数据框1：
Item LC1 LC2 LC3
8T4121 MW92 OY01 RM11
数据框2：
Item LC custfcst
8T4121 MW92 10
8T4121 OY01 12
8T4121 RM11 10
AB7654 MW92 20
AB7654 WK14 10
AB7654 RM11 8
数据框3：
Item LC ToLC Rolledfcst
8T4121 MW92 OY01 22
8T4121 OY01 RM11 10
AB7654 MW92 WK14 30
AB7654 WK14 RM11 12
数据框4：
Item LC Safetystock(SS) X
8T4121 MW92 15 .25
8T4121 OY01 7 .25
8T4121 RM11 5 .25
AB7654 MW92 30 .25
AB7654 WK14 8 .25
AB7654 RM11 20 .25
输出：这是我在数据框1中将单行作为输入时的输出
Item LC xprcnt remainingss prcntvalue share SSNew `Leftover`
1 8T4121 MW92 3.75 11.25 0.3125000 3.515625 7.265625 7.734375
2 8T4121 OY01 1.75 5.25 0.5454545 2.863636 4.613636 2.386364
3 8T4121 RM11 NA NA NA NA NA NA
但是当我在数据帧1中接受多于1行作为输入时，它没有提供所需的输出。有人可以帮我吗？
数据框1：
Item LC1 LC2 LC3
8T4121 MW92 OY01 RM11
AB7654 MW92 WK14 RM11
代码：
library(plyr)
library(dplyr)
library(igraph)
library(data.table)
library(magrittr)
library(tidyr)
lctolc <- read.csv("LCtoLC.csv") #DF to get DF1
custfcst <- read.csv("custfcst.csv") #DF2
rolledfcst <- read.csv("rolledfcst.csv") #DF3
safetystock <- read.csv("safetystock.csv") #DF4
bodlane <- lapply(
lapply(split(lctolc, lctolc$Item), function(x) graph.data.frame(x[, 2:3])),
function(x) lapply(
all_simple_paths(x, from = V(x)[degree(x, mode = "in") == 0],
to = V(x)[degree(x, mode = "out") == 0]),
function(y) as.data.table(t(names(y))) %>% setnames(paste0("LC", seq_along(.)))
) %>% rbindlist(fill = TRUE)
) %>% rbindlist(fill = TRUE, idcol = "Item")
distributn <- bodlane %>%
as_tibble() %>%
gather(key = LC_ref, value = LC, - Item) %>%
left_join(select(custfcst, -Item), by = "LC") %>%
left_join(select(rolledfcst, -Item), by = "LC","ToLC") %>%
left_join(select(safetystock, -Item), by = "LC") %>%
mutate(xprcnt= (x * SS)) %>%
mutate(remainingss= (SS - xprcnt)) %>%
mutate(prcntvalue = (custfcst / (custfcst +Rolledfcst))) %>%
mutate(share = (prcntvalue * remainingss)) %>%
mutate(SSNew = (xprcnt + share)) %>%
mutate(Leftover = (SS - SSNew)) %>%
select(Item, LC, xprcnt, remainingss,prcntvalue,share,SSNew,Leftover)
答案 0 :(得分：0)
您在这里。我承认您在问题中指定了循环，但在R中，我尽可能避免循环。这样更好。
这将使用plyr::join_all按Item和LC连接所有数据帧，然后使用dplyr::mutate进行计算。请注意，您可以在一个mutate()函数中添加多个突变：
library(plyr)
library(dplyr)
library(tidyr)
join_all(list(gather(df1, key = LC_ref, value = LC, - Item), df2, df3, df4),
by = c("Item", "LC"),
type = "left") %>%
as_tibble() %>%
rename("SS" = "Safetystock.SS.") %>%
mutate(xprcnt= X * SS,
remainingss= SS - xprcnt,
prcntvalue = custfcst / (custfcst + Rolledfcst),
share = prcntvalue * remainingss,
SSNew = xprcnt + share,
Leftover = SS - SSNew) %>%
arrange(Item, LC_ref) %>%
group_by(Item) %>%
mutate(lag = lag(Leftover, 1) + SS)
# A tibble: 6 x 15
# Groups: Item [2]
Item LC_ref LC custfcst ToLC Rolledfcst SS X xprcnt remainingss prcntvalue share SSNew Leftover lag
<chr> <chr> <chr> <int> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 8T4121 LC1 MW92 10 OY01 22 15 0.25 3.75 11.2 0.312 3.52 7.27 7.73 NA
2 8T4121 LC2 OY01 12 RM11 10 7 0.25 1.75 5.25 0.545 2.86 4.61 2.39 14.7
3 8T4121 LC3 RM11 10 NA NA 5 0.25 1.25 3.75 NA NA NA NA 7.39
4 AB7654 LC1 MW92 NA NA NA 30 0.25 7.5 22.5 NA NA NA NA NA
5 AB7654 LC2 WK14 NA NA NA 8 0.25 2 6 NA NA NA NA NA
6 AB7654 LC3 RM11 NA NA NA 20 0.25 5 15 NA NA NA NA NA
> select(.Last.value, -LC_ref, -(custfcst:X))
# A tibble: 6 x 9
# Groups: Item [2]
Item LC xprcnt remainingss prcntvalue share SSNew Leftover lag
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 8T4121 MW92 3.75 11.2 0.312 3.52 7.27 7.73 NA
2 8T4121 OY01 1.75 5.25 0.545 2.86 4.61 2.39 14.7
3 8T4121 RM11 1.25 3.75 NA NA NA NA 7.39
4 AB7654 MW92 7.5 22.5 NA NA NA NA NA
5 AB7654 WK14 2 6 NA NA NA NA NA
6 AB7654 RM11 5 15 NA NA NA NA NA
（还要注意dplyr和plyr具有一些匹配名称的功能，我发现通常最好先在您的库语句中加载plyr。）
答案 1 :(得分：0)
library(plyr)
library(dplyr)
library(tidyr)
library(igraph)
library(data.table)
library(magrittr)
lctolc <- read.csv("LCtoLC.csv")
custfcst <- read.csv("custfcst.csv")
rolledfcst <- read.csv("rolledfcst.csv")
safetystock <- read.csv("safetystock.csv")
bodlane <- lapply(
lapply(split(lctolc, lctolc$Item), function(x) graph.data.frame(x[, 2:3])),
function(x) lapply(
all_simple_paths(x, from = V(x)[degree(x, mode = "in") == 0],
to = V(x)[degree(x, mode = "out") == 0]),
function(y) as.data.table(t(names(y))) %>% setnames(paste0("LC", seq_along(.)))
) %>% rbindlist(fill = TRUE)
) %>% rbindlist(fill = TRUE, idcol = "Item")
df1<- merge(custfcst,lctolc,by=c("LC","Item"),all.x=TRUE)
df2<- merge(rolledfcst, df1,by.x=c("LC","Item","ToLC"),by.y=c("LC","Item","ToLC"),all=TRUE)
Final<- merge(safetystock, df2, by = c("LC","Item"))
Final$xprcnt <- (Final$x * Final$SS)
Final$remainingss= (Final$SS - Final$xprcnt)
Final$prcntvalue = (Final$custfcst / (Final$custfcst +Final$Rolledfcst))
Final$share = (Final$prcntvalue * Final$remainingss)
Final$SSNew = (Final$xprcnt + Final$share)
Final$Leftover = (Final$SS - Final$SSNew)
Final<-Final[,c(2,1,5,7,6,3,4,8,9,10,11,12,13)]
答案 2 :(得分：0)
Item LC ToLC custfcst Rolledfcst SS x xprcnt remainingss prcntvalue share SSNew Leftover
1 8T4121 MW92 OY01 10 22 15 0.25 3.75 11.25 0.3125000 3.515625 7.265625 7.734375
2 8T4121 OY01 RM11 12 10 7 0.25 1.75 5.25 0.5454545 2.863636 4.613636 2.386364
3 8T4121 RM11 NA 10 NA 5 NA NA NA NA NA NA NA
I have pasted the code above.
Now I am stuck with like Item 8T4121 and LC MW92 after the computations whatever is the leftover it should be added to SS at 8T4121 and OY01 for computing the other calculations at that level.
Similarly, leftover at OY should added to SS at RM11.
THis should work for all the Items