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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