Using Mann Whitney to create list of pvalues

I am looking to find a way to write a for loop using a Mann Whitney Wilcox test in R. The command I have seen online is wilcox.test(). But I am trying to do so for large data sets that have thousands of columns. I have not found any luck online for other resources.

I have this data frame, DF1, and two groups (Sam and Anna) under DF1$Name. The nonparametric approach with two groups is desired for this data, and I want to run a for loop to get the p-value for each of the column names (Companies, Store, Cars, and Homes) when comparing the two groups (Sam and Anna). Is there an efficient way to do so?


Name Companies Store Cars Homes
Sam 23 10 10 8
Anna 21 8 7 4
Anna 22 5 5 5
Sam 24 5 6 8
Anna 45 6 7 4

My goal is to get a list of p-values generated. Any suggestions would be appreciated! Thank you!

# DF1
Name <- c("Sam", "Anna", "Anna", "Sam", "Anna")
Companies <- c(23, 21, 22, 24, 45)
Store <- c(10, 8, 5, 5, 6)
Cars <- c(10, 7, 5, 6, 7)
Home <- c(8, 4, 5, 8, 4)
DF1 <- data.frame(Name, Companies, Store, Cars, Home)

I have tried this so far, and it definitely doesnt work, but I feel this is something towards I want to get. The code below was the first part of the test that was derived from here. But now is there a way to grab all of the p-values here in a list next to the descriptors (companies, store, cars, homes?)

DF1$Group <- as.factor(DF1$Name)

Z <- lapply(DF1[-1], function(x){
    wilcox.test(x ~ DF1$Name)


  • Here is one way:

    DF1 %>% 
      select_if(is.numeric) %>%
      map_df(~ broom::tidy(wilcox.test(. ~ Name)), .id = 'var')
    # A tibble: 4 × 5
      var       statistic p.value method                                            alternative
      <chr>         <dbl>   <dbl> <chr>                                             <chr>      
    1 Companies       2     0.8   Wilcoxon rank sum exact test                      two.sided  
    2 Store           2.5   1     Wilcoxon rank sum test with continuity correction two.sided  
    3 Cars            2     0.767 Wilcoxon rank sum test with continuity correction two.sided  
    4 Home            0     0.128 Wilcoxon rank sum test with continuity correction two.sided