this list at the end of each sub-data frame
dfl.added <- lapply(dfl, function(df) rbind(df, to.be.added))

# join the sub data frames by rowbinding
res <- Reduce(rbind, dfl.added)

# properly name the rows
rownames(res) <- 1:nrow(res)
# remove helper column
res <- res[, -(ncol(res))] 

# voila!
res # remove last line if you don't want it
   Engine_ID Oil_Change Value
1       1006          1     5
2       1006       <NA>     0
3       1006          0     6
4       1006          1     3
5       1006       <NA>     0
6       1006          1     7
7       1006       <NA>     0
8       1006          0     9
9       1006          0    11
10      1006          0    12
11      1006       <NA>     0

Before$order <- 1:nrow(Before)

new <- Before[Before$Oil_Change == 1, ]
new$Oil_Change <- NA
new$Value <- 0

After <- rbind(Before, new)

After[order(After$order), ][ , -4]

   Engine_ID Oil_Change Value
1       1006          1     5
11      1006       <NA>     0
2       1006          0     6
3       1006          1     3
31      1006       <NA>     0
4       1006          1     7
41      1006       <NA>     0
5       1006          0     9
6       1006          0    11
7       1006          0    12

 library(dplyr); library(reshape2)
            newChange  <- mutate(Before, no = c(1:nrow(Before)), 
                                 changeRate = ifelse(as.numeric(as.character(Oil_Change)) > 0, 0,NA)) %>%
                          melt(., id=c('no', 'Engine_ID')) %>%
                          mutate(., no = ifelse(variable =='changeRate', no+0.5,no),
                                 variable = ifelse(variable =='changeRate', 'Value', as.character(variable))) %>%
                          reshape(., direction ='wide', idvar = c('no', 'Engine_ID'), timevar = 'variable') %>%
                          arrange(no) %>% subset(., !(is.na(value.Oil_Change) & is.na(value.Value)))
            names(newChange) <- gsub('value.', '', names(newChange)) 
newChange$no <- NULL