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Matej Cepl

2002-Oct-23 06:48 UTC

[R] Counting NA?

Hi,

how to do quickly equivalent of the following?

	counter = 0
	for(i in 1:length(data$S2)) {
		if(!is.na(data$S2[i])) {
			counter = counter + 1
		}
	}

I have imagined something like length(x,na.rm=TRUE).

How can I get values usually taken from tables like z-score, 
values of t distribution etc.? I could not find them among 
values mentioned in info file.

Thanks,

Matej

-- 
Matej Cepl, matej at ceplovi.cz, PGP ID# D96484AC
138 Highland Ave. #10, Somerville, Ma 02143, (617) 623-1488
 
The difference between death and taxes is death doesn't get worse
every time Congress meets
    -- Will Rogers

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Laurent Gautier

2002-Oct-23 08:53 UTC

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[R] Counting NA?

On Wed, Oct 23, 2002 at 02:48:20AM -0400, Matej Cepl
wrote:> Hi,
> 
> how to do quickly equivalent of the following?
> 
> 	counter = 0
> 	for(i in 1:length(data$S2)) {
> 		if(!is.na(data$S2[i])) {
> 			counter = counter + 1
> 		}
> 	}
> 

Try:

sum(is.na(data$2))



Hopin' it helps,


L.
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ripley@stats.ox.ac.uk

2002-Oct-23 10:14 UTC

head link

[R] Counting NA?

On Wed, 23 Oct 2002, Matej Cepl wrote:
> Hi,
>
> how to do quickly equivalent of the following?
>
> 	counter = 0
> 	for(i in 1:length(data$S2)) {
> 		if(!is.na(data$S2[i])) {
> 			counter = counter + 1
> 		}
> 	}
>
> I have imagined something like length(x,na.rm=TRUE).
sum(is.na(data$s2)), using that the fact that TRUE/FALSE are coerced to
1/0.
> How can I get values usually taken from tables like z-score,
> values of t distribution etc.? I could not find them among
> values mentioned in info file.
Use qnorm/pnorm etc.  Here's the examples from chapter 1 of MASS4 (a good
reference!)

The \s. environment includes the equivalent of a comprehensive set of
statistical tables; one can work out $P$ values or critical values for
a wide range of distributions (see Table~\ref{tab:dist.1} on
page~\pageref{tab:dist.1}).
\begin{session}
1 - pf(4.3781, 4, 76)&$P$ value from the ANOVA table above.\cr
qf(0.95, 4, 76)&corresponding 5\% critical point.\cr
\end{session}

In R you could also use

pf(4.3781, 4, 76, lower.tail=FALSE)

although I tend to find that too much typing.

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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John Fox

2002-Oct-23 11:31 UTC

head link

[R] Counting NA?

Dear Matej,

At 02:48 AM 10/23/2002 -0400, Matej Cepl wrote:
>How can I get values usually taken from tables like z-score,
>values of t distribution etc.? I could not find them among
>values mentioned in info file.
R has random-number generators and cumulative-probability, density, and 
quantile functions for all of the standard statistical distributions. The 
names are very regular -- for example, rt, pt, dt, and qt for the 
t-distribution, and rnorm, pnorm, dnorm, and qnorm for the normal. Try, for 
example, help(rt) for the details. Even better, look at section 8 (on 
probability distributions) of  An Introduction to R, one of the manuals 
available on CRAN.

I hope that this helps,
  John
-----------------------------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada L8S 4M4
email: jfox at mcmaster.ca
phone: 905-525-9140x23604
web: www.socsci.mcmaster.ca/jfox
-----------------------------------------------------

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David Wartel

2002-Oct-23 11:54 UTC

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[R] Counting NA?

Surely not the best method:
length(which(is.na(data$S2)==TRUE))


On Wednesday 23 October 2002 08:48, Matej Cepl wrote:> Hi,
>
> how to do quickly equivalent of the following?
>
> 	counter = 0
> 	for(i in 1:length(data$S2)) {
> 		if(!is.na(data$S2[i])) {
> 			counter = counter + 1
> 		}
> 	}
>
> I have imagined something like length(x,na.rm=TRUE).
>
> How can I get values usually taken from tables like z-score,
> values of t distribution etc.? I could not find them among
> values mentioned in info file.
>
> Thanks,
>
> Matej
-- 
David Wartel

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r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
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Ben Bolker

2002-Oct-23 12:12 UTC

head link

[R] Counting NA?

sum(is.na(data$S2))
  [is.na returns TRUE/FALSE, which can also be added up as 0/1 values]

  For your other question: see ?pt, ?pnorm (which will also give you 
information about qt, qnorm, the quantile functions)

  Or help.search("normal"), help.search("Student")

On Wed, 23 Oct 2002, Matej Cepl wrote:
> Hi,
> 
> how to do quickly equivalent of the following?
> 
> 	counter = 0
> 	for(i in 1:length(data$S2)) {
> 		if(!is.na(data$S2[i])) {
> 			counter = counter + 1
> 		}
> 	}
> 
> I have imagined something like length(x,na.rm=TRUE).
> 
> How can I get values usually taken from tables like z-score, 
> values of t distribution etc.? I could not find them among 
> values mentioned in info file.
> 
> Thanks,
> 
> Matej
> 
> 
-- 
318 Carr Hall                                bolker at zoo.ufl.edu
Zoology Department, University of Florida    http://www.zoo.ufl.edu/bolker
Box 118525                                   (ph)  352-392-5697
Gainesville, FL 32611-8525                   (fax) 352-392-3704

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Jan_Svatos@eurotel.cz

2002-Oct-23 13:11 UTC

head link

[R] Counting NA?

Hi,

length(data$S2[is.na(data$S2)]) #counts NA
length(data$S2[!is.na(data$S2)]) #counts NOT NA

is the easiest solution I know.
JS


- - - Original message: - - -
From: owner-r-help at stat.math.ethz.ch
Send: 23.10.2002 9:50:19
To: r-help at stat.math.ethz.ch
Subject: [R] Counting NA?

Hi,

how to do quickly equivalent of the following?

 counter = 0
 for(i in 1:length(data$S2)) {
  if(!is.na(data$S2[i])) {
   counter = counter + 1
  }
 }

I have imagined something like length(x,na.rm=TRUE).

How can I get values usually taken from tables like z-score,
values of t distribution etc.? I could not find them among
values mentioned in info file.

Thanks,

Matej

--
Matej Cepl, matej at ceplovi.cz, PGP ID# D96484AC
138 Highland Ave. #10, Somerville, Ma 02143, (617) 623-1488

The difference between death and taxes is death doesn't get worse
every time Congress meets
    -- Will Rogers

-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.
-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at
stat.math.ethz.ch
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_._._

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r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
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Warnes, Gregory R

2002-Oct-23 23:56 UTC

head link

[R] Counting NA?

> -----Original Message-----
> From: Matej Cepl [mailto:matej at ceplovi.cz]
> Sent: Wednesday, October 23, 2002 10:53 AM
> To: r-help at stat.math.ethz.ch
> Subject: Re: [R] Counting NA?
> 
> 
> On Wed, Oct 23, 2002 at 01:54:50PM +0200, David Wartel wrote:
> > Surely not the best method:
> > length(which(is.na(data$S2)==TRUE))
> 
For pure convenience, the gregmisc package includes a generic function
'nobs' which (for vectors) does sum(!is.na(x)).

	> library(gregmisc)
	> nobs( c(1,2,3,4,5,NA,NA,NA ))
	[1] 5
> One this I was really surprised what that in order to get data
> from the same data I have to use following construct constantly:
> 
> 	sumyes <- length(data$S2[data$S2 == 1 & !is.na(data$S2)])
> 
> Isn't there any way how to say R, that I want eliminate NA data 
> for all my following calculations?
Well, the simplest thing would be to create a new variable with the missing
values removed, 

	y <- na.omit(data$S2)

which is pretty much equivalent to

	y <- data$S2[!is.na(data$S2)]

in this case.

For data frames it na.omit removes rows with any missing value, which is
what we often desire:
> data <- data.frame( x=rnorm(10), y=rnorm(10))
> data$y[3] <- NA
> data             x          y
1  -1.40045667  0.1370657
2   0.16997476  0.4742317
3   0.66760007         NA
4   1.55857918  0.7787977
5  -0.70213268 -0.3806202
6  -1.03643219  0.4481208
7  -0.72489209  0.5521957
8  -0.86034676  1.3522844
9   0.50605859  1.5335474
10 -0.05295296  1.4871456> na.omit(data)             x          y
1  -1.40045667  0.1370657
2   0.16997476  0.4742317
4   1.55857918  0.7787977
5  -0.70213268 -0.3806202
6  -1.03643219  0.4481208
7  -0.72489209  0.5521957
8  -0.86034676  1.3522844
9   0.50605859  1.5335474
10 -0.05295296  1.4871456> 
-Greg


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