On 12/02/17 18:36, Bert Gunter wrote:
Basic stuff!
Either subscripting or ?subset.
There are many good R tutorials on the web. You should spend some
(more?) time with some.
Uh, Bert, perhaps I'm being obtuse (a common occurrence) but it doesn't
seem basic to me. The only way that I can see how to go at it is via
a for loop:
rdln <- function(X) {
# Remove discordant last names.
ok <- logical(nrow(X))
for(nm in unique(X$first)) {
xxx <- unique(X$last[X$first==nm])
if(length(xxx)==1) ok[X$first==nm] <- TRUE
}
Y <- X[ok,]
Y <- Y[order(Y$first),]
rownames(Y) <- 1:nrow(Y)
Y
}
Calling the toy data frame "melvin" rather than "df" (since "df" is the
name of the built in F density function, it is bad form to use it as the
name of another object) I get:
> rdln(melvin)
first week last
1 Bob 1 John
2 Bob 2 John
3 Bob 3 John
4 Cory 1 Jack
5 Cory 2 Jack
which is the desired output. If there is a "basic stuff" way to do this
I'd like to see it. Perhaps I will then be toadally embarrassed, but
they say that this is good for one.
cheers,
Rolf
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
On Sat, Feb 11, 2017 at 9:02 PM, Val <valkr...@gmail.com> wrote:
Hi all,
I have a big data set and want to remove rows conditionally.
In my data file each person were recorded for several weeks. Somehow
during the recording periods, their last name was misreported. For
each person, the last name should be the same. Otherwise remove from
the data. Example, in the following data set, Alex was found to have
two last names .
Alex West
Alex Joseph
Alex should be removed from the data. if this happens then I want
remove all rows with Alex. Here is my data set
df <- read.table(header=TRUE, text='first week last
Alex 1 West
Bob 1 John
Cory 1 Jack
Cory 2 Jack
Bob 2 John
Bob 3 John
Alex 2 Joseph
Alex 3 West
Alex 4 West ')
Desired output
first week last
1 Bob 1 John
2 Bob 2 John
3 Bob 3 John
4 Cory 1 Jack
5 Cory 2 Jack
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