Thanks, Andrew. I didn't realise as.Date *only* read two formats, I
think I was tripped up by using %y instead of %Y, though I also know
that '/' is a special character in R (if that's the right term) and as
such know there is special syntax to use (which I don't know).
On Sat, 20 Nov 2021 at 18:02, Andrew Simmons <akwsi...@gmail.com> wrote:
>
> The as.Date function for a character class argument will try reading in two
> formats (%Y-%m-%d and %Y/%m/%d).
>
>
> This does not look like the format you have provided, which is why it doesn't
> work. Try something like:
>
>
> x <- c("28/10/2016", "19/11/2016", "31/12/2016", "16/01/2016", "05/03/2017")
> as.Date(x, format = "%d/%m/%Y")
>
>
> which produces this output:
>
>
> > x <- c("28/10/2016", "19/11/2016", "31/12/2016", "16/01/2016", "05/03/2017")
> > as.Date(x, format = "%d/%m/%Y")
> [1] "2016-10-28" "2016-11-19" "2016-12-31" "2016-01-16" "2017-03-05"
> >
>
>
> much better than before! I hope this helps
>
> On Sat, Nov 20, 2021 at 12:49 PM Philip Monk <prm...@gmail.com> wrote:
>>
>> Thanks Eric & Jeff.
>>
>> I'll certainly read up on lubridate, and the posting guide (again)
>> (this should be in plain text).
>>
>> CSV extract below...
>>
>> Philip
>>
>> Buffer 28/10/2016 19/11/2016 31/12/2016 16/01/2017 05/03/2017
>> 100 2.437110889 -8.69674895 3.239299816 2.443183304
>> 2.346743827
>> 200 2.524329899 -7.688862068 3.386811734 2.680347706
>> 2.253885237
>> 300 2.100784256 -8.059855835 3.143786507 2.615152896
>> 2.015645973
>> 400 1.985608385 -10.6707206 2.894572791 2.591925038
>> 2.057913137
>> 500 1.824982163 -9.122519736 2.560350727 2.372226799
>> 1.995863839
>>
>>
>> On Sat, 20 Nov 2021 at 17:08, Philip Monk <prm...@gmail.com> wrote:
>> >
>> > Hello,
>> >
>> > Simple but infuriating problem.
>> >
>> > Reading in CSV of data using :
>> >
>> > ```
>> > # CSV file has column headers with date of scene capture in format
>> > dd/mm/yyyy
>> > # check.names = FALSE averts R incorrectly processing dates due to '/'
>> > data <- read.csv("C:/R_data/Bungala (b2000) julian.csv", check.names =
>> > FALSE)
>> >
>> > # Converts data table from wide (many columns) to long (many rows) and
>> > creates the new object 'data_long'
>> > # Column 1 is the 'Buffer' number (100-2000), Columns 2-25 contain monthly
>> > data covering 2 years (the header row being the date, and rows 2-21 being
>> > a value for each buffer).
>> > # Column headers for columns 2:25 are mutated into a column called 'Date',
>> > values for each buffer and each date into the column 'LST'
>> > data_long <- data %>% pivot_longer(cols = 2:25, names_to = "Date",
>> > values_to = "LST")
>> >
>> > # Instructs R to treat the 'Date' column data as a date
>> > data_long$Date <- as.Date(data_long$Date)
>> > ```
>> >
>> > Using str(data), I can see that R has correctly read the dates in the
>> > format %d/%m/%y (e.g. 15/12/2015) though has the data type as chr.
>> >
>> > Once changing the type to 'Date', however, the date is reconfigured. For
>> > instance, 15/01/2010 (15 January 2010), becomes 0015-01-20.
>> >
>> > I've tried ```data_long$Date <- as.Date(data_long$Date, format =
>> > "%d/%m.%y")```, and also ```tryformat c("%d/%m%y")```, but either the
>> > error persists or I get ```NA```.
>> >
>> > How do I make R change Date from 'chr' to 'date' without it going wrong?
>> >
>> > Suggestions/hints/solutions would be most welcome. :)
>> >
>> > Thanks for your time,
>> >
>> > Philip
>> >
>> > Part-time PhD Student (Environmental Science)
>> > Lancaster University, UK.
>> >
>> > ~~~~~
>> >
>> > I asked a question a few weeks ago and put together the answer I needed
>> > from the responses but didn't know how to say thanks on this list. So,
>> > thanks Andrew Simmons, Bert Gunter, Jeff Newmiller and Daniel Nordlund!
>>
>> ______________________________________________
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> 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.
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