dplyr使用ifelse过滤数据帧变量的值？

Question

I have a dataframe:

structure(list(a = c(1, 2, 3), b = c(TRUE, TRUE, FALSE)), .Names = c("a", 
"b"), row.names = c(NA, -3L), class = c("tbl_df", "tbl", "data.frame"
))

and a function:

foo <- function(df, L = TRUE) {

    return(df %>% filter(ifelse(L, b, !b))) }

When I run it, it seems that ifelse doesn't do the job. Please advise how can I "tell" the function to filter for all TRUE's if L is TRUE and FALSE's otherwise?

Answer 1

The ifelse needs a vectorize argument when used with dplyr::filter or dplyr::mutate . That means the condition should be a vector of length matching with row numbers provided to ifelse as condition is evaluated for each row.

You can modify your function to provide L as below:

library(dplyr)

foo <- function(df, L = TRUE) {
  # replicate the condition to match number of rows
  return(df %>% filter(ifelse(rep(L,nrow(.)), b, !b))) 
  }

Now verify results:

foo(df)
# # A tibble: 2 x 2
# a b    
# <dbl> <lgl>
# 1  1.00 T    
# 2  2.00 T    

foo(df,FALSE)
# # A tibble: 1 x 2
# a b    
# <dbl> <lgl>
# 1  3.00 F 

Answer 2

What about this in base R?

foo <- function(df, L = TRUE) {
  if (L == TRUE) return(df[df$b == TRUE, ])
  else return(df[df$b == FALSE, ])
}

Yielding

> foo(df, L=TRUE)
# A tibble: 2 x 2
      a b    
  <dbl> <lgl>
1     1 TRUE 
2     2 TRUE 
> foo(df, L=FALSE)
# A tibble: 1 x 2
      a b    
  <dbl> <lgl>
1     3 FALSE