如何為R代碼輸入新條件

下面的代碼作業正常，但我想創建另一個名為JOVafter 的變數SPV。此變數將具有如下條件：

如果我有"Category", "Week"and "DTT"in group_cols, 請執行以下操作：

  SPV %>% filter(date2 == dmda, Category == CategoryChosse, DTT==DTest)

如果我有 "Category"和"Week"in group_cols，請執行以下操作：

 SPV %>% filter(date2 == dmda, Category == CategoryChosse)

如果我只有"Category"in group_cols，請執行以下操作：

 SPV %>% filter(date2 == dmda)

可執行代碼如下

library(dplyr)
library(tidyverse)
library(lubridate)

df1 <- structure(
  list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
       date2 = c("2021-06-23","2021-06-24","2021-06-30","2021-07-01"),
       DTT= c("Hol","Hol","Hol",0),
       Week= c("Wednesday","Thursday","Wednesday","Thursday"),
       Category = c("ABC","FDE","ABC","FDE"),
       DR1 = c(4,1,1,2),
       DR01 = c(4,1,2,3), DR02= c(4,2,0,2),DR03= c(9,5,0,1),
       DR04 = c(5,4,3,2),DR05 = c(5,4,0,2)),
  class = "data.frame", row.names = c(NA, -4L))

dmda<-"2021-07-01"
CategoryChosse<-"FDE"
DTest<-"Hol"
Wk<-"Thursday"

Dx<-subset(df1,df1$date2<df1$date1)

x<-Dx %>% select(starts_with("DR0"))

x<-cbind(Dx, setNames(Dx$DR1 - x, paste0(names(x), "_PV")))

PV<-select(x, date2,Week, Category, DTT, DR1, ends_with("PV"))

group_cols <-
  if (any(PV$DTT == DTest & PV$Week == Wk, na.rm = TRUE)) {
    c("Category", "Week", "DTT")
  } else if (any(PV$Week == Wk & PV$Category == CategoryChosse & PV$DTT != DTest, na.rm=TRUE)) {
    c("Category", "Week")
  } else {
    "Week"
  }

med <- PV %>%
  group_by(across(all_of(group_cols))) %>%
  summarize(across(ends_with("PV"), median),.groups = 'drop')

SPV <- df1 %>%
  inner_join(med, by = group_cols) %>%
  mutate(across(matches("^DR0\\d $"), ~.x   
                  get(paste0(cur_column(), '_PV')),
                .names = '{col}_{col}_PV')) %>%
  select(date1:Category, DR01_DR01_PV:last_col())

uj5u.com熱心網友回復：

嘗試：

SPV %>% 
  filter(
    date2 == dmda,
    !("Category" %in% group_cols) | Category == CategoryChosse,
    !all(c("Category", "DTT") %in% group_cols) | DTT == DTest
  )

這是您的條件的字面翻譯。但是，如果我沒看錯的話，可以將其簡化為

SPV %>% 
  filter(
    date2 == dmda,
    !("Category" %in% group_cols) | Category == CategoryChosse,
    !("DTT" %in% group_cols) | DTT == DTest
  )

如果您曾經想象允許"DTT"而不是"Category"在您的group_cols. （即使這永遠不會發生，這也有效。）

uj5u.com熱心網友回復：

您可以將不同的案例存盤在一個串列中，并根據需要提取元素。

1. 更改此函式以回傳向量和串列索引。

filter_condition <-
  if (any(PV$DTT == DTest & PV$Week == Wk, na.rm = TRUE)) {
    1:3 # if you had options out of order, you could have something like c(1, 3)
  } else if (any(PV$Week == Wk & PV$Category == CategoryChosse & PV$DTT != DTest, na.rm=TRUE)) {
    1:2
  } else {
    1
  }

2. 創建用于分組和過濾的向量和串列。

group_cols <- c("Week", "Category", "DTT")

filter_opts <- rlang::exprs(date2 == dmda,
                            Category == CategoryChosse,
                            DTT == DTest)

3. 改變你的group_by()基于你在這種情況下，從變數來拉。

med <- PV %>%
  group_by(across(all_of(group_cols[filter_condition]))) %>%
  summarize(across(ends_with("PV"), median),.groups = 'drop')

4. 和以前一樣的代碼。

  inner_join(med, by = group_cols) %>%
  mutate(across(matches("^DR0\\d $"), ~.x   
                  get(paste0(cur_column(), '_PV')),
                .names = '{col}_{col}_PV')) %>%
  select(date1:Category, DR01_DR01_PV:last_col())

5. 根據您所處的情況應用過濾條件。

SPV %>% 
  filter(!!!filter_opts[filter_condition])

正如另一個答案中提到的，您可以縮短它，因為它似乎date2總是需要的。但這為此類事情制定了一些框架。

標籤：r

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