Hi Charlie,
I am comfortable to put the data in any way that works best. Here are two
possibilities: an xts and a data frame.
library(quantmod)
quantmod::getSymbols("SPY") # creates xts variable SPY
SPYxts <- SPY[,c("SPY.Close","SPY.Volume")]
SPYdf <- data.frame(Date=index(SPYxts),close=as.numeric(SPYxts$SPY.Close),
volume=as.numeric(SPYxts$SPY.Volume))
rownames(SPYdf) <- NULL
head(SPYxts)
head(SPYdf)
# SPY.Close SPY.Volume
#2007-01-03 141.37 94807600
#2007-01-04 141.67 69620600
#2007-01-05 140.54 76645300
#2007-01-08 141.19 71655000
#2007-01-09 141.07 75680100
#2007-01-10 141.54 72428000
# Date close volume
#1 2007-01-03 141.37 94807600
#2 2007-01-04 141.67 69620600
#3 2007-01-05 140.54 76645300
#4 2007-01-08 141.19 71655000
#5 2007-01-09 141.07 75680100
#6 2007-01-10 141.54 72428000
Thanks,
Eric
On Thu, Jan 18, 2018 at 8:00 PM, Charlie Redmon <redm...@gmail.com> wrote:
> Could you provide some information on your data structure (e.g., are the
> two time series in separate columns in the data)? The solution is fairly
> straightforward once you have the data in the right structure. And I do not
> think tidyquant is necessary for what you want.
>
> Best,
> Charlie
>
> --
> Charles Redmon
> GRA, Center for Research Methods and Data Analysis
> PhD Student, Department of Linguistics
> University of Kansas
> Lawrence, KS, USA
>
>
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