使用另一个具有var名称和其他条件的数据帧对数据帧进行子集设置

df_keep

conditions_met <- df_keep$othvar == "r" | is.na(df_keep$othvar)

> conditions_met
[1]  TRUE FALSE  TRUE FALSE  TRUE

df_keep$keepvar

kept_rows <- df_keep$keep_var[conditions_met]

> kept_rows
[1] coat   book   bottle

df_main 他们的名字和 kept_rows :

df_main[, as.character(kept_rows)]
  coat book bottle
1    1    1      1
2    2    2      2
3    3    3      3
4    4    4      4
5    5    5      5

或者在一行中:

> df_main[, as.character(df_keep$keep_var[df_keep$othvar == "r" |
+                                           is.na(df_keep$othvar)])]
  coat book bottle
1    1    1      1
2    2    2      2
3    3    3      3
4    4    4      4
5    5    5      5

注意, as.character 因为示例数据集不使用 stringsAsFactors = FALSE . 如果有,你可以省略 as.字符 参数,所以如果您的实际数据是字符而不是因子,那么您应该能够删除 as.字符 . 如:

df_main <-
  data.frame(
    coat = c(1:5),
    hanger = c(1:5),
    book = c(1:5),
    dvd = c(1:5),
    bookcase = c(1:5),
    clock = c(1:5),
    bottle = c(1:5),
    curtains = c(1:5),
    wall = c(1:5),
    stringsAsFactors = FALSE
  )

df_keep <-
  data.frame(
    keep_var = c("coat", "hanger", "book", "wall", "bottle"),
    othvar = c("r", "w", "r", "w", NA),
    stringsAsFactors = FALSE
  )

df_goal <- data.frame(coat = c(1:5),
                      book = c(1:5),
                      bottle = c(1:5))


df_main[, df_keep$keep_var[df_keep$othvar == "r" |
                                          is.na(df_keep$othvar)]]

这是一个 dplyr 解决方案

library(dplyr)
# Filter based on 'othvar' and convert factor to string.
keep.vec <- as.character(
    (df_keep %>% dplyr::filter(is.na(othvar) | othvar == 'r'))$keep_var
)
df_main %>% dplyr::select(keep.vec)

##   coat book bottle
## 1    1    1      1
## 2    2    2      2
## 3    3    3      3
## 4    4    4      4
## 5    5    5      5