Hi,
It may help that:
aggregate(DF$total, list(DF$note, DF$id, DF$month), mean)
should give you means broken down by time slice (note), id and month.
You could then subset means for GA or GB from the aggregated dataframe.
Philip
On 27/11/2016 3:11 AM, lily li wrote:
Hi R users,
I'm trying to manipulate a dataframe and have some difficulties.
The original dataset is like this:
DF
year month total id note
2000 1 98 GA 1
2001 1 100 GA 1
2002 2 99 GA 1
2002 2 80 GB 1
...
2012 1 78 GA 2
...
The structure is like this: when year is between 2000-2005, note is 1; when
year is between 2006-2010, note is 2; GA, GB, etc represent different
groups, but they all have years 2000-2005, 2006-2010, 2011-2015.
I want to calculate one average value for each month in each time slice.
For example, between 2000-2005, when note is 1, for GA, there is one value
in month 1, one value in month 2, etc; for GB, there is one value in month
1, one value in month 2, between this time period. So later, there is no
'year' column, but other columns.
I tried the script: DF_GA = aggregate(total~year+month,data=subset(DF,
id==GA¬e==1)), but it did not give me the ideal dataframe. How to do
then?
Thanks for your help.
[[alternative HTML version deleted]]
______________________________________________
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.
______________________________________________
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.