CODEWITHSUNDEEP
ralgorithmdataframeiterationcombinatorics
Jonathan Rhein
Jonathan Rhein

Reputation: 1723

Iterate over all possible combinations of columns and rows in a dataframe

I am looking for some way of iterating over all possible combinations of columns and rows in a numerical dataframe. So it could possibly look like this (just a few of the many possible combinations there could be):

For each combination of columns and rows a simple mathematical calculation shall be carried out and its result shall be stored to a dataframe result. This way I want to eventually find the combination of columns and rows that yields the highest/lowest calculation result.

So my code looks like this (with respect to the calculation):

calc = sum(sum(colSums(data)) + sum(rowSums(data)) / (nrow(data) * ncol(data)))

So my questions are:

  1. How do I create this iterating process in r-code, i.e. the process of trying all possible combinations? I thought of using two nested for()-loops, but I am not sure wether this will work (especially how do I address the columns/rows without knowing their names and their number)
  2. How can I finally store all the results to a single dataframe result? result should contain the calculation result and the respective combination of columns and rows.

Do you have any ideas how I could solve this?

Here is some data to play around with:

data = structure(list(GDP = c(18.2, 8.5, 54.1, 1.4, 2.1, 83.6, 17), 
    Population = c(1.22, 0.06, 0, 0.54, 2.34, 0.74, 1.03), Birth.rate = c(11.56, 
    146.75, 167.23, 7, 7, 7, 10.07), Income = c(54, 94, 37, 95, 
    98, 31, 78), Savings = c(56.73, 56.49, 42.81, 70.98, 88.24, 
    35.16, 46.18)), .Names = c("GDP", "Population", "Birth.rate", 
    "Income", "Savings"), class = "data.frame", row.names = c(NA, 
    -7L))

Upvotes: 2

Views: 1317

Answers (1)

zx8754
zx8754

Reputation: 56219

I am not fully following what we are trying to achieve, maybe this is a start:

library(data.table)

cc <- 1:ncol(data)
rr <- 1:nrow(data)

rbindlist(
  lapply(cc, function(i){
    ccN <- combn(cc, i)
    rbindlist(
      apply(ccN, 2, function(iN){
        rbindlist(
          lapply(rr, function(j){
            rrN <- combn(rr, j)
            rbindlist(
              apply(rrN, 2, function(jN){
                data.frame(
                  Sum = sum(c(
                    unlist(data[jN, ]),
                    unlist(data[, iN]))),
                  Desc = paste(c("rows",jN,"cols",iN), collapse = ",")
                )
              })
            )
          })
        )
      })
    )
  })
)


#          Sum                              Desc
#   1:  326.61                     rows,1,cols,1
#   2:  490.70                     rows,2,cols,1
#   3:  486.04                     rows,3,cols,1
#   4:  359.82                     rows,4,cols,1
#   5:  382.58                     rows,5,cols,1
#  ---                                          
#3933: 2687.14   rows,1,2,3,5,6,7,cols,1,2,3,4,5
#3934: 2560.92   rows,1,2,4,5,6,7,cols,1,2,3,4,5
#3935: 2556.26   rows,1,3,4,5,6,7,cols,1,2,3,4,5
#3936: 2720.35   rows,2,3,4,5,6,7,cols,1,2,3,4,5
#3937: 2862.06 rows,1,2,3,4,5,6,7,cols,1,2,3,4,5

Upvotes: 1

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