20 Nov
2004
20 Nov
'04
11:09 a.m.
I discovered an unpleasant R feature and wondered if anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
20 Nov
20 Nov
11:26 a.m.
New subject: [gov2001-l] help! marginal effects?
Hey
help!!
does anyone know how to use R to calculate marginal effects for bivariate
probit coefficients??
thanks!!!
yang
11:33 a.m.
That is strange. Thanks for pointing that out--that's something that
would be hard to debug.
The simplest hack around that is just to use is.na() or is.integer.
nrow(X[X[,1]==TRUE & !is.na(X),])
Also strange to notice that it looks like R is very eager to force
Booleans into integers
c(TRUE, 7)
[1] 1 7
I have no idea what this would do.
/\llan
On Sat, 20 Nov 2004 16:09:50 -0500, Andrew Eggers <aeggers(a)gmail.com> wrote:
I discovered an unpleasant R feature and wondered if
anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
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11:50 a.m.
I think you want sum(which()), not nrow(). And no variable should have
NA, 1, and TRUE/FALSE in it. That's whack. You need to clean your data.
On Sat, 20 Nov 2004, Andrew Eggers wrote:
I discovered an unpleasant R feature and wondered if
anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
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12:09 p.m.
Wouldn't sum(which(CONDITION)) add up the index numbers for all the
rows where the CONDITION was true? Please elaborate what I should do.
For the record, none of my data has NA, 1, and T/F in it. I was trying
to say that the same thing happens whether you look at vars with
T/F/NA using ==TRUE and vars with integers/NA using ==integer. Don't
call my variables wack.
Andy
On Sat, 20 Nov 2004 16:50:28 -0500 (EST), Olivia Lau
<olau(a)fas.harvard.edu> wrote:
I think you want sum(which()), not nrow(). And no
variable should have
NA, 1, and TRUE/FALSE in it. That's whack. You need to clean your data.
On Sat, 20 Nov 2004, Andrew Eggers wrote:
I discovered an unpleasant R feature and wondered
if anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
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http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l
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21 Nov
21 Nov
11:46 a.m.
The key thing to understand here is that R treats an NA as a missing value
-- literally. Which means that if you want to do a logical operation on a
NA value, you get "missing value where TRUE/FALSE needed". Since R
doesn't know what to do if the logical value is missing, and so keeps the
row by default. You need to omit the NA values using:
nrow(na.omit(data[data$var,]))
This has the effect of omitting observations 3-5 below:
x y
1 TRUE 1
2 TRUE 2
3 TRUE NA
4 FALSE 3
5 NA 4
That is, if any of the variables for which x is TRUE has an NA in any of
of the *other* variables, that row will be omitted from the count.
Also, note that data$var == TRUE is redundant in this case, and also note
that you should use the name of the variable, not a column indicator.
(You want to preserve the indexing of observations against each other.)
Also, Allan's hack from yesterday works too...
Olivia.
On Sat, 20 Nov 2004, Andrew Eggers wrote:
I discovered an unpleasant R feature and wondered if
anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
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gov2001-l mailing list
gov2001-l(a)lists.fas.harvard.edu
http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l
29 Nov
29 Nov
2:15 p.m.
Hi Olivia,
I need to send you an email copy of the memo (the homework), could you
please let me know your email address? I am not sure whether I could send it
to you by this email account.
Thanks.
Chunling
-----Original Message-----
From: gov2001-l-bounces(a)lists.fas.harvard.edu
[mailto:gov2001-l-bounces@lists.fas.harvard.edu]On Behalf Of Olivia Lau
Sent: Sunday, November 21, 2004 4:46 PM
To: gov2001-l(a)lists.fas.harvard.edu
Subject: Re: [gov2001-l] NA and TRUE
The key thing to understand here is that R treats an NA as a missing value
-- literally. Which means that if you want to do a logical operation on a
NA value, you get "missing value where TRUE/FALSE needed". Since R
doesn't know what to do if the logical value is missing, and so keeps the
row by default. You need to omit the NA values using:
nrow(na.omit(data[data$var,]))
This has the effect of omitting observations 3-5 below:
x y
1 TRUE 1
2 TRUE 2
3 TRUE NA
4 FALSE 3
5 NA 4
That is, if any of the variables for which x is TRUE has an NA in any of
of the *other* variables, that row will be omitted from the count.
Also, note that data$var == TRUE is redundant in this case, and also note
that you should use the name of the variable, not a column indicator.
(You want to preserve the indexing of observations against each other.)
Also, Allan's hack from yesterday works too...
Olivia.
On Sat, 20 Nov 2004, Andrew Eggers wrote:
I discovered an unpleasant R feature and wondered if
anyone could
suggest a workaround or show me where I am going wrong.
I have been using logical statements and nrow() to extract the number
of observations that have certain characteristics.
for example, I thought the following statement
nrow(X[X[,1]==TRUE,])
would tell me how many rows of X had TRUE in the first column.
But it turns out that R considers anything that is TRUE or 1 _or_ NA
as TRUE. (The same is true when you say nrow(X[X[,1]==1,]).)
Can anyone tell me how to deal with this? Can anyone explain why R
would count NA as TRUE?
Andy
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http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l
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6 comments
5 participants
participants (5)
-
aeggers＠gmail.com -
allan.friedman＠gmail.com -
chunling_lu＠harvard.edu -
olau＠fas.harvard.edu -
yanglin＠fas.harvard.edu