Filtering rows which satisfy a condition per group in r

Question

I have a big dataframe and I want to remove all rows if the number of rows for a given group based on a column in this datafram is less than a given number. Here is an example:

x=1:6; y=c("A","B","B","B","C","C")
df<- data.frame(x,y)

If I group by variable y, I have three rows that belong to group "B". Here I want to remove all rows that don't satisfy this condition (<3 rows). Expected output:

df
  x y
1 2 B
2 3 B
3 4 B

Is there an easy way to do this?

Answer 1

We can use dplyr::filter() and count the number of row in each group using dplyr::n()

library(dplyr)

df %>% 
  group_by(y) %>% 
  filter(n()>2)

Answer 2

Another option is

library(data.table)
setDT(df)[, .SD[.N >2], by  = y]

Answer 3

Using base R

t <- table(df$y)
df[df$y %in% names(t[t > 2]), ]

  x y
2 2 B
3 3 B
4 4 B

Answer 4

Here's a base R solution using the split, apply, combine approach:

do.call(rbind, lapply(split(df, df$y), function(i) if(nrow(i) >= 3) { i }))

Answer 5

Here is a base R solution which used ave()

res <-df[ave(seq(nrow(df)),df$y,FUN = length)>=3,]

and you will get

> res
  x y
2 2 B
3 3 B
4 4 B