[R] identify duplicate entries in data frame and calculate mean
Matthew
mccormack at molbio.mgh.harvard.edu
Tue May 24 22:36:26 CEST 2016
Thanks, Tom. I was making a mistake looking at your example and that's
what my problem was.
Cool answer, works great. Thank you very much.
Matthew
On 5/24/2016 4:23 PM, Tom Wright wrote:
> Don't see that as being a big problem. If your data grows then dplyr
> supports connections to external databases. Alternately if you just
> want a mean, most databases can do that directly in SQL.
>
> On Tue, May 24, 2016 at 4:17 PM, Matthew
> <mccormack at molbio.mgh.harvard.edu
> <mailto:mccormack at molbio.mgh.harvard.edu>> wrote:
>
> 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
>> <mccormack at molbio.mgh.harvard.edu
>> <mailto:mccormack at 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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>>
>>
>
>
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