Honestly, given what a pain dates are in Excel, I might simply import
them as strings and do the conversion on the R side of things. Also,
I'd recommend you use Date objects rather than POSIXct to cut out the
unnecessary complexity of timezones, DST, etc. [See Gabor's article in
RNews 4/1 for a fuller treatment]
Best,
Michael
On Fri, Jun 15, 2012 at 9:08 AM, Keith Weintraub <kw1...@gmail.com> wrote:
> Jeff,
> Thanks. I was able to easily get rid of the do.call code and use the t(
> t(...)) construct.
>
> In terms of the dates I have tried your suggestion and I am having an odd
> problem.
>
> The dates I included in my previous message were only a subset of the actual
> dates I am using.
>
> My dates were imported from Excel via RExcel. Here are 3 of them in various
> formats:
>
> Displayed in Excel via one type of formatting: 12/1/2023, 1/1/2024, 2/1/2024
>
> As integers from the "epoch" (which is only day based): 45261, 45292, 45323
>
> In R imported from Excel via RExcel (a little more context here):
> "2023-11-30 23:00:00 EST"
> "2023-12-31 23:00:00 EST"
> "2024-01-31 23:00:00 EST"
> "2024-02-29 23:00:00 EST"
> "2024-04-01 00:00:00 EDT"
> "2024-05-01 00:00:00 EDT"
> "2024-06-01 00:00:00 EDT"
> "2024-07-01 00:00:00 EDT"
> "2024-08-01 00:00:00 EDT"
> "2024-09-01 00:00:00 EDT"
>
> Notice how March 2024 is skipped. Also notice how the conversion process
> gives some dates an EDT and some an EST tag. I assume that is what you were
> warning me about timezones.
>
> In addition when I convert using just the function year (lubridate) the
> result is:
> 2023 2023 2024 2024 2024 2024 2024 2024 2024 2024
>
> Where I was expecting (based on the Excel dates):
> 2023 2024 2024 2024 2024 2024 2024 2024 2024 2024
>
> Any help on how to do this the "right" way would be greatly appreciated.
>
> I know that Excel has "issues" with regards to dates and there may even be
> issues using RExcel for this type of conversion.
>
> Any help would is appreciated.
>
> Thanks again,
> KW
>
> PS Here is a dput of the last 10 dates:
>
> someDates<-structure(c(1701403200, 1704081600, 1706760000, 1709265600,
> 1711944000,
> 1714536000, 1717214400, 1719806400, 1722484800, 1725163200), class =
> c("POSIXct",
> "POSIXt"))
>
>
> On Jun 15, 2012, at 1:48 AM, Jeff Newmiller wrote:
>
>> a) Avoid mixing Date objects and POSIXt objects. The timezones will mess you
>> up in the conversions. Just eliminate the as.Date conversion entirely.
>>
>> b) By the time you reach the do.call function call, amortsByYears is a
>> matrix. While a data.frame is a special kind of list, a matrix is not.
>> Hence, the error message.
>>
>> You can replace the do.call with
>>
>> t( t( amortsByYears )/amortsByYears[1,] )
>>
>> which is rather more efficient than do.call anyway.
>> ---------------------------------------------------------------------------
>> Jeff Newmiller The ..... ..... Go Live...
>> DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go...
>> Live: OO#.. Dead: OO#.. Playing
>> Research Engineer (Solar/Batteries O.O#. #.O#. with
>> /Software/Embedded Controllers) .OO#. .OO#. rocks...1k
>> ---------------------------------------------------------------------------
>> Sent from my phone. Please excuse my brevity.
>>
>> Keith Weintraub <kw1...@gmail.com> wrote:
>>
>>> Folks,
>>>
>>> I call the function calcAmorts like so:
>>> calcAmorts(prevAm, amort, myDates)
>>>
>>> Note that I use the package lubridate.
>>>
>>> The last line where do.call is called to first divide all the rows by
>>> the first row and then rbind gives the following error:
>>> Error in do.call("rbind", apply(amortsByYears, 1, "/", amortsByYears[,
>>> :
>>> second argument must be a list
>>>
>>> By contrast if I run
>>> do.call('rbind', apply(amortsByYears, 1, "/", amortsByYears[,1]))
>>>
>>> On its own with any kind of numeric data.frame the call works fine.
>>> That is it divides every row in the data.frame by the first row.
>>>
>>> Thanks so much for your time,
>>> KW
>>>
>>> _____________
>>> My data:
>>>
>>> myDates<-structure(c(1338523200, 1341115200, 1343793600, 1346472000,
>>> 1349064000,
>>> 1351742400, 1354334400, 1357012800, 1359691200, 1362110400, 1364788800,
>>>
>>> 1367380800, 1370059200, 1372651200, 1375329600, 1378008000, 1380600000,
>>>
>>> 1383278400, 1385870400), class = c("POSIXct", "POSIXt"))
>>>
>>>
>>>
>>> amort<-structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0333,
>>> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0333,
>>> 0, 0, 0.0333, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>>> 0, 0, 0.0333, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>>> 0, 0, 0.0333, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>>> 0.0357142857142857,
>>> 0, 0, 0, 0, 0.0333, 0, 0, 0.0333, 0, 0, 0.0357142857142857, 0,
>>> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0333, 0, 0, 0, 0,
>>> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0333, 0, 0, 0, 0,
>>> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0357142857142857, 0, 0, 0, 0, 0.0333,
>>> 0, 0, 0.0333, 0, 0, 0.0357142857142857, 0, 0, 0, 0, 0, 0, 0,
>>> 0, 0, 0, 0, 0, 0, 0, 0, 0.0333, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>>> 0, 0, 0, 0), .Dim = c(10L, 19L))
>>>
>>> prevAm<-c(0, 0, 0, 0.0666, 0, 0.0666, 0.0666, 0, 0, 0)
>>>
>>> calcAmorts<-function(prevAmort, currAmorts, dates) {
>>> yrs<-year(as.Date(dates))
>>> currAmorts<-data.frame(yrs,t(currAmorts))
>>> amortsByYears<-aggregate(x = currAmorts, by = list(yrs), FUN =
>>> "sum")[,-c(1,2)]
>>> amortsByYears<-rbind(prevAmort, amortsByYears)
>>> amortsByYears<-(1-apply(amortsByYears, 2, cumsum))[-1,]
>>>
>>> do.call('rbind', apply(amortsByYears, 1, "/", amortsByYears[,1]))
>>>
>>> }
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list
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>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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