Hi I am a new R user and need some help converting a data frame object to time series. 1. My input is a CSV file, contents something like these: DATE ,STOCK ,RETURN-A ,RETURN-B, etc. 2009/02/02 ,A ,0.01 ,0.011 2009/01/30 ,A ,0.01 ,0.011 2009/01/29 ,A ,0.01 ,0.011 2009/01/28 ,A ,0.01 ,0.011 2009/02/02 ,B ,0.01 ,0.011 2009/01/30 ,B ,0.01 ,0.011 2009/01/29 ,B ,0.01 ,0.011 2009/02/02 ,C ,0.01 ,0.011 2009/01/30 ,C ,0.01 ,0.011 2009/01/29 ,C ,0.01 ,0.011 and so on, going down a few years. Notice that there are gaps in observation dates (weekends), and also that some stocks do not have all the dates because there was no data that day (may be the stock is newly listed, or de-listed, or something else.) 2. I have this loaded into a data.frame object using read.table(). Factor the STOCK names. Then split the big table into N smaller data.frames one per STOCK name. The mode() for DATE and STOCK print as numeric. (That somehow did not feel right, esp. STOCK). I have converted the DATE <- as.Date(DATE,"%Y/%m/%d") 3. I am now trying to create time series objects to perform my main work which is single-stock and pairwise analysis. When I try to create from the data.frame a ts object, two strange things happen - one, the DATE shows going from 1 onwards, and STOCK is fixed to 1 (2 for Stock B, 3 for C, etc.). I will greatly appreciate your help in resolving these issues, namely - why am I losing DATE and STOCK - how can I get a proper time series out of it Thanks a lot Dinesh.
Gabor Grothendieck
2009-Feb-04 08:45 UTC
[R] need help converting data.frame to time series
Without the code we can't tell what the problem is but
try this noting that ts is not normally used for daily data.
Using zoo package L is a list of time series and z
merges them into a multivariate series. Read the 3
zoo vignettes (pdf documents) that come with zoo:
Lines <-
"DATE ,STOCK ,RETURN-a ,RETURN-b
2009/02/02 ,A ,0.01 ,0.011
2009/01/30 ,A ,0.01 ,0.011
2009/01/29 ,A ,0.01 ,0.011
2009/01/28 ,A ,0.01 ,0.011
2009/02/02 ,B ,0.01 ,0.011
2009/01/30 ,B ,0.01 ,0.011
2009/01/29 ,B ,0.01 ,0.011
2009/02/02 ,C ,0.01 ,0.011
2009/01/30 ,C ,0.01 ,0.011
2009/01/29 ,C ,0.01 ,0.011"
library(zoo)
# DF <- read.csv("myfile.csv")
DF <- read.csv(textConnection(Lines))
f <- function(x) zoo(as.matrix(x[3:4]), as.Date(x$DATE,
"%Y/%m/%d"))
L <- lapply(split(DF, DF$STOCK), f)
z <- do.call(merge, L)
On Wed, Feb 4, 2009 at 2:27 AM, Somani, Dinesh K
<dinesh.somani at gatech.edu> wrote:> Hi
>
> I am a new R user and need some help converting a data frame object to time
series.
>
> 1. My input is a CSV file, contents something like these:
> DATE ,STOCK ,RETURN-A ,RETURN-B, etc.
> 2009/02/02 ,A ,0.01 ,0.011
> 2009/01/30 ,A ,0.01 ,0.011
> 2009/01/29 ,A ,0.01 ,0.011
> 2009/01/28 ,A ,0.01 ,0.011
> 2009/02/02 ,B ,0.01 ,0.011
> 2009/01/30 ,B ,0.01 ,0.011
> 2009/01/29 ,B ,0.01 ,0.011
> 2009/02/02 ,C ,0.01 ,0.011
> 2009/01/30 ,C ,0.01 ,0.011
> 2009/01/29 ,C ,0.01 ,0.011
> and so on, going down a few years. Notice that there are gaps in
observation dates (weekends), and
> also that some stocks do not have all the dates because there was no data
that day (may be the stock
> is newly listed, or de-listed, or something else.)
>
> 2. I have this loaded into a data.frame object using read.table(). Factor
the STOCK names. Then split
> the big table into N smaller data.frames one per STOCK name. The mode() for
DATE and STOCK print
> as numeric. (That somehow did not feel right, esp. STOCK). I have converted
the DATE <- as.Date(DATE,"%Y/%m/%d")
>
> 3. I am now trying to create time series objects to perform my main work
which is single-stock and pairwise
> analysis.
>
> When I try to create from the data.frame a ts object, two strange things
happen - one, the DATE shows
> going from 1 onwards, and STOCK is fixed to 1 (2 for Stock B, 3 for C,
etc.).
>
>
> I will greatly appreciate your help in resolving these issues, namely
> - why am I losing DATE and STOCK
> - how can I get a proper time series out of it
>
> Thanks a lot
> Dinesh.
>
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