Maximum Maxima!

J, 27 bytes


This is a monadic verb, used as follows in the case of the second example:

   f =: ((I.@:=;])>./)@(+/@:=>./"1)
   m =: 3 2 $ 7 93 69 35 77 77
   f m
|0 1|1|

The output consists of two boxes, and uses 0-based indexing. Try it here!


((I.@:=;])>./)@(+/@:=>./"1)  Input is m.
(            )@(          )  Composition: apply right hand side, then left hand side.
                     >./"1   Take maximum of each row of m.
                    =        Replace row maxima by 1 and other values by 0,
                +/@:         then take sum (number of maxima) on each column.
                             The result is the array of number of row maxima in each column.
          >./                Compute the maximum of this array
 (     ;])                   and put it in a box with
  I.@:=                      the indices of those entries that are equal to it.

Pyth, 20 19 17 bytes

1 byte thanks to @Suever.

1 byte thanks to @Jakube.


Test suite.

Output is 0-indexed.

Order is reversed.

All inputs


All outputs

[[2], [0]]

[[2], [0, 1]]

[[2], [3]]

[[1], [0, 1, 3]]

[[1], [0, 1, 2, 3]]

[[1], [0, 3]]

[[4], [0]]

[[1], [0]]

How it works


               Q   Yield input.
           L       For each array in input (as d):
            eSd      Yield maximum of d.
          x          Yield the 0-indexed indices of the maximum in d.
         s          Flatten.
        S           Sort.
       r         8  Run-length encoding.
                    Now the array is:
                      [number of maxima in column, index of column]
                      for all the columns
   .MhZ             Yield the sub-arrays whose first element is maximum.
                     The first element of each sub-array
                     is "number of maxima in column".
                     Now the array is:
                       [number of maxima in column, index of column]
                       for all the required columns
  C                 Transpose.
                    Now the array is:
                      [[number of maxima in each column],
                       [index of each required column]]
                    Note that every element in the
                    first sub-array is the same.
{M                  Deduplicate each.

MATL, 17 bytes


The first output is the max number of maxima and the second output is the columns in which this occured (1-based indexing).

Try it Online!


v       % Vertically concatenate everything on the stack (nothing), yields []
        % Implicitly grab the input
H       % Push the number 2 to the stack
3$X>    % Compute the maximum value of each row (along the second dimension)
G       % Explicitly grab input again
=       % Compare each row of the input to the row-wise max (automatically broadcasts). 
Xs      % Sum the number of matches in each column
t       % Duplicate the array
X>      % Determine the max number of maxima in all columns
t       % Duplicate this value
b=f     % Find the index of the columns which had the maximum number of maxima
        % Implicitly display stack contents