डेटा फ्रेम में संग्रहीत चर नामों को पुनरावृत्त रूप से जोड़कर दो स्ट्रिंग्स की सूची कैसे बनाएं ताकि प्रत्येक कॉलम से एक हो

यहां एक base समाधान है जो सामान्य है (अधिक कॉलम तक स्केल)। आपके डेटा को कॉल करना dd:

# Omit missing values - data isn't really rectangular
# and rows seem to have no meaning
# so a list is an appropriate structure
dd_list = lapply(dd, na.omit)

# generate all pairs of "columns" (now list items)
col_pairs = combn(seq_along(dd_list), 2)

# for each pair, use `expand.grid` to generate all combinations
# since the wanted result is a list of vectors, not a data frame
# we strip the names and convert to matrix
result = apply(col_pairs, MARGIN = 2, FUN = function(x) {
  as.matrix(unname(do.call(expand.grid, args = dd_list[x])))
})

# bind the matrices together - this seems like a nice result to work with
result = do.call(rbind, result)
result
 #      [,1]                                      [,2]                   
 # [1,] "Combined_t2|t1_lag8"                     "mean_RT_200_all"      
 # [2,] "Combined_abmag_t2_lag8_minus_lag3"       "mean_RT_200_all"      
 # [3,] "Combined_abmag_t2_1.0_minus_lag3"        "mean_RT_200_all"      
 # [4,] "Combined_abwidth"                        "mean_RT_200_all"      
 # [5,] "Combined_abdepth"                        "mean_RT_200_all"      
 # [6,] "Combined_lag3vslag8_residuals"           "mean_RT_200_all"      
 # [7,] "Combined_lag3vslag8_stdrdized_residuals" "mean_RT_200_all"      
 # [8,] "Combined_t2|t1_lag8"                     "mean_RT_1000_all"   
 # ...

  
# but if you really want a list we can `split` the matrix into 
# individual rows:
split(result, 1:nrow(result))
# $`1`
# [1] "Combined_t2|t1_lag8" "mean_RT_200_all"    
# 
# $`2`
# [1] "Combined_abmag_t2_lag8_minus_lag3" "mean_RT_200_all"                  
# 
# $`3`
# [1] "Combined_abmag_t2_1.0_minus_lag3" "mean_RT_200_all"                 
# ...

उपरोक्त इसे करने का फैंसी (और स्केलेबल) तरीका है - यह इस त्वरित और गंदे तरीके के बराबर है:

result = rbind(
  expand.grid(x = na.omit(dd$AB), y = na.omit(dd$PRP)),
  expand.grid(x = na.omit(dd$AB), y = na.omit(dd$DUAL)),
  expand.grid(x = na.omit(dd$PRP), y = na.omit(dd$DUAL))
)

split(as.matrix(unname(result)), 1:nrow(result))