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    <pre><code># start with the mtcars data frame (included with your installation of R) mtcars # pick your 'group by' variable gbv &lt;- 'cyl' # IMPORTANT NOTE: you can only include one group by variable here # ..if you need more, the `order` function below will need # one per inputted parameter: order( x$cyl , x$am ) # choose whether you want to find the minimum or maximum find.maximum &lt;- FALSE # create a simple data frame with only two columns x &lt;- mtcars # order it based on x &lt;- x[ order( x[ , gbv ] , decreasing = find.maximum ) , ] # figure out the ranks of each miles-per-gallon, within cyl columns if ( find.maximum ){ # note the negative sign (which changes the order of mpg) # *and* the `rev` function, which flips the order of the `tapply` result x$ranks &lt;- unlist( rev( tapply( -x$mpg , x[ , gbv ] , rank ) ) ) } else { x$ranks &lt;- unlist( tapply( x$mpg , x[ , gbv ] , rank ) ) } # now just subset it based on the rank column result &lt;- x[ x$ranks &lt;= 3 , ] # look at your results result # done! # but note only *two* values where cyl == 4 were kept, # because there was a tie for third smallest, and the `rank` function gave both '3.5' x[ x$ranks == 3.5 , ] # ..if you instead wanted to keep all ties, you could change the # tie-breaking behavior of the `rank` function. # using the `min` *includes* all ties. using `max` would *exclude* all ties if ( find.maximum ){ # note the negative sign (which changes the order of mpg) # *and* the `rev` function, which flips the order of the `tapply` result x$ranks &lt;- unlist( rev( tapply( -x$mpg , x[ , gbv ] , rank , ties.method = 'min' ) ) ) } else { x$ranks &lt;- unlist( tapply( x$mpg , x[ , gbv ] , rank , ties.method = 'min' ) ) } # and there are even more options.. # see ?rank for more methods # now just subset it based on the rank column result &lt;- x[ x$ranks &lt;= 3 , ] # look at your results result # and notice *both* cyl == 4 and ranks == 3 were included in your results # because of the tie-breaking behavior chosen. </code></pre>
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    1. POhow to find the top N values by group or within category (groupwise) in an R data.frame
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    1. USAnthony Damico
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    1. CO@Arun ..there's no other choice? :) ps thanx for your awesome answer
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    2. COThis is way complicated for such a simple task!
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    3. CO@Arun I down voted because it seems way too complicated, as I complained about in my comment above. Maybe I'm just a bit cranky after spending hours shoveling my driveway...
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