是否有 R 函数来比较 1 列值与另一列的所有值？

Question

I am working with two different large data set and trying to make use of mapply() to get iterative functions working.

The goal is to take each data point column wise from column 'a', and compare it against all the data points in column'b'. If one element from 'a' is greater than any element of 'b' then 'compar' column is 'YES'. df<-data.frame('a'=c(10,15,8),'b'=c(22,11,9))

and I want the output to be something like this:

   a  b compar
1 10 22    yes
2 15 11    yes
3  8  9     no

Answer 1

library(dplyr)
library(lubridate)

df=data.frame(
   col1=c('2001-06-30 01:00:00','2001-07-01 01:00:00','2000-07-01 01:00:00'),
   col2=c('2000-08-01 01:00:00','2003-07-01 01:00:00','2004-06-30 01:00:00')
)

df <- df %>%
 #format dates
 mutate_at(c('col1','col2'), ~ymd_hms(.)) %>%
 #add the new column
 mutate(compar = case_when(col1 > col2 ~ 'yes', TRUE ~ 'no'))

Answer 2

You can do

df$compar <- c('no', 'yes')[(df$a > df$b) + 1]

Or

df$compar <- ifelse(df$a > df$b, "yes", "no")

Answer 3

here's a working example of your original post.

col1 <- c(as.Date("2001-06-30 01:00:00 UTC"),as.Date("2001-07-01 01:00:00 UTC"),as.Date("2000-07-01 01:00:00 UTC"))
col2 <- c(as.Date("2000-08-01 01:00:00 UTC"),as.Date("2003-07-01 01:00:00 UTC"),as.Date("2004-06-30 01:00:00 UTC"))
df <- data.frame(col1, col2)
df

check <- function(elem, datafr){

  if (TRUE %in% (elem > datafr$col2)) {
    return (TRUE)
  }
  else {
    return (FALSE)
  }
}

addCol3 <- function(vector, dframe) {
  vr <- c() ### an empty vector 

  for (i in 1:length(vector)) { 
    vr[i] <- check(vector[i], dframe)
  }
  return (vr)
}

df$col3 <- addCol3(df$col1, df)
df