Importing time series from SQL base into R I have a number of regular daily measurements in a MySQL database that I'd like to manipulate using R.  When it's returned from RMySQL, it looks like this:
> memdata
        date    vsize
1  2011-04-22 3535.178
2  2011-04-23 5680.516
3  2011-04-24 5468.914
4  2011-04-25 4761.044
5  2011-04-26 4403.515
6  2011-04-27 4459.155 
7  2011-04-28 4889.884
8  2011-04-29 5290.908
9  2011-04-30 5370.952
> str(memdata)
'data.frame':   9 obs. of  2 variables:
 $ date : chr  "2011-04-22" "2011-04-23" "2011-04-24" "2011-04-25" ...
 $ vsize: num  3535 5681 5469 4761 4404 ...

Since many of the time series libraries expect ts objects, I'd like to convert the data frame into one, but there doesn't seem to be a straightforward way of doing that.  This site has a lot of good examples, but none that deal with daily data.
Any help would be greatly appreciated!
 A: Here's a better reference for that kind of stuff:
http://cran.r-project.org/web/packages/zoo/index.html
Take a look at the vignettes.
Edit 1 =========================================
To answer chl's question, I would do the following:
library(zoo)
memdata.zoo <- read.zoo(memdata)

However, the reason that I pointed to the vignettes is because it is required reading.  Trust me, I've screwed up enough code that I am well aware that I don't yet fully understand everything in those articles.    There's a lot of subtle stuff in there.
Also, if you use packages likestl and decompose, be careful to notice that what they want as a frequency and what zoo wants as a frequency may not be what you expect.     You'll simply have to play around with it, and refer back to the vignettes. 
A: Unless I missed something, you want to convert your data.frame into a suitable time-indexed series of measurement. In this case, you can use the zoo package as follows:
> library(zoo)
> memdata.ts <- with(memdata, zoo(vsize, date))
> str(memdata.ts)
‘zoo’ series from 2011-04-22 to 2011-04-30
  Data: Factor w/ 9 levels "3535.178","4403.515",..: 1 9 8 4 2 3 5 6 7
  Index:  Factor w/ 9 levels "2011-04-22","2011-04-23",..: 1 2 3 4 5 6 7 8 9

