To Find Most Frequently Occuring Element in Matrix in R

to find most frequently occuring element in matrix in R

Set up some test data.

> (image = matrix(sample(1:10, 100, replace = TRUE), nrow = 10))
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    4    4    2    7    2    2    3    8    2     5
 [2,]    7    3    2    6    6    5    7    8    1     3
 [3,]    7    5    7    9    4    9    4    8    2     7
 [4,]    5    3    4    2    1    5    9   10    9     5
 [5,]    9   10    7    2    7    4    9    1    1     9
 [6,]    2    3    5    1    2    8    1    5    9     4
 [7,]    5    4   10    5    9   10    1    6    1    10
 [8,]    6    3    9    7    1    1    9    2    1     7
 [9,]    5    9    4    8    9    9    5   10    5     4
[10,]   10    1    4    7    3    2    3    5    4     5

Do it manually.

> table(image)
image
 1  2  3  4  5  6  7  8  9 10 
12 12  8 12 15  4 11  5 14  7 

Here we can see that the value 5 appeared most often (15 times). To get the same results programmatically:

> which.max(table(image))
5 
5 

Most frequent element per column

It can be done in base like this:

 sapply(1:ncol(example), function(x) rev(tail(names(sort(table(example[,x]))), 2)))

And if you want to know the frequencies then just ignore names():

sapply(1:ncol(example), function(x) rev(tail(sort(table(example[,x])), 2)))

Find the n most common values in a vector

I'm sure this is a duplicate, but the answer is simple:

sort(table(variable),decreasing=TRUE)[1:3]

Identify most frequent row from matrix

> (mat <- matrix(c(rep(c(0,1),3),rep(c(1,0),2)),5, byrow=TRUE))
     [,1] [,2]
[1,]    0    1
[2,]    0    1
[3,]    0    1
[4,]    1    0
[5,]    1    0

do get the row:

while(anyDuplicated(mat)>0) {
    mat <- mat[duplicated(mat),]
    if (class(mat)=="numeric") break
}

Result:

> mat
[1] 0 1

Find the most frequent value by row

Something like :

apply(df,1,function(x) names(which.max(table(x))))
[1] "red"    "yellow" "green" 

In case there is a tie, which.max takes the first max value. From the
which.max help page :

Determines the location, i.e., index of the (first)
minimum or maximum of a numeric vector.

Ex :

var4 <- c("yellow","green","yellow")
df <- data.frame(cbind(id, var1, var2, var3, var4))

> df
  id   var1   var2   var3   var4
1  1    red    red yellow yellow
2  2 yellow yellow orange  green
3  3  green  green  green yellow

apply(df,1,function(x) names(which.max(table(x))))
[1] "red"    "yellow" "green" 

Most frequent element in matrix

Your algorithm does not work for the 1D matrix, but once fixed, it can be used for the 2D matrix unchanged:

#include <stdio.h>

double find_most_frequent(const double *arr, size_t vel) {
    size_t i, j, maxcount = 0, mostfreq = 0;
    
    for (i = 0; i < vel; i++) {
        size_t count = 1;
        for (j = i + 1; j < vel; j++) {
            if (arr[i] == arr[j]) {
                count++;
        }
        if (maxcount < count || (maxcount == count && arr[mostfreq] > arr[i])) {
            maxcount = count;
            mostfreq = i;
        }
    }
    return arr[mostfreq];
} 

#define ROWS  3
#define COLS  4

int main() {
    double mat[ROWS][COLS];
    double arr[] = { 1.3, 4.2, 1.3, 5, 4.2, 6.8, 3.7 };

    for (int i = 0; i < ROWS; i++) {
        for (int j = 0; j < COLS; j++) {
            if (scanf("%lf", &mat[i][j]) != 1)
                return 1;
        }
    }
    printf("Most frequent in array is: %g\n", find_most_frequent(arr, sizeof(arr) / sizeof(arr[0]));
    printf("Most frequent in matrix is: %g\n", find_most_frequent(&mat[0][0], sizeof(mat) / sizeof(mat[0][0]));
    return 0;
}

How to calculate most frequent occurring terms/words in a document collection/corpus using R?

You can use

sorted.sums[sorted.sums > 5][1:4]

But if you have at least 4 values that are greater than 5 only using sorted.sums[1:4] should work as well.

To get the words you can use names.

names(sorted.sums[sorted.sums > 5][1:4])

Find the most frequent value in a column and take a subset of that

You can use subset

 indx <- tail(names(sort(table(df1$Value))),1)
 subset(df1, Value==indx)

Or using dplyr

 library(dplyr)
 df1 %>% 
   group_by(Value) %>% 
   mutate(N=n()) %>%
   ungroup() %>% 
   filter(N==max(N))

Or

  library(data.table)
  setDT(df1)[, N:=.N, Value][N==max(N)][, N:=NULL]

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