[R] Best way to do temporal joins in R?

[Gabor Grothendieck]

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On Mon, Mar 16, 2009 at 3:11 PM, Jonathan Greenberg
<greenberg at ucdavis.edu> wrote:
> Sorry for the immediate follow-up, but Phil Spector correctly reminded me
> this is a lot easier for the community I provide some sample data, so I'm
> attaching 3 small CSVs to this email:
>
> species_data_Rexample.csv contains the "field data" (which species was ID'd
> and what time it was ID'd),
> temperature_data_Rexample.csv contains the date, time, station ID and the
> temperature "value"
>
> I'd like a dataframe which contains for each unique line in
> species_data_Rexample.csv, a series of lines, one per station, and the
> temperature of the nearest time stamp, or an interpolated value (weighted
> average would be fine, but so would just grabbing the nearest value), so for
> this example I'd like something that looks like the csv
> "fused_data_Rexample.csv"
>
> Thanks!
>
> --j
>
> Jonathan Greenberg wrote:
>>
>> I've been playing with zoo a bit, and it seems ok except it doesn't
>> support non-unique time stamps when performing joins.  I have two databases
>> which contain a dataframe of a Date object (with the time, not just
>> MM/DD/YY), e.g.:
>>
>> DB 1:
>> UniqueID,Date1,Data 1,Data 2
>>
>> DB 2:
>> Date2, Station, Data 3
>>
>> We'll say Station can contain three values: A,B and C
>>
>> DB 1 may have some repeat times, and DB 2 definitely has them -- although
>> each Date, Station combo is unique (this DB contains weather data collected
>> on the half-hour or fifteen minute interval at a set of stations).  I'd like
>> DB2's station and Data3 to be joined with DB1 based on the nearest time
>> stamp (interpolating Data3 or not).
>>
>> Ideally, I'd like a fused database such that I get for each uniqueID in
>> DB1:
>>
>> UniqueID,Date,Data1,Data2,Station,Data3
>>
>> Thoughts?  Hints?
>>
>> --j
>>
>>
>>
>
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