r - Find the largest product in a dataframe -

i have dataframe , need find largest product in data frame in same direction(up, down, left, right, or diagonally).

the dataframe follows:

structure(list(v1 = c(8l, 49l, 81l, 52l, 22l, 24l, 32l, 67l,  24l, 21l, 78l, 16l, 86l, 19l, 4l, 88l, 4l, 20l, 20l, 1l), v2 = c(2l,  49l, 49l, 70l, 31l, 47l, 98l, 26l, 55l, 36l, 17l, 39l, 56l, 80l,  52l, 36l, 42l, 69l, 73l, 70l), v3 = c(22l, 99l, 31l, 95l, 16l,  32l, 81l, 20l, 58l, 23l, 53l, 5l, 0l, 81l, 8l, 68l, 16l, 36l,  35l, 54l), v4 = c(97l, 40l, 73l, 23l, 71l, 60l, 28l, 68l, 5l,  9l, 28l, 42l, 48l, 68l, 83l, 87l, 73l, 41l, 29l, 71l), v5 = c(38l,  17l, 55l, 4l, 51l, 99l, 64l, 2l, 66l, 75l, 22l, 96l, 35l, 5l,  97l, 57l, 38l, 72l, 78l, 83l), v6 = c(15l, 81l, 79l, 60l, 67l,  3l, 23l, 62l, 73l, 0l, 75l, 35l, 71l, 94l, 35l, 62l, 25l, 30l,  31l, 51l), v7 = c(0l, 18l, 14l, 11l, 63l, 45l, 67l, 12l, 99l,  76l, 31l, 31l, 89l, 47l, 99l, 20l, 39l, 23l, 90l, 54l), v8 = c(40l,  57l, 29l, 42l, 89l, 2l, 10l, 20l, 26l, 44l, 67l, 47l, 7l, 69l,  16l, 72l, 11l, 88l, 1l, 69l), v9 = c(0l, 60l, 93l, 69l, 41l,  44l, 26l, 95l, 97l, 20l, 15l, 55l, 5l, 28l, 7l, 3l, 24l, 34l,  74l, 16l), v10 = c(75l, 87l, 71l, 24l, 92l, 75l, 38l, 63l, 17l,  45l, 94l, 58l, 44l, 73l, 97l, 46l, 94l, 62l, 31l, 92l), v11 = c(4l,  17l, 40l, 68l, 36l, 33l, 40l, 94l, 78l, 35l, 3l, 88l, 44l, 92l,  57l, 33l, 72l, 99l, 49l, 33l), v12 = c(5l, 40l, 67l, 56l, 54l,  53l, 67l, 39l, 78l, 14l, 80l, 24l, 37l, 13l, 32l, 67l, 18l, 69l,  71l, 48l), v13 = c(7l, 98l, 53l, 1l, 22l, 78l, 59l, 63l, 96l,  0l, 4l, 0l, 44l, 86l, 16l, 46l, 8l, 82l, 48l, 61l), v14 = c(78l,  43l, 88l, 32l, 40l, 36l, 54l, 8l, 83l, 61l, 62l, 17l, 60l, 52l,  26l, 55l, 46l, 67l, 86l, 43l), v15 = c(52l, 69l, 30l, 56l, 40l,  84l, 70l, 40l, 14l, 33l, 16l, 54l, 21l, 17l, 26l, 12l, 29l, 59l,  81l, 52l), v16 = c(12l, 48l, 3l, 71l, 28l, 20l, 66l, 91l, 88l,  97l, 14l, 24l, 58l, 77l, 79l, 32l, 32l, 85l, 16l, 1l), v17 = c(50l,  4l, 49l, 37l, 66l, 35l, 18l, 66l, 34l, 34l, 9l, 36l, 51l, 4l,  33l, 63l, 40l, 74l, 23l, 89l), v18 = c(77l, 56l, 13l, 2l, 33l,  17l, 38l, 49l, 89l, 31l, 53l, 29l, 54l, 89l, 27l, 93l, 62l, 4l,  57l, 19l), v19 = c(91l, 62l, 36l, 36l, 13l, 12l, 64l, 94l, 63l,  33l, 56l, 85l, 17l, 55l, 98l, 53l, 76l, 36l, 5l, 67l), v20 = c(8l,  0l, 65l, 91l, 80l, 50l, 70l, 21l, 72l, 95l, 92l, 57l, 58l, 40l,  66l, 69l, 36l, 16l, 54l, 48l)), .names = c("v1", "v2", "v3",  "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13",  "v14", "v15", "v16", "v17", "v18", "v19", "v20"), class = "data.frame", row.names = c(na,  -20l)) 

the dataframe looks this:

> newjd    v1 v2 v3 v4 v5 v6 v7 v8 v9 v10 v11 v12 v13 v14 v15 v16 v17 v18 v19 v20 1   8  2 22 97 38 15  0 40  0  75   4   5   7  78  52  12  50  77  91   8 2  49 49 99 40 17 81 18 57 60  87  17  40  98  43  69  48   4  56  62   0 3  81 49 31 73 55 79 14 29 93  71  40  67  53  88  30   3  49  13  36  65 4  52 70 95 23  4 60 11 42 69  24  68  56   1  32  56  71  37   2  36  91 5  22 31 16 71 51 67 63 89 41  92  36  54  22  40  40  28  66  33  13  80 6  24 47 32 60 99  3 45  2 44  75  33  53  78  36  84  20  35  17  12  50 7  32 98 81 28 64 23 67 10 26  38  40  67  59  54  70  66  18  38  64  70 8  67 26 20 68  2 62 12 20 95  63  94  39  63   8  40  91  66  49  94  21 9  24 55 58  5 66 73 99 26 97  17  78  78  96  83  14  88  34  89  63  72 10 21 36 23  9 75  0 76 44 20  45  35  14   0  61  33  97  34  31  33  95 11 78 17 53 28 22 75 31 67 15  94   3  80   4  62  16  14   9  53  56  92 12 16 39  5 42 96 35 31 47 55  58  88  24   0  17  54  24  36  29  85  57 13 86 56  0 48 35 71 89  7  5  44  44  37  44  60  21  58  51  54  17  58 14 19 80 81 68  5 94 47 69 28  73  92  13  86  52  17  77   4  89  55  40 15  4 52  8 83 97 35 99 16  7  97  57  32  16  26  26  79  33  27  98  66 16 88 36 68 87 57 62 20 72  3  46  33  67  46  55  12  32  63  93  53  69 17  4 42 16 73 38 25 39 11 24  94  72  18   8  46  29  32  40  62  76  36 18 20 69 36 41 72 30 23 88 34  62  99  69  82  67  59  85  74   4  36  16 19 20 73 35 29 78 31 90  1 74  31  49  71  48  86  81  16  23  57   5  54 20  1 70 54 71 83 51 54 69 16  92  33  48  61  43  52   1  89  19  67  48 

any suggestion highly appreciated.

m <- as.matrix(df) ll <- c(lapply(1:20, function(x) row(m)==x),                 ## rows         lapply(1:20, function(x) col(m)==x),                 ## columns         lapply(-19:19, function(x) (col(m)+x)==row(m)),      ## nw-se diagonals         lapply(-19:19, function(x) (col(m)+x)==(21-row(m)))) ## sw-ne diagonals ## calculate product of each row, column, , diagonal pp <- sapply(ll, function(x) prod(m[x])) max(pp) # [1] 1.824798e+35 m[ll[[which.max(pp)]]] # [1] 75 87 71 24 92 75 38 63 17 45 94 58 44 73 97 46 94 62 31 92 

or, more generally:

maxprodelements <- function(m) {     mm <- nrow(m)     nn <- ncol(m)     ll <- c(lapply(seq_len(mm), function(x) which(row(m)==x)),             lapply(seq_len(nn), function(x) which(col(m)==x)),             lapply((-mm+1):(nn-1), function(x) which(col(m)==(row(m)+x))),             lapply((-mm+1):(nn-1), function(x) which((nn+1-col(m))==(row(m)+x))))     pp <- sapply(ll, function(x) prod(m[x]))     ll[[which.max(pp)]] }  ## try 2 5 matrix m <- matrix(1:10, ncol=5) m[maxprodelements(m)] # [1]  2  4  6  8 10 prod(m[maxprodelements(m)]) # [1] 3840