r summarize_if with multiple conditions

Question

I'm trying to reduce a df of observations to a single observation (single line). I would like to summarize_if is numeric with the mean and if is string or factor with the mode. The code below doesn't work, but I hope it gives the idea. Thanks!

#data frame
num <- c(1:7)
str <- c("toy","control","play",NA,"give","toy","toy")
df_finale <- data.frame(num,str)

#mode function
Mode <- function(x) {
        ux <- unique(x)
        ux[which.max(tabulate(match(x, ux)))]
}

#df reduction
df_finale <- df_finale %>%
                    summarize_if(is.numeric, mean, na.rm = TRUE) %>%
                    summarize_else_if(!is.numeric, Mode)

tmfmnk · Accepted Answer · 2021-02-13T17:54:42.173

5

One possibility could be:

df_finale %>%
 summarise_all(~ if(is.numeric(.)) mean(., na.rm = TRUE) else Mode(.))

  num str
1   4 toy

Or an option since dplyr 1.0.0:

df_finale %>%
 summarise(across(everything(), ~ if(is.numeric(.)) mean(., na.rm = TRUE) else Mode(.)))

edited Feb 13 '21 at 17:54

answered May 06 '20 at 15:13

tmfmnk

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Great! Where can I place na.rm = TRUE in the mean formula? – fiodeno May 06 '20 at 15:44
2

You can simply use `mean(., na.rm = TRUE)` :) – tmfmnk May 06 '20 at 15:55
1

And please note, that the mode function you've chosen will only return the first mode is there are more than one, where first means that it is the first string encountered – Chuck P May 06 '20 at 15:59

score 1 · Answer 2 · answered May 06 '20 at 18:51

We could use mutate_if with distinct

library(dplyr)
library(purrr)
df_finale %>%
     mutate_if(is.numeric, mean, na.rm = TRUE) %>% 
     mutate_if(negate(is.numeric), Mode) %>%
     distinct
#   num str
#1   4 toy

Or with across/summarise from the new version of dplyr

i1 <- df_finale %>% 
           summarise_all(is.numeric) %>%
           flatten_lgl

df_finale %>% 
     summarise(across(names(.)[i1], ~ mean(., na.rm = TRUE)), 
               across(names(.)[!i1], Mode))

r summarize_if with multiple conditions

2 Answers2

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