Hi Val,
The by() function could be used here. With the dataframe dfr:
# split the data by first name and check for more than one last name for
each first name
res <- by(dfr, dfr['first'], function(x) length(unique(x$last)) > 1)
# make the result more easily manipulated
res <- as.table(res)
res
# first
# Alex Bob Cory
# TRUE FALSE FALSE
# then use this result to subset the data
nw.dfr <- dfr[!dfr$first %in% names(res[res]) , ]
# sort if needed
nw.dfr[order(nw.dfr$first) , ]
first week last
2 Bob 1 John
5 Bob 2 John
6 Bob 3 John
3 Cory 1 Jack
4 Cory 2 Jack
Philip
On 12/02/2017 4:02 PM, Val 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
Thank you in advance
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______________________________________________
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.
