Hello,
I'm glad it helped. See answer inline.
Em 03-07-2012 17:09, Claudia Penaloza escreveu:
Thank you Rui and Jim, both 'i1' and 'i1new' worked perfectly
because there are no instances of 'Dd' or 'dD' in the data set (that I
would/not want to include/exclude)... but I understand that 'i1new'
targets precisely what I want.
Why isn't a leader of zero's required for either 'i1' or 'i1new', as so?
i1newer <- grepl("^0{0,}[D]*$|^0{0,}[d]*$", dd$ch)
Because both 'i1' and 'i1new' test from beginning to end of string,
allowing only '0' and either 'd' or 'D', but not both (i1new).
So, there's no need to explicitly test for a string that begins with '0'.
Rui Barradas
Thank you again,
Claudia
On Tue, Jul 3, 2012 at 2:06 AM, Rui Barradas <ruipbarra...@sapo.pt
<mailto:ruipbarra...@sapo.pt>> wrote:
Hello,
Inline.
Em 03-07-2012 01:15, jim holtman escreveu:
You will have to change the 'i1' expression as follows:
i1 <- grepl("^([0D]|[0d])*$", dd$ch)
i1 # matches strings with d & D in them
[1] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# second string had 'd' & 'D' in it so it was TRUE above and
FALSE below
i1new <- grepl("^([0D]*$|[0d]*$)", dd$ch)
i1new
[1] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
Right, apparently, I forgot that grep is greedy, and the test cases
were not complete.
I put a 'd' and 'D' in the second string and the original regular
expression is equivalent to
grepl("^[0dD]*$", dd$ch)
This is only for the first request, and does not solve cases where
there are characters other than '0', 'd' or 'D', but 'd' or 'D' are
the first non-zero. This is the case of my 4th row, changed from the
OP's data example.
My regexpr for 'i2' is equivalent to this one, that I believe is
more readable:
i2b <- grepl("^0{0,}[Dd]", dd$ch)
First a zero, that might occur zero or more times, then a 'd' or
'D', then and til the end, irrelevant.
which will match strings containing d, D and 0. If you only
want 'd'
or 'D' (and not both), then you will have to use the one in 'i1new'.
To the OP: bottom line, use Jim's 'i1new' and my 'i2' or 'i2b'.
Rui Barradas
On Mon, Jul 2, 2012 at 7:24 PM, Rui Barradas
<ruipbarra...@sapo.pt <mailto:ruipbarra...@sapo.pt>> wrote:
Hello,
Try regular expressions instead.
In this data.frame, I've changed row nr.4 to have a row with
'D' as first
non-zero character.
dd <- read.table(text="
ch count
1 0000000000D0000000000000000000__000000000000000000 0.007368
2 0000000000d0000000000000000000__000000000000000000 0.002456
3 000000000T00000000000000000000__000000000000000000 0.007368
4 000000000DT0000000000000000000__000000000000000000 0.007368
5 000000000T00000000000000000000__000000000000000000 0.002456
6 000000000Td0000000000000000000__000000000000000000 0.002456
7 00000000T000000000000000000000__000000000000000000 0.007368
8 00000000T0D0000000000000000000__000000000000000000 0.007368
9 00000000T000000000000000000000__000000000000000000 0.002456
10 00000000T0d0000000000000000000__000000000000000000 0.002456
", header=TRUE)
dd
i1 <- grepl("^([0D]|[0d])*$", dd$ch)
i2 <- grepl("^0*[Dd]", dd$ch)
dd[!i1, ]
dd[!i2, ]
dd[!(i1 | i2), ]
Hope this helps,
Rui Barradas
Em 02-07-2012 23:48, Claudia Penaloza escreveu:
I would like to remove rows from the following data
frame (df) if there
are
only two specific elements found in the df$ch character
string (I want to
remove rows with only "0" & "D" or "0" & "d").
Alternatively, I would like
to remove rows if the first non-zero element is "D" or "d".
ch
count
1 0000000000D0000000000000000000__000000000000000000
0.007368;
2 0000000000d0000000000000000000__000000000000000000
0.002456;
3 000000000T00000000000000000000__000000000000000000
0.007368;
4 000000000TD0000000000000000000__000000000000000000
0.007368;
5 000000000T00000000000000000000__000000000000000000
0.002456;
6 000000000Td0000000000000000000__000000000000000000
0.002456;
7 00000000T000000000000000000000__000000000000000000
0.007368;
8 00000000T0D0000000000000000000__000000000000000000
0.007368;
9 00000000T000000000000000000000__000000000000000000
0.002456;
10 00000000T0d0000000000000000000__000000000000000000
0.002456;
I tried the following but it doesn't work if there is
more than one
character per string:
df <- df[!df$ch %in% c("0","D"),]
df <- df[!df$ch %in% c("0","d"),]
Any help greatly appreciated,
Claudia
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