您不需要自定义函数来执行此操作。让dplyr处理它。假设您的数据位于名为 的数据框中df，它可能如下所示：

df %>%                                       # Set up the pipe
subset(complete.cases(df)) %>%               # Removes rows with NA values
group_by(Name) %>%                           # Groups by the Name column
count(Color) %>%                             # Counts each Color by Name, creates a new column n
mutate(max = max(n)) %>%                     # Creates a new column for the max(n) by Name
subset(n == max(n)) %>%                      # Keeps only those rows where n equals max(n)
mutate(Keep == case_when(                    # Creates a dummy logical column named 'Keep'
   n > 1 ~ TRUE,                             # That is TRUEfor n > 1 to keep ties
   n == 1 & Color == head(Color, 1) ~ TRUE,  # That is TRUE for the first row of n = 1
   TRUE ~ FALSE)) %>%                        # That is FALSE for all other cases
subset(Keep) %>%                             # Keeps only those rows where Keep is TRUE
select(Name, Mode = Color, n)                # Keeps only the Name, Color, and n columns and
                                             # renames Color as Mode

这是输出

 # A tibble: 3 x 3
 # Groups:   Name [3]
   Name  Mode   Count
   <fct> <fct>  <int>
 1 Bob   Green      3
 2 Drew  Blue       1
 3 Jim   Blue       2
 4 Jim   Red        2

如果您想要一个函数，请将其包装在函数定义中：

my_mode_func <- function(df){
df %>% 
   subset(complete.cases(df)) %>%
   group_by(Name) %>%
   count(Color) %>%
   mutate(max = max(n)) %>%
   subset(n == max) %>%
   mutate(Keep = case_when(
      n > 1 ~ TRUE,
      n == 1 & Color == head(Color,1) ~ TRUE,
      TRUE ~ FALSE)) %>%
   subset(Keep) %>%
   select(Name, Mode = Color, Count = n)
}