R - 供应周数
R - Weeks of supply
我正在尝试根据具有 10 万行的数据集的销售预测来计算手头库存将持续的周数。我在下面给出的数据结构的最后一列中列出了预期的输出。我还在 Excel.
中附上了这个的实现
Logic
Weeksofsupply = Number of weeks the current inventory on hand will last.
example - in the attached image (SKU_CD 222, STORE_CD 33), the inventory on hand is 19, the sales values are
WK1 + WK2 = 15, Wk1 + Wk2 + Wk3 = 24, Which is greater than 19,
So we are picking 2, which the count of Weeks the current inventory will last.
最后一列的预期输出
Data = structure(list(
SKU_CD = c(111, 111, 111, 111, 111, 111, 111,111, 111, 111, 111, 111, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222),
STORE_CD = c(22, 22, 22, 22, 22, 22, 22,22, 22, 22, 22, 22, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33),
FWK_CD = c(201627, 201628, 201629, 201630, 201631, 201632,201633, 201634, 201635, 201636, 201637, 201638, 201627, 201628, 201629, 201630, 201631, 201632, 201633, 201634, 201635, 201636, 201637, 201638),
SALES = c(5, 2, 2, 2, 1, 3, 2, 2, 3, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 7, 5),
INVENTORY = c(29, 27, 25, 23, 22, 19, 17, 15, 12, 10, 25, 1, 19, 17, 15, 13, 12,9, 7, 5, 2, 0, 25, 18),
WeeksofSupply = c("11", "10", "9", "8", "8", "6", "5", "4", "3", "2", "Inventory More", "Inventory Less", "2", "2", "1", "1", "1", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory More", "Inventory More")),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -24L),
.Names = c("SKU_CD", "STORE_CD", "FWK_CD", "SALES", "INVENTORY", "WeeksofSupply"))
当前 Excel 代码：（这里的周数显示在列中，但它应该是预期输出中显示的行。）
=IF(A2<SUM(B2:K2),SUMPRODUCT(--(SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))<=A2))+LOOKUP(0,SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))-B2:K2-A2,(A2-(SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))-B2:K2))/B2:K2),IF(A2=SUM(B2:K2),COUNT(B2:K2),"Inventory
exceeds forecast"))
如果能在 R 中有效地实现这一点，我将不胜感激。非常感谢您的宝贵时间！
这是一种方法，使用线性插值法approxfun...
data$WeeksSupply <- sapply(1:nrow(data),function(i)
approxfun(cumsum(as.vector(c(data[i,2:11]))),1:10)(data$Inventory[i]))
data$WeeksSupply <- replace(data$WeeksSupply,is.na(data$WeeksSupply),
"Inventory Exceeds Forecast")
data
# A tibble: 2 x 12
Inventory Wk1 Wk2 Wk3 Wk4 Wk5 Wk6 Wk7 Wk8 Wk9 Wk10 WeeksSupply
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
1 200 20 15 25 40 35 45 30 50 45 55 6.66666666666667
2 2000 20 15 25 40 35 45 30 50 45 55 Inventory Exceeds Forecast
对于长格式的修改数据，您可以执行以下操作...
library(dplyr) #for the grouping functionality
#define a function to calculate weeks Supply from Sales and Inventory
weekSup <- function(sales,inv){
sales <- unlist(sales)
inv <- unlist(inv)
n <- length(sales)
weeksup <- rep(NA,n)
for(i in 1:n){
if(i==n | inv[i]<sales[i]){
weeksup[i] <- ifelse(inv[i]>sales[i],NA,inv[i]/sales[i])
} else {
weeksup[i] <- approxfun(cumsum(sales[i:n]),1:(n-i+1))(inv[i])
}
}
#Your 'inventory more' is coded as -1 (a number) to avoid whole column being forced to a character vector
weeksup <- replace(weeksup,is.na(weeksup),-1)
return(weeksup) #for whole weeks, change this to `return(floor(weeksup))`
}
Data2 <- Data %>% group_by(SKU_CD,STORE_CD) %>% mutate(weekSup=weekSup(SALES,INVENTORY))
head(Data2,20)
SKU_CD STORE_CD FWK_CD SALES INVENTORY WeeksofSupply weekSup
<dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
1 111 22 201627 5 29 11 11.3333333
2 111 22 201628 2 27 10 10.8333333
3 111 22 201629 2 25 9 9.8333333
4 111 22 201630 2 23 8 8.8333333
5 111 22 201631 1 22 8 8.0000000
6 111 22 201632 3 19 6 6.6666667
7 111 22 201633 2 17 5 5.8333333
8 111 22 201634 2 15 4 4.8333333
9 111 22 201635 3 12 3 3.6666667
10 111 22 201636 2 10 2 2.8333333
11 111 22 201637 3 25 Inventory More -1.0000000
12 111 22 201638 6 1 Inventory Less 0.1666667
13 222 33 201627 7 19 2 2.4444444
14 222 33 201628 8 17 2 2.0000000
15 222 33 201629 9 15 1 1.6000000
16 222 33 201630 10 13 1 1.2727273
17 222 33 201631 11 12 1 1.0833333
18 222 33 201632 12 9 Inventory Less 0.7500000
19 222 33 201633 13 7 Inventory Less 0.5384615
20 222 33 201634 14 5 Inventory Less 0.3571429
我正在尝试根据具有 10 万行的数据集的销售预测来计算手头库存将持续的周数。我在下面给出的数据结构的最后一列中列出了预期的输出。我还在 Excel.
中附上了这个的实现Logic
Weeksofsupply = Number of weeks the current inventory on hand will last.
example - in the attached image (SKU_CD 222, STORE_CD 33), the inventory on hand is 19, the sales values are
WK1 + WK2 = 15, Wk1 + Wk2 + Wk3 = 24, Which is greater than 19,
So we are picking 2, which the count of Weeks the current inventory will last.
最后一列的预期输出
Data = structure(list(
SKU_CD = c(111, 111, 111, 111, 111, 111, 111,111, 111, 111, 111, 111, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222, 222),
STORE_CD = c(22, 22, 22, 22, 22, 22, 22,22, 22, 22, 22, 22, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33),
FWK_CD = c(201627, 201628, 201629, 201630, 201631, 201632,201633, 201634, 201635, 201636, 201637, 201638, 201627, 201628, 201629, 201630, 201631, 201632, 201633, 201634, 201635, 201636, 201637, 201638),
SALES = c(5, 2, 2, 2, 1, 3, 2, 2, 3, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 7, 5),
INVENTORY = c(29, 27, 25, 23, 22, 19, 17, 15, 12, 10, 25, 1, 19, 17, 15, 13, 12,9, 7, 5, 2, 0, 25, 18),
WeeksofSupply = c("11", "10", "9", "8", "8", "6", "5", "4", "3", "2", "Inventory More", "Inventory Less", "2", "2", "1", "1", "1", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory Less", "Inventory More", "Inventory More")),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -24L),
.Names = c("SKU_CD", "STORE_CD", "FWK_CD", "SALES", "INVENTORY", "WeeksofSupply"))
当前 Excel 代码：（这里的周数显示在列中，但它应该是预期输出中显示的行。）
=IF(A2<SUM(B2:K2),SUMPRODUCT(--(SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))<=A2))+LOOKUP(0,SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))-B2:K2-A2,(A2-(SUBTOTAL(9,OFFSET(B2:K2,,,,COLUMN(B2:K2)-
COLUMN(B2)+1))-B2:K2))/B2:K2),IF(A2=SUM(B2:K2),COUNT(B2:K2),"Inventory
exceeds forecast"))
如果能在 R 中有效地实现这一点，我将不胜感激。非常感谢您的宝贵时间！
这是一种方法，使用线性插值法approxfun...
data$WeeksSupply <- sapply(1:nrow(data),function(i)
approxfun(cumsum(as.vector(c(data[i,2:11]))),1:10)(data$Inventory[i]))
data$WeeksSupply <- replace(data$WeeksSupply,is.na(data$WeeksSupply),
"Inventory Exceeds Forecast")
data
# A tibble: 2 x 12
Inventory Wk1 Wk2 Wk3 Wk4 Wk5 Wk6 Wk7 Wk8 Wk9 Wk10 WeeksSupply
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
1 200 20 15 25 40 35 45 30 50 45 55 6.66666666666667
2 2000 20 15 25 40 35 45 30 50 45 55 Inventory Exceeds Forecast
对于长格式的修改数据，您可以执行以下操作...
library(dplyr) #for the grouping functionality
#define a function to calculate weeks Supply from Sales and Inventory
weekSup <- function(sales,inv){
sales <- unlist(sales)
inv <- unlist(inv)
n <- length(sales)
weeksup <- rep(NA,n)
for(i in 1:n){
if(i==n | inv[i]<sales[i]){
weeksup[i] <- ifelse(inv[i]>sales[i],NA,inv[i]/sales[i])
} else {
weeksup[i] <- approxfun(cumsum(sales[i:n]),1:(n-i+1))(inv[i])
}
}
#Your 'inventory more' is coded as -1 (a number) to avoid whole column being forced to a character vector
weeksup <- replace(weeksup,is.na(weeksup),-1)
return(weeksup) #for whole weeks, change this to `return(floor(weeksup))`
}
Data2 <- Data %>% group_by(SKU_CD,STORE_CD) %>% mutate(weekSup=weekSup(SALES,INVENTORY))
head(Data2,20)
SKU_CD STORE_CD FWK_CD SALES INVENTORY WeeksofSupply weekSup
<dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
1 111 22 201627 5 29 11 11.3333333
2 111 22 201628 2 27 10 10.8333333
3 111 22 201629 2 25 9 9.8333333
4 111 22 201630 2 23 8 8.8333333
5 111 22 201631 1 22 8 8.0000000
6 111 22 201632 3 19 6 6.6666667
7 111 22 201633 2 17 5 5.8333333
8 111 22 201634 2 15 4 4.8333333
9 111 22 201635 3 12 3 3.6666667
10 111 22 201636 2 10 2 2.8333333
11 111 22 201637 3 25 Inventory More -1.0000000
12 111 22 201638 6 1 Inventory Less 0.1666667
13 222 33 201627 7 19 2 2.4444444
14 222 33 201628 8 17 2 2.0000000
15 222 33 201629 9 15 1 1.6000000
16 222 33 201630 10 13 1 1.2727273
17 222 33 201631 11 12 1 1.0833333
18 222 33 201632 12 9 Inventory Less 0.7500000
19 222 33 201633 13 7 Inventory Less 0.5384615
20 222 33 201634 14 5 Inventory Less 0.3571429