R - 週間の供給

Question

私は、10億以上の行を持つデータセットの売上予想が与えられている在庫の持続時間を計算しようとしています。私は、以下に示すデータ構造の最後の列に期待される出力を列挙しました。私はExcelのこの実装を添付しました。

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. 

最後の列

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")) 

現在のExcelコードで

予想される出力：（ここ数週間は、列に示されているが、それは予想される出力に示すような行でなければなりません。 ）

=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")) 

これをRで効率的に実装するための入力がありがとうと思います。ここで

Answer 1

それを行うための一つの方法である、次の操作を行うことができます...

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 

Answer 2

が...線形補間法approxfunを使用して、長い形式で改訂されたデータについては

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