Is there a way to loop through a matrix/df in R to create an adjacency matrix?

问题

I am trying to loop through 53 rows in a data.frame and create an adjacency matrix with the results. However, my efforts continue to be stalled by the fact that the loop will not run correctly.

I have tried to create matches as well as applying numerous count() functions, without success.

MRE: (In truth, the data is a lot larger so my unique search is actually 217k elements)

df1<-data.frame(col1=c(12345,123456,1234567,12345678),
col2=c(54321,54432,12345,76543),
col3=c(11234,12234,1234567,123345),
col4=c(54321,54432,12345,76543))

search<-c(12345,1234567,75643,54432)

I would like to loop through each row and update a new matrix/df where the count per number in [search] would be the output.

Ex:

df2

        12345     1234567    75643    54432
row1    TRUE       TRUE      FALSE    FALSE
row2    FALSE      FALSE     TRUE      TRUE
row3    TRUE       TRUE      FALSE    FALSE
row4    TRUE       FALSE     TRUE     TRUE

回答1:

While it is unclear how your counts are derived as there might even be a typo (75643 != 76543) or if you are running by rows or columns, consider a nested sapply and apply solution for both margins:

By Row

search <- c(12345, 1234567, 76543, 54432)                                # ADJUSTED TYPO    
mat <- sapply(search, function(s) apply(df1, 1, function(x) s %in% x))   # 1 FOR ROW MARGIN

colnames(mat) <- search
rownames(mat) <- paste0("row", seq(nrow(df1)))

mat
#      12345 1234567 76543 54432
# row1  TRUE   FALSE FALSE FALSE
# row2 FALSE   FALSE FALSE  TRUE
# row3  TRUE    TRUE FALSE FALSE
# row4 FALSE   FALSE  TRUE FALSE

By Column

search <- c(12345, 1234567, 76543, 54432)                                # ADJUSTED TYPO
mat <- sapply(search, function(s) apply(df1, 2, function(x) s %in% x))   # 2 FOR COL MARGIN

colnames(mat) <- search
rownames(mat) <- paste0("col", seq(ncol(df1)))

mat
#      12345 1234567 76543 54432
# col1  TRUE    TRUE FALSE FALSE
# col2  TRUE   FALSE  TRUE  TRUE
# col3 FALSE    TRUE FALSE FALSE
# col4  TRUE   FALSE  TRUE  TRUE

Rextester demo

回答2:

I think you should check the tf (term frequency) algorithm for text mining. Here an interesting approach for your example using the library(quanteda) to create the matrix with the counts. Then you can do the searches you feel like based on counts:

library("tibble")
library("quanteda")


df1<-data.frame(col1=c(12345,123456,1234567,12345678),
                col2=c(54321,54432,12345,76543),
                col3=c(11234,12234,1234567,123345),
                col4=c(54321,54432,12345,76543))
df2<-apply(df1,2,paste, collapse = " ") # Passing it to string format
DocTerm <- quanteda::dfm(df2)
DocTerm

Document-feature matrix of: 4 documents, 10 features (60.0% sparse).
4 x 10 sparse Matrix of class "dfm"
      features
docs   12345 123456 1234567 12345678 54321 54432 76543 11234 12234 123345
  col1     1      1       1        1     0     0     0     0     0      0
  col2     1      0       0        0     1     1     1     0     0      0
  col3     0      0       1        0     0     0     0     1     1      1
  col4     1      0       0        0     1     1     1     0     0      0

I hope this helps !

来源：https://stackoverflow.com/questions/56775324/is-there-a-way-to-loop-through-a-matrix-df-in-r-to-create-an-adjacency-matrix

标签

loops

apply