That is great! Thank you very much.
Ben
On Thu, Mar 1, 2012 at 2:57 PM, Petr Savicky <savi...@cs.cas.cz> wrote:
> On Thu, Mar 01, 2012 at 02:31:01PM -0700, Ben quant wrote:
> > Hello,
> >
> > My direct desire is a good (fast) way to fill values forward until there
> is
> > another value then fill that value foward in the data xx (at the bottom
> of
> > this email). For example, from row 1 to row 45 should be NA (no change),
> > but from row 46 row 136 the value should be 12649, and from row 137 to
> the
> > next value should be 13039.00. The last line of code is all you need for
> > this part.
> >
> > If you are so inclined, my goal is this: I want to create a weekly time
> > series out of some data based on the report date. The report date is 'rd'
> > below, and is the correct date for the time series. My idea (in part seen
> > below) is to align rd and ua via the incorrect date (the time series
> date),
> > then merge that using the report date (rd) and a daily series (so I
> capture
> > all of the dates) of dates (dt). That gets the data in the right start
> > period. I've done all of this so far below and it looks fine. Then I plan
> > to roll all of those values forward to the next value (see question
> above),
> > then I'll do something like this:
> >
> > xx[weekdays(xx[,1]) == "Friday",]
> >
> > ...to get a weekly series of Friday values. I'm thinking someone probably
> > has a faster way of doing this. I have to do this many times, so speed is
> > important. Thanks!
> >
> > Here is what I have done so far:
> >
> > dt <- seq(from =as.Date("2009-06-01"), to = Sys.Date(), by = "day")
> >
> > > nms
> > [1] "2009-06-30" "2009-09-30" "2009-12-31" "2010-03-31" "2010-06-30"
> > "2010-09-30" "2010-12-31" "2011-03-31" "2011-06-30" "2011-09-30"
> > [11] "2011-12-31"
> >
> > > rd
> > 2009-06-30 2009-09-30 2009-12-31 2010-03-31 2010-06-30
> > 2010-09-30 2010-12-31 2011-03-31 2011-06-30 2011-09-30
> > "2009-07-16" "2009-10-15" "2010-01-19" "2010-04-19" "2010-07-19"
> > "2010-10-18" "2011-01-18" "2011-04-19" "2011-07-18" "2011-10-17"
> > 2011-12-31
> > "2012-01-19"
> >
> > > ua
> > 2009-06-30 2009-09-30 2009-12-31 2010-03-31 2010-06-30 2010-09-30
> > 2010-12-31 2011-03-31 2011-06-30 2011-09-30 2011-12-31
> > 12649.00 13039.00 13425.00 13731.00 14014.00 14389.00
> > 14833.00 15095.00 15481.43 15846.43 16186.43
> >
> > > x = merge(ua,rd,by='row.names')
> > > names(x) = c('z.date','val','rt_date')
> > > xx = merge(dt,x,by.y= 'rt_date',by.x=1,all.x=T)
> > > xx
> > x z.date val
> > 1 2009-06-01 <NA> NA
> > 2 2009-06-02 <NA> NA
> > 3 2009-06-03 <NA> NA
> > 4 2009-06-04 <NA> NA
> > 5 2009-06-05 <NA> NA
> >
> > ...ect....
> >
> > 36 2009-07-06 <NA> NA
> > 37 2009-07-07 <NA> NA
> > 38 2009-07-08 <NA> NA
> > 39 2009-07-09 <NA> NA
> > 40 2009-07-10 <NA> NA
> > 41 2009-07-11 <NA> NA
> > 42 2009-07-12 <NA> NA
> > 43 2009-07-13 <NA> NA
> > 44 2009-07-14 <NA> NA
> > 45 2009-07-15 <NA> NA
> > 46 2009-07-16 2009-06-30 12649
> > 47 2009-07-17 <NA> NA
> > 48 2009-07-18 <NA> NA
> > 49 2009-07-19 <NA> NA
> > 50 2009-07-20 <NA> NA
> > 51 2009-07-21 <NA> NA
> > 52 2009-07-22 <NA> NA
> > 53 2009-07-23 <NA> NA
> > 54 2009-07-24 <NA> NA
> > 55 2009-07-25 <NA> NA
> > 56 2009-07-26 <NA> NA
> > 57 2009-07-27 <NA> NA
> > 58 2009-07-28 <NA> NA
> >
> > ...ect....
> >
> > 129 2009-10-07 <NA> NA
> > 130 2009-10-08 <NA> NA
> > 131 2009-10-09 <NA> NA
> > 132 2009-10-10 <NA> NA
> > 133 2009-10-11 <NA> NA
> > 134 2009-10-12 <NA> NA
> > 135 2009-10-13 <NA> NA
> > 136 2009-10-14 <NA> NA
> > 137 2009-10-15 2009-09-30 13039.00
> > 138 2009-10-16 <NA> NA
> > 139 2009-10-17 <NA> NA
> > 140 2009-10-18 <NA> NA
> > 141 2009-10-19 <NA> NA
> > 142 2009-10-20 <NA> NA
> > 143 2009-10-21 <NA> NA
>
> Hi.
>
> Try first the following simpler version.
>
> # an input vector
> x <- rep(NA, times=20)
> x[4] <- "A"
> x[9] <- "B"
> x[17] <- "C"
>
> # extending the values forward
> values <- c(NA, x[!is.na(x)])
> ind <- cumsum(!is.na(x)) + 1
> y <- values[ind]
>
> # compare with the original
> cbind(x, y)
>
> x y
> [1,] NA NA
> [2,] NA NA
> [3,] NA NA
> [4,] "A" "A"
> [5,] NA "A"
> [6,] NA "A"
> [7,] NA "A"
> [8,] NA "A"
> [9,] "B" "B"
> [10,] NA "B"
> [11,] NA "B"
> [12,] NA "B"
> [13,] NA "B"
> [14,] NA "B"
> [15,] NA "B"
> [16,] NA "B"
> [17,] "C" "C"
> [18,] NA "C"
> [19,] NA "C"
> [20,] NA "C"
>
> This could be applied directly to the last two columns of your
> data frame "xx". However, it may be more natural to obtain the
> vector "values" from the input data and not from their sparse
> form, which is the data frame. Also, the logical vector !is.na(x)
> is the same for the last two columns of your data frame, so
> it may be computed only once.
>
> Hope this helps.
>
> Petr Savicky.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
