How to identify all columns that contain binary representation

We could use colSums with stack

stack(colSums(dframe[-1] > 1) == 0)

#  values    ind
#1  FALSE Google
#2   TRUE  Yahoo
#3   TRUE Amazon

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Some other methods using dplyr

library(dplyr)
dframe %>% summarise_at(-1, ~all(. < 2)) 

Or using apply

!apply(dframe[-1] > 1, 2, any)

A tidyverse approach:

dframe %>% 
  purrr::map_lgl(~all(.x %in% c(0,1)))
    id Google  Yahoo Amazon 
 FALSE  FALSE   TRUE   TRUE 

Or if you want it in the exact format:

 dframe %>% 
   purrr::map_lgl(~all(.x %in% c(0,1))) %>% 
 .[-1] %>% 
   as.data.frame() %>%  
   setNames("values")
       values
Google  FALSE
Yahoo    TRUE
Amazon   TRUE

An option is

dframe[!Reduce(`|`, lapply(dframe[-1], `>`, 0)),]

You can create your own fnction:

is_binary <- function(x) length(unique(x)) == 2


sapply(dframe, is_binary)

 #id Google  Yahoo Amazon 
 #FALSE   TRUE   TRUE   TRUE 

If you're actually looking for 0 and 1 binary, you can do:

is_binary <- function(x) all(unique(x) %in% c(0, 1))

sapply(dframe, is_binary)
 #  id Google  Yahoo Amazon 
 #FALSE  FALSE   TRUE   TRUE