This is a convenient wrapper that uses filter()
and
min_rank()
to select the top or bottom entries in each group,
ordered by wt
.
top_n(x, n, wt)
a tbl()
to filter
number of rows to return. If x
is grouped, this is the
number of rows per group. Will include more than n
rows if
there are ties.
If n
is positive, selects the top n
rows. If negative,
selects the bottom n
rows.
# NOT RUN { df <- data.frame(x = c(10, 4, 1, 6, 3, 1, 1)) df %>% top_n(2) # Negative values select bottom from group. Note that we get more # than 2 values here because there's a tie: top_n() either takes # all rows with a value, or none. df %>% top_n(-2) if (require("Lahman")) { # Find 10 players with most games # A little nicer with %>% tbl_df(Batting) %>% group_by(playerID) %>% tally(G) %>% top_n(10) # Find year with most games for each player tbl_df(Batting) %>% group_by(playerID) %>% top_n(1, G) } # }
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