CODEWITHSUNDEEP
r
user3642360
user3642360

Reputation: 792

Find frequency of an element in a matrix in R

I have dataset "data" with 7 rows and 4 columns, as follows:

var1       var2    var3    var4
    A        C      
    A        C       B  
    B        A       C       D
    D        B  
             B  
    D        B      
    B        C

I want to create following table "Mat" based on the data I have:

A   B   C   D
1       1   
1   1   1   
1   1   1   1
    1       1
    1       
    1       1
    1   1   1

Basically, I have taken unique elements from the original data and create a matrix "Mat" where number of rows in Mat=number of rows in Data and number of columns in "Mat"=number of unique elements in Data (that is, A, B, C, D)

I wrote following code in R:

 rule <-c("A","B","C","D")

 mat<-matrix(, nrow = dim(data)[1], ncol = dim(rule)[1])

 mat<-data.frame(mat)

 x<-rule[,1]

 nm<-as.character(x)

 names(mat)<-nm

 n_data<-dim(data)[1]

 for(i in 1:n_data)

    {

      for(j in 2:dim(data)[2])

            {

                  for(k in 1:dim(mat)[2])

                    {

                          ifelse(data[i,j]==names(mat)[k],mat[i,k]==1,0)

                  }

          }

   }

I am getting all NA in "mat". Also, the running time is too much because in my original data set I have 20,000 rows and 100 columns in "Mat".

Any advice will be highly appreciated. Thanks!

Upvotes: 1

Views: 411

Answers (2)

BENY
BENY

Reputation: 323366

By using table and rep

table(rep(1:nrow(df),dim(df)[2]),unlist(df))
  A B C D
1 1 0 1 0
2 1 1 1 0
3 1 1 1 1
4 0 1 0 1
5 0 1 0 0
6 0 1 0 1
7 0 1 1 0

Upvotes: 3

C. Braun
C. Braun

Reputation: 5211

This should be faster than the nested for loops:

> sapply(c("A", "B", "C", "D"), function(x) { rowSums(df == x, na.rm = T) })
#      A B C D
# [1,] 1 0 1 0
# [2,] 1 1 1 0
# [3,] 1 1 1 1
# [4,] 0 1 0 1
# [5,] 0 1 0 0
# [6,] 0 1 0 1
# [7,] 0 1 1 0

Data

df <- read.table(text = "var1       var2    var3    var4
                         A          C       NA      NA
                         A          C       B       NA
                         B          A       C       D
                         D          B       NA      NA
                         NA         B       NA      NA
                         D          B       NA      NA
                         B          C       NA      NA", header = T, stringsAsFactors = F)

Upvotes: 3

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