Hi Paul,
The date format that you have supplied to R isn’t exactly right.
Instead of supplying the format “%Y-%m-%d”, it appears that the format of your
data adheres to the “%e-%B-%y” format. In this case, %e refers to Day, and
takes an integer between (0 - 31), %B refers to the 3 letter abbreviated
version of the Month, and %y refers to the Year provided in a “2-integer”
format.
Hope this helps!
Thank you.
Regards,
Bo Lin
> On 28 Mar 2017, at 10:12 PM, Paul Bernal <paulberna...@gmail.com> wrote:
>
> Dear friends Ng Bo Lin, Mark and Ulrik, thank you all for your kind and
> valuable replies,
>
> I am trying to reformat a date as follows:
>
> Data<-read.csv("Container.csv")
>
> DataFrame<-data.frame(Data)
>
> DataFrame$TransitDate<-as.Date(DataFrame$TransitDate, "%Y-%m-%d")
>
> #trying to put it in YYYY-MM-DD format
>
> However, when I do this, I get a bunch of NAs for the dates.
>
> I am providing a sample dataset as a reference.
>
> Any help will be greatly appreciated,
>
> Best regards,
>
> Paul
>
> 2017-03-28 8:15 GMT-05:00 Ng Bo Lin <ngboli...@gmail.com
> <mailto:ngboli...@gmail.com>>:
> Hi Paul,
>
> Using the example provided by Ulrik, where
>
> > exdf1 <- data.frame(Date = c("1985-10-01", "1985-11-01", "1985-12-01”,
> > "1986-01-01"), Transits = c(NA, NA, NA, NA))
> > exdf2 <- data.frame(Date = c("1985-10-01", "1986-01-01"), Transits =
> > c(15,20)),
>
> You could also try the following function:
>
> for (i in 1:dim(exdf1)[1]){
> if (!exdf1[i, 1] %in% exdf2[, 1]){
> exdf2 <- rbind(exdf2, exdf1[i,])
> }
> }
>
> Basically, what the function does is that it runs through the number of rows
> in exdf1, and checks if the Date of the exdf1 row already exists in Date
> column of exdf2. If so, it skips it. Otherwise, it binds the row to df2.
>
> Hope this helps!
>
>
> Side note.: Computational efficiency wise, think Ulrik’s answer is probably
> better. Presentation wise, his is also much better.
>
> Regards,
> Bo Lin
>
> > On 28 Mar 2017, at 5:22 PM, Ulrik Stervbo <ulrik.ster...@gmail.com
> > <mailto:ulrik.ster...@gmail.com>> wrote:
> >
> > Hi Paul,
> >
> > does this do what you want?
> >
> > exdf1 <- data.frame(Date = c("1985-10-01", "1985-11-01", "1985-12-01",
> > "1986-01-01"), Transits = c(NA, NA, NA, NA))
> > exdf2 <- data.frame(Date = c("1985-10-01", "1986-01-01"), Transits = c(15,
> > 20))
> >
> > tmpdf <- subset(exdf1, !Date %in% exdf2$Date)
> >
> > rbind(exdf2, tmpdf)
> >
> > HTH,
> > Ulrik
> >
> > On Tue, 28 Mar 2017 at 10:50 Paul Bernal <paulberna...@gmail.com
> > <mailto:paulberna...@gmail.com>> wrote:
> >
> > Dear friend Mark,
> >
> > Great suggestion! Thank you for replying.
> >
> > I have two dataframes, dataframe1 and dataframe2.
> >
> > dataframe1 has two columns, one with the dates in YYYY-MM-DD format and the
> > other colum with number of transits (all of which were set to NA values).
> > dataframe1 starts in 1985-10-01 (october 1st 1985) and ends in 2017-03-01
> > (march 1 2017).
> >
> > dataframe2 has the same two columns, one with the dates in YYYY-MM-DD
> > format, and the other column with number of transits. dataframe2 starts
> > have the same start and end dates, however, dataframe2 has missing dates
> > between the start and end dates, so it has fewer observations.
> >
> > dataframe1 has a total of 378 observations and dataframe2 has a total of
> > 362 observations.
> >
> > I would like to come up with a code that could do the following:
> >
> > Get the dates of dataframe1 that are missing in dataframe2 and add them as
> > records to dataframe 2 but with NA values.
> >
> > <dataframe1 <dataframe2
> >
> > Date Transits Date
> > Transits
> > 1985-10-01 NA 1985-10-01 15
> > 1985-11-01 NA 1986-01-01 20
> > 1985-12-01 NA 1986-02-01 5
> > 1986-01-01 NA
> > 1986-02-01 NA
> > 2017-03-01 NA
> >
> > I would like to fill in the missing dates in dataframe2, with NA as value
> > for the missing transits, so that I could end up with a dataframe3 looking
> > as follows:
> >
> > <dataframe3
> > Date Transits
> > 1985-10-01 15
> > 1985-11-01 NA
> > 1985-12-01 NA
> > 1986-01-01 20
> > 1986-02-01 5
> > 2017-03-01 NA
> >
> > This is what I want to accomplish.
> >
> > Thanks, beforehand for your help,
> >
> > Best regards,
> >
> > Paul
> >
> >
> > 2017-03-27 15:15 GMT-05:00 Mark Sharp <msh...@txbiomed.org
> > <mailto:msh...@txbiomed.org>>:
> >
> >> Make some small dataframes of just a few rows that illustrate the problem
> >> structure. Make a third that has the result you want. You will get an
> >> answer very quickly. Without a self-contained reproducible problem,
> > results
> >> vary.
> >>
> >> Mark
> >> R. Mark Sharp, Ph.D.
> >> msh...@txbiomed.org
> >>
> >>
> >>
> >>
> >>
> >>> On Mar 27, 2017, at 3:09 PM, Paul Bernal <paulberna...@gmail.com
> >>> <mailto:paulberna...@gmail.com>> wrote:
> >>>
> >>> Dear friends,
> >>>
> >>> I have one dataframe which contains 378 observations, and another one,
> >>> containing 362 observations.
> >>>
> >>> Both dataframes have two columns, one date column and another one with
> >> the
> >>> number of transits.
> >>>
> >>> I wanted to come up with a code so that I could fill in the dates that
> >> are
> >>> missing in one of the dataframes and replace the column of transits with
> >>> the value NA.
> >>>
> >>> I have tried several things but R obviously complains that the length of
> >>> the dataframes are different.
> >>>
> >>> How can I solve this?
> >>>
> >>> Any guidance will be greatly appreciated,
> >>>
> >>> Best regards,
> >>>
> >>> Paul
> >>>
> >>> [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
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> >>> <http://www.r-project.org/>
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> >>
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>
> <Container.csv>
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