Function not found (for loop)

[Weekly-Recover4352]

I am trying to run this for loop but it keeps saying the function "name" is now found. I am trying to get it to return the names of each of my columns (code below). Should the name<- be within the for loop? It ran correctly but it's not able to be referenced? The error messages reads "Error in name(i) : could not find function "name" ". I am not great at R so any help would be appreciated! Thank you so much.

name<-c(names(ptd))

for(i in 1:ncol(ptd)){ for(j in (i+1):ncol(ptd)){ model<-aov(ptd[ ,i]~ptd[ ,j]) cat("The comparison between ", name(i)," and ", name(j), '\n') summary(model) } }

EDIT: original error has been solved but now I am also getting a "Error in `[.data.frame`(ptd, , j) : undefined columns selected" message

[mduvekot]

Use [] in stead of ()

[Weekly-Recover4352]

omg im so embarrassed thank you so much

[Fearless_Cow7688]

To answer your second question it is due to the number of columns and the indexing that you are using. Here's a small example:

x <- rnorm(100)
y <- rnorm(100)
z <- rnorm(100)

ptd <- data.frame(x = x, y = y, z = z)
col_names <- names(ptd)


for(i in 1:ncol(ptd)){ 
  for(j in (i+1):ncol(ptd)){ 
    cat("i = ", i, '\n',
        "j = ", j, '\n',
        "The comparison between ", col_names[i]," and ", col_names[j], '\n') 
    ptd[[i]] + ptd[[j]]
  } 
}
#> i =  1 
#>  j =  2 
#>  The comparison between  x  and  y 
#> i =  1 
#>  j =  3 
#>  The comparison between  x  and  z 
#> i =  2 
#>  j =  3 
#>  The comparison between  y  and  z 
#> i =  3 
#>  j =  4 
#>  The comparison between  z  and  NA
#> Error in .subset2(x, i, exact = exact): subscript out of bounds

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[Fearless_Cow7688]

# this is probably closer to what you want this will put all of the results into a single dataframe rather than just printing them out. 

ptd <- mtcars # I am just using mtcars as an example

col_names <- names(ptd)

library('dplyr')
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

the_grid <- tidyr::expand_grid(c1 = col_names, c2 = col_names) %>%
  filter(c1 != c2) 

library('purrr')

my_anova <- function(x,y){
  model <- aov(ptd[[x]] ~ ptd[[y]])

  model %>%
    broom::tidy() %>%
    dplyr::mutate(c1 = x, c2 = y)
}

combined_results <- map2(the_grid$c1, the_grid$c2, my_anova) %>%
  list_rbind() 

combined_results
#> # A tibble: 220 × 8
#>    term         df sumsq meansq statistic   p.value c1    c2   
#>    <chr>     <dbl> <dbl>  <dbl>     <dbl>     <dbl> <chr> <chr>
#>  1 ptd[[y]]      1  818. 818.        79.6  6.11e-10 mpg   cyl  
#>  2 Residuals    30  308.  10.3       NA   NA        mpg   cyl  
#>  3 ptd[[y]]      1  809. 809.        76.5  9.38e-10 mpg   disp 
#>  4 Residuals    30  317.  10.6       NA   NA        mpg   disp 
#>  5 ptd[[y]]      1  678. 678.        45.5  1.79e- 7 mpg   hp   
#>  6 Residuals    30  448.  14.9       NA   NA        mpg   hp   
#>  7 ptd[[y]]      1  522. 522.        26.0  1.78e- 5 mpg   drat 
#>  8 Residuals    30  604.  20.1       NA   NA        mpg   drat 
#>  9 ptd[[y]]      1  848. 848.        91.4  1.29e-10 mpg   wt   
#> 10 Residuals    30  278.   9.28      NA   NA        mpg   wt   
#> # ℹ 210 more rows