Removing certain rows whose column value does not match another column (all within the same data frame) - r

Question

I'm attempting to remove all of the rows (cases) within a data frame in which a certain column's value does not match another column value.
The data frame bilat_total contains these 10 columns/variables:
bilat_total[,c("year", "importer1", "importer2", "flow1",
"flow2", "country", "imports", "exports", "bi_tot",
"mother")]
Thus the table's head is:
year importer1 importer2 flow1 flow2 country
6 2009 Afghanistan Bhutan NA NA Afghanistan
11 2009 Afghanistan Solomon Islands NA NA Afghanistan
12 2009 Afghanistan India 516.13 120.70 Afghanistan
13 2009 Afghanistan Japan 124.21 0.46 Afghanistan
15 2009 Afghanistan Maldives NA NA Afghanistan
19 2009 Afghanistan Bangladesh 4.56 1.09 Afghanistan
imports exports bi_tot mother
6 6689.35 448.25 NA United Kingdom
11 6689.35 448.25 NA United Kingdom
12 6689.35 448.25 1.804361e-02 United Kingdom
13 6689.35 448.25 6.876602e-05 United Kingdom
15 6689.35 448.25 NA United Kingdom
19 6689.35 448.25 1.629456e-04 United Kingdom
I've attempted to remove all the cases in which importer2 do not match mother by making a subset:
subset(bilat_total, importer2 == mother)
But each time I do, I get the error:
Error in Ops.factor(importer2, mother) : level sets of factors are different
How would I go about dropping all the rows/cases in which importer 2 and mother don't match?

Answer 1

The error may be because the columns are factor class. We can convert the columns to character class and then compare to subset the rows.
subset(bilat_total, as.character(importer2) == as.character(mother))
Based on the data example showed
subset(bilat_total, importer2 == mother)
# Error in Ops.factor(importer2, mother) :
# level sets of factors are different