Question

我正在尝试通过将接下来的3个值和接下来的4个值相加来计算forcast_leadtime并预测第一行中的供应周数来生成一系列。我已经填充了两者的预期值，即1.008＆amp;分别为1.64。你能否告诉我如何在R中生成这个运行系列。谢谢

forecast_leadtime（FL）=第2,3周的SYS_FORC总和4 forecast_weeks of supply（FWOS）=每周5,6,7,8的SYS_FORC总和

SKU STORE_CD FWK_CD WK_Sequence_NBR SYS_FORC FL FWOS 12345 10 201648 935 0.328 1.008 1.64 12345 10 201649 936 0.326 0 0 12345 10 201650 937 0.323 0 0 12345 10 201651 938 0.359 0 0 12345 10 201652 939 0.366 0 0 12345 10 201701 940 0.414 0 0 12345 10 201702 941 0.433 0 0 12345 10 201703 942 0.4 enter image description here 27 0 0 12345 10 201704 943 0.421 0 0 12345 10 201705 944 0.422 0 0

Answer 1

遵循@akrun方法，但使用库zoo和dplyr lead。我按照SKU STORE_CD进行分组，以表明这是可能的

df <- read.table(header= TRUE, text=
"SKU STORE_CD    FWK_CD  WK_Sequence_NBR SYS_FORC    forecast_leadtime   forecast_weeksofsupply
12345   10  201648  935 0.328   1.008   1.64
12345   10  201649  936 0.326   0   0
12345   10  201650  937 0.323   0   0
12345   10  201651  938 0.359   0   0
12345   10  201652  939 0.366   0   0
12345   10  201701  940 0.414   0   0
12345   10  201702  941 0.433   0   0
12345   10  201703  942 0.427   0   0
12345   10  201704  943 0.421   0   0
12345   10  201705  944 0.422   0   0
")


library(zoo)
library(dplyr)
df %>% 
  group_by(SKU, STORE_CD) %>%
  mutate(forecast_leadtime = rollsum(lead(SYS_FORC), 3, na.pad = TRUE, align = "left"),
         forecast_weeksofsupply = rollsum(lead(SYS_FORC, 4), 4, na.pad = TRUE,  align = "left"))

#      SKU STORE_CD FWK_CD WK_Sequence_NBR SYS_FORC forecast_leadtime forecast_weeksofsupply
# 1  12345       10 201648             935    0.328             1.008                  1.640
# 2  12345       10 201649             936    0.326             1.048                  1.695
# 3  12345       10 201650             937    0.323             1.139                  1.703
# 4  12345       10 201651             938    0.359             1.213                     NA
# 5  12345       10 201652             939    0.366             1.274                     NA
# 6  12345       10 201701             940    0.414             1.281                     NA
# 7  12345       10 201702             941    0.433             1.270                     NA
# 8  12345       10 201703             942    0.427                NA                     NA
# 9  12345       10 201704             943    0.421                NA                     NA
# 10 12345       10 201705             944    0.422                NA                     NA

R根据接下来的3个值

1 个答案: