Is the question 'duplicated next to each other' or 'duplicated anywhere
later'? I read it as the latter, so would use
dup <- duplicated(x$dt)
or
dup <- duplicated(x[c("Date", "time")]
Also, be very careful as Date-time values like this can be duplicated and
refer to different times on days
Here are three possibilities:
# 1
DF[!duplicated(DF$Datetime), ]
# 2
aggregate(DF[-1], DF[1], head, 1)
These give the first one but if you want the
last one use the fromLast= arg of duplicated
or tail instead of head with aggregate.
# 3
# The zoo package can read in data, convert the
# first co
Oliver Bandel wrote:
Antje Nöthlich web.de> writes:
[...]
Now for the whole dataframe i would like to delete rows that have the same
"Datetime" value as the prior row.
Well, if you do this, then you loose data.
is this really, what you want?
Throwing away data?
I would think it make sense,
Antje -
I may be missing something, but I usually do this with the negation of
duplicated instead of unique.
So, as an example:
test <- data.frame(a = rep(1:5, each = 2),
b = rep(1:5, each = 2), c = rnorm(10))
test[!duplicated(test[c("a", "b")]), ]
Hope that helps!
Erik
Antje Nöthlich
This should do it for you:
> x <- read.table(textConnection( "Date time
> Temperature
+ 12008-6-1 00:00:00 5
+ 22008-6-1 02:00:00 5
+ 32008-6-1 03:00:00 6
+ 42008-6-1 03:00:00 0
+ 52008-6-1 04:00:00 6
+
Antje Nöthlich web.de> writes:
[...]
> Now for the whole dataframe i would like to delete rows that have the same
> "Datetime" value as the prior row.
Well, if you do this, then you loose data.
is this really, what you want?
Throwing away data?
I would think it make sense, if all columns are eq
Hei R Users,
i have the following dataframe:
Datetime Temperature and many more
collumns
12008-6-1 00:00:00 5
22008-6-1 02:00:00 5
32008-6-1 03:00:00 6
42008-6-1 03:00:00 0
52008-6-1 04:00:00
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