根据R中的条件获取data.frame的行列名

Question

This is probably much easier than I am making it. It is one of those little problems which hangs you up and you wonder why.

Given dataframe as so:

a <- c(1,2,3)
b <- c(4,5,6)
test.df <- data.frame(a,b)

How could one use iterate through the values in each column and return the column name and row name if the value = '1'?

Something like this:

for (i in test.df) {
    for (j in i) {
        if (i == 1) {
            print(rowname,columnname)
            }
        }
    }  
}  

Where rowname and columnname are actual values.

Answer 1

Using which and arr.ind=T is a way:

Example Data

a <- c(1,2,3)
b <- c(4,5,6)
test.df <- data.frame(a,b)

Solution and Output

#test.df==1 gives a TRUE/FALSE matrix
#which with the arr.ind argument=TRUE gives the row/col of the TRUE elements
a <- which(test.df==1,arr.ind=T)

> a
     row col
[1,]   1   1

And then you use the above to get the row and column names:

> row.names(test.df[a[,1],] ) #row names
[1] "1"

> names(test.df[a[,2]])       #column names
[1] "a"

Answer 2

Another approach:

> col = colnames(test.df)[apply(test.df, 2, function(u) any(u==1))]
> col
[1] "a"
> row = row.names(test.df)[apply(test.df, 1, function(u) any(u==1))]
> row
[1] "1"

Answer 3

This is an old thread but I am not very satisfied with the previous solutions.

For me the most intuitive is:

row.names(data)[which(data$feature1==value)]

Which is basically saying: Given the row names of all the data give me those where a given condition is satisfied.