On Mon, 4 Aug 2014, Florian Denzinger wrote:
this is great, thanks!
one problem I noticed though is that it fills all NA values in every
column, is it possible to specify only one column, e.g. only ID (I have
NA values in another column I want to keep)
Yes, of course. Just access only one column, not all: Something like
yourdataframe$ID <- na.locf( yourdataframe$ID)
should replace the ID-column with the modified version you want.
Regards -- Gerrit
Kind regards,
Florian
Am 04.08.2014 um 11:31 schrieb Gerrit Eichner
<gerrit.eich...@math.uni-giessen.de>:
Hello, Florian,
function na.locf() from package zoo mightdo what you want.
Hth -- Gerrit
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On Mon, 4 Aug 2014, fd wrote:
I have the following .csv file containing about 40000 values (here only an
extract and simplified version):
NAME ; YEAR; ID; VALUE; CUMMB
Sample1; 1998; 354; 45; 45
Sample1; 1999; 354; 23; 68
Sample1; 2000; NA; 66; 134
Sample1; 2001; NA; 98; 232
Sample1; 2002; NA; 36; 268
Sample1; 2003; NA; 59; 327
Sample1; 2004; NA; 64; 391
Sample1; 2005; 354; 23; 414
Sample1; 2006; 354; 69; 483
Sample1; 2007; 354; 94; 577
Sample1; 2008; 354; 24; 601
Sample2; 1964; 1342; 7; 7
Sample2; 1965; 1342; 24; 31
Sample3; 2002; 859; 90; 90
Sample3; 2003; NA; 93; 183
Sample3; 2004; NA; 53; 236
Sample3; 2005; 859; 98; 334
What I would like to do is to replace the NA values in ID with the values
from the ID. E.g. all values in ID from Sample 1 should have the value 354;
all values in ID from Sample 3 should have the value 859 etc.
Is there a simple way to do this?
Thanks for your help.
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