Applying function (ks.test) between two data frames colum-wise in R

Question

My simple question is: How do you do a ks.test between two data frames column by column?

Eg. We have two data frames:

D1 <- data.fra         


        

Answer 1

A tidyverse solution using map function from the purrr package together with tidy function from the broom package

library(purrr)
library(broom)

# Data posted by @TUSHAr
set.seed(12)
D1 <- data.frame(A = rnorm(n = 30, mean = 5, sd = 2.5), 
                 B = rnorm(n = 30, mean = 4.5, sd = 2.2), 
                 C = rnorm(n = 30, mean = 2.5, sd = 12))
D2 <- data.frame(A = rnorm(n = 30, mean = 5, sd = 2.49), 
                 B = rnorm(n = 30, mean = 4.4, sd = 2.2), 
                 C = rnorm(n = 30, mean = 2, sd = 12))

# Loop through each column
result <- colnames(D1) %>%
  set_names() %>% 
  # apply `ks.test` function for each column pair
  map(~ ks.test(D1[, .x], D2[, .x])) %>%
  # extract test results using `tidy` then bind them together by rows
  map_dfr(., broom::tidy, .id = "parameter")
result

#> # A tibble: 3 x 5
#>   parameter statistic p.value method                           alternative
#>   <chr>         <dbl>   <dbl> <chr>                            <chr>      
#> 1 A             0.167   0.808 Two-sample Kolmogorov-Smirnov t~ two-sided  
#> 2 B             0.2     0.594 Two-sample Kolmogorov-Smirnov t~ two-sided  
#> 3 C             0.233   0.393 Two-sample Kolmogorov-Smirnov t~ two-sided

Created on 2018-08-24 by the reprex package (v0.2.0.9000).

Answer 2

Created two data.frames D1 and D2 with some random numbers and same column names.

set.seed(12)
D1 = data.frame(A=rnorm(n = 30,mean = 5,sd = 2.5),B=rnorm(n = 30,mean = 4.5,sd = 2.2),C=rnorm(n = 30,mean = 2.5,sd = 12))
D2 = data.frame(A=rnorm(n = 30,mean = 5,sd = 2.49),B=rnorm(n = 30,mean = 4.4,sd = 2.2),C=rnorm(n = 30,mean = 2,sd = 12))

Now we can use the column names to loop through and pass it to D1 and D2 to perform the ks.test on the corresponding columns of the respective data.frames.

col.names = colnames(D1)
lapply(col.names,function(t,d1,d2){ks.test(d1[,t],d2[,t])},D1,D2)

#[[1]]

#Two-sample Kolmogorov-Smirnov test

#data:  d1[, t] and d2[, t]
#D = 0.167, p-value = 0.81
#alternative hypothesis: two-sided


#[[2]]

#Two-sample Kolmogorov-Smirnov test

#data:  d1[, t] and d2[, t]
#D = 0.233, p-value = 0.39
#alternative hypothesis: two-sided


#[[3]]

#Two-sample Kolmogorov-Smirnov test

#data:  d1[, t] and d2[, t]
#D = 0.2, p-value = 0.59
#alternative hypothesis: two-sided

In the notation you have used in the question description, ideally the following code should work:

col.names =colnames(S)
lapply(col.names,function(t,d1,d2){ks.test(d1[,t],d2[,t])},D,S)