I have a data.frame called world. This data frame lists countries in column name.y, I have a column for languages named languages. I need to List the names of countries where more than 4 languages are spoken.

My first take on this is to aggregate country and languages.

language <- data.frame(table(World$name.y,World$language))

when I run head(language) it doesn't work out.

  • $\begingroup$ library(data.table); as.data.table(World)[, .(n=length(unique(language))),by=.(country)][n>=4,] $\endgroup$
    – Valentas
    Commented Dec 6, 2018 at 7:36
  • $\begingroup$ Sorry, but there was an error with this one. Error in [.data.table(as.data.table(World), , .(n = length(unique(language))), : column or expression 1 of 'by' or 'keyby' is type list. Do not quote column names. Usage: DT[,sum(colC),by=list(colA,month(colB))] $\endgroup$
    – Chris Kehl
    Commented Dec 6, 2018 at 11:52

1 Answer 1


The dplyr package should be useful for this.


World %>%
  group_by(name) %>%
  mutate(num_distinct_languages = n_distinct(language)) %>%
  filter(num_distinct_lanagues > 4)

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