Thank you very much, Tom.
This gets me thinking in the right direction.
One thing I should have mentioned that I did not is that the number of
rows in the data frame will be a little over 40,000 rows.
On 5/24/2016 4:08 PM, Tom Wright wrote:
> Using dplyr
>
> $ library(dplyr)
> $ x<-data.frame(Length=c(321,350,340,180,198),
> ID=c(rep('A234',3),'B123','B225') )
> $ x %>% group_by(ID) %>% summarise(m=mean(Length))
>
>
>
> On Tue, May 24, 2016 at 3:46 PM, Matthew
> <mccorm...@molbio.mgh.harvard.edu
> <mailto:mccorm...@molbio.mgh.harvard.edu>> wrote:
>
> I have a data frame with 10 columns.
> In the last column is an alphaneumaric identifier.
> For most rows, this alphaneumaric identifier is unique to the
> file, however some of these alphanemeric idenitifiers occur in
> duplicate, triplicate or more. When they do occur more than once
> they are in consecutive rows, so when there is a duplicate or
> triplicate or quadruplicate (let's call them multiplicates), they
> are in consecutive rows.
>
> In column 7 there is an integer number (may or may not be unique.
> does not matter).
>
> I want to identify each multiple entries (multiplicates) occurring
> in column 10 and then for each multiplicate calculate the mean of
> the integers column 7.
>
> As an example, I will show just two columns:
> Length Identifier
> 321 A234
> 350 A234
> 340 A234
> 180 B123
> 198 B225
>
> What I want to do (in the above example) is collapse all the
> A234's and report the mean to get this:
> Length Identifier
> 337 A234
> 180 B123
> 198 B225
>
>
> Matthew
>
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