I would probably try a different approach than the other suggestions.
Paste all the columns other than pond_id together. You now have a
character vector. Then keep the rows in which an element of the
vector contains "dnv" but does not contain "0 dnv" [use grep()]. This
assumes there are no extraneous space characters in any of the
values. You'd also for this approach want to watch for columns that
have no "dnv" in them, as they might be stored as numeric instead of
character. And make sure all your zeros are formatted exactly as "0".
The caveat is that I haven't tested this.
-Don
At 12:26 PM -0600 6/16/09, Mark Na wrote:
Hi R-helpers,
I would like to subset my dataframe, keeping only those rows which
satisfy the following conditions:
1) the string "dnv" is found in at least one column;
2) the value in the column previous to the one "dnv" is found in is not "0"
Here's what my data look like:
POND_ID 2009-05-07 2009-05-15 2009-05-21 2009-05-28 2009-06-04
4 101 0.15 0 dnv dnv dnv
7 102 0 dnv dnv dnv dnv
87 103 0.15 dnv 1 1 1
99 104 dnv 0.25 1 1 0.75
So, for above example, the new dataframe would not contain POND_ID 101
or 102 (because there is a 0 before the dnv) but it WOULD contain
POND_ID 103 (because there is a 0.15 before the dnv) and 104 (because
dnv occurs in the first column, so cannot be preceded by a 0).
One extra twist: I would like to retain rows in the new dataframe
which satisfy the above conditions even if they also have a "0" then
"dnv" sequence preceding or following the "problem" , e.g., the
following rows would be retained in the new dataframe
POND_ID 2009-05-07 2009-05-15 2009-05-21 2009-05-28 2009-06-04
100 105 0.15 dnv 1 0 dnv
101 106 0 dnv 1 0.15 dnv
Thanks in advance for any help you might provide.
(I hope I've provided enough of an example; I could also provide a
.csv file if that would help.)
Mark Na
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--
---------------------------------
Don MacQueen
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
m...@llnl.gov
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