[R-SIG-Finance] Database for Historical Security Prices

[Johnson, Cedrick W.]

That is another way, I [automatically, perhaps incorrectly] assume that 
more than 1 person would be accessing the data. If it's just you, then 
the native/binary way is the way to go :)

-c

On 10/25/2010 7:42 AM, Mark Breman wrote:
> Why not use R's native (binary) storage, i.e. use:
>
> load("vsmirk.Rdata")
> .... update data here...
> save(smirkresult, vsmirkdata, file="vsmirk.Rdata")
>
> Regards,
>
> -Mark-
>
> 2010/10/25 Johnson, Cedrick W. <cedrick at cedrickjohnson.com 
> <mailto:cedrick at cedrickjohnson.com>>
>
>     [moderator: my earlier email was being held b/c of a mistake I
>     made on my end with my email address, sorry for the re-post]
>
>     I personally use a mysql database here with the 'quantmod'
>     package. See:
>
>     ?getSymbols.MySQL for the nitty gritty details.
>
>     You could also just open a connection to mysql either directly or
>     via ODBC and convert your time series into a data.frame and then
>     use dbWriteTable(dbcon, "SymbolName", Symbol.df). Conversely, to
>     read back into R, just use dbReadTable(dbcon, "SymbolName") and
>     convert it into a xts time series.
>
>     ?dbReadTable and ?dbWriteTable ... If your dataset only adds the
>     new row everyday, when writing the table you could specify
>     append=TRUE, overwrite=FALSE.
>
>     HTH,
>
>     C
>
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