[R] Adding Records to a Table in R

[PIKAL Petr]

Sorry, I was too quick

Should be
dput(TransitDateFrame[1:20,])
dput(dataset1[1:20, ])

Cheers
Petr

> Hi
>
> Instead of attachments copy directly result of dput(TransitDateFrame) and
> dput(dataset1) to your email. Or, if your data have more than about 20 rows
> you could copy only part of it.
>
> dput(TransitDateFrame[,1:20])
> dput(dataset1[,1:20])


>
> Only with this approach we can evaluate your data in all aspects and provide
> correct answer.
>
> Cheers
> Petr
>
> > -----Original Message-----
> > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Paul
> > Bernal
> > Sent: Wednesday, November 8, 2017 2:46 PM
> > To: Eric Berger <ericjberger at gmail.com>
> > Cc: r-help at r-project.org
> > Subject: Re: [R] Adding Records to a Table in R
> >
> > Dear Eric,
> >
> > Hope you are doing great. I also tried the following:
> >
> > #First I created the complete date sequence
> >
> > TransitDateFrame <- data.frame(TransitDate=seq(as.Date(dataset1[1,1]),
> > as.Date(dataset1[nrow(dataset1),1]), by = "month"))
> >
> > #Then I did the merging
> >
> >  dataset1NEW <- merge(TransitDateFrame, dataset1, by="TransitDate",
> > all.x=TRUE)
> >
> > Now it has, as expected the total number of rows. The problem is, it
> > filled absolutely everything with NAs, and this shouldn´t be the case
> > since there are dates that actually have data.
> >
> > why is this happening?
> >
> > I am attaching the dataset1 table as a .csv document for your reference.
> > Basically what I want is to bring all the values in dataset1 and only
> > add the dates missing with value 0.
> >
> > Best regards,
> >
> > Paul
> >
> > 2017-11-01 15:21 GMT-05:00 Eric Berger <ericjberger at gmail.com>:
> >
> > > Hi Paul,
> > >
> > > #First I set up some sample data since I don't have a copy of your
> > > data dtOrig <- as.Date(
> > > c("1985-04-01","1985-07-01","1985-12-01","1986-04-01"))
> > > dfOrig <- data.frame( TransitDate=dtOrig,
> > > Transits=c(100,100,500,325),
> > > CargoTons=c(1000,1080,3785,4200) )
> > >
> > > #Generate the complete set of dates as a data frame
> > > dfDates<- data.frame(
> > > TransitDate=seq(from=as.Date("1985-04-01"),by="1
> > > month",length=13) )
> > >
> > > # do the merge adding the "missing" rows (where NA will appear)
> > > dfNew
> > > <- merge(dfDates, dfOrig, by="TransitDate", all.x=TRUE )
> > >
> > > # replace the NA's by zero
> > > dfNew[is.na(dfNew)] <- 0
> > >
> > > HTH,
> > > Eric
> > >
> > >
> > > On Wed, Nov 1, 2017 at 9:45 PM, Paul Bernal <paulbernal07 at gmail.com>
> > > wrote:
> > >
> > >> Dear R friends,
> > >>
> > >> I am currently working with time series data, and I have a table(as
> > >> data
> > >> frame) that has looks like this (TransitDate are in format = "%e-%B-%Y") :
> > >>
> > >> TransitDate       Transits      CargoTons
> > >> 1985-04-01        100            2500
> > >> 1985-05-01        135            4500
> > >> 1985-06-01        120            1750
> > >> 1985-07-01        100            3750
> > >> 1985-08-01        200            1250
> > >>
> > >> The problem is, that there are several periods that don´t exist in
> > >> the table, so it has the following behavior:
> > >>
> > >> TransitDate        Transits      CargoTons
> > >> 1985-04-01        100             1000
> > >> 1985-07-01        100             1080
> > >> 1985-12-01        500             3785
> > >> 1986-04-01        325             4200
> > >> .
> > >> .
> > >> 2017-09-01        400             2350 (*this is the last observation)
> > >>
> > >> You can see in the last table fragment that the series jumps from
> > >> 1985-04-01 to 1985-07-01, then it jumps from there to 1985-12-01
> > >> making the time series quite irregular (non-constant
> > >> chronologically speaking).
> > >>
> > >> What I want to do is create a dummy table that has the sequence
> > >> from the first observation (1985-04-01) up to the last one
> > >> (2017-09-01) and then develop a code that checks if the dates
> > >> contained in the dummy table exist in the original table, if they
> > >> don´t exist then add those dates and put zeroes on the fields.
> > >>
> > >> How can I achieve this?
> > >>
> > >> Any help will be greatly appreciated,
> > >>
> > >> Best regards,
> > >>
> > >> Paul
> > >>

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