Data manipulation: transforming SQL query in an appropriate dataframe
Correcting the inconsistencies in the data, try this
(and also see ?reshape and the reshape package for
other approaches):
DF <- structure(list(Id = 1:4, Fund = structure(c(1L, 1L, 2L, 2L),
.Label = c("Fund01",
"Fund02"), class = "factor"), Return = c(0.5, 0.4, -0.3, -0.4
), Period = structure(c(2L, 1L, 2L, 1L), .Label = c("june/08",
"may/08"), class = "factor")), .Names = c("Id", "Fund", "Return",
"Period"), class = "data.frame", row.names = c(NA, -4L))
DF
tapply(DF$Return, DF[c(2, 4)], c)
On Fri, Sep 5, 2008 at 10:13 AM, Hebbertt de Farias Soares
<hebbertt.soares at rosasoffice.com> wrote:
Dear list,
I am a beginner with R and I have a question which may sound stupid: How can I transform my SQL query into an appropriate dataframe?
I've looking around, and haven't found any solution.
My return data is stored in a SQL database. When I query it, it gives me the following output:
Id Fund Return Period
1 Fund01 0,5 may/08
2 Fund01 0,4 june/08
3 Fund 02 -0,3 may/08
4 Fund02 -0,4 june/2008
However this data is not suitable for analysis. I would like to transform it to a format like:
Period Fund01 Fund02
May/08 0,5 0,4
June/08 -0,3 -0,4
Is it possible to do this with R? Could you please recommend me references or packages which are useful for handling this kind of data?
Thank you very much for your time.
Regards,
Hebbertt
[[alternative HTML version deleted]]
_______________________________________________ R-sig-DB mailing list -- R Special Interest Group R-sig-DB at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-db