[R] cluster analysis

[Venky]

Hi friends,

I have data like this



Group
  Employee size WOE Employee size2 Weight of Evidence 1081680995 0
0.12875537 0.128755 -0.30761 1007079896 1 0.48380133 -0.46544 -0.70464
1000507407 2 0.26029825 -0.46544 0.070221 1006400720 3 0.12875537 0.128755
0.151385 1006916029 4 0.12875537 -0.05955 0.320269 1006717587 5 0.12875537
1002032301 6 0.12875537 1007021594 7 0.26029825 1007118066 8 0.26029825
In this data first variable (Employee size) has 10 rows and variable 2
(employee size2) has only 5 rows

Question 1:there are different number of rows so that, we can able to do
K-means cluster or not?
Question 2:If we run k-means clustering in R answer not coming  because of
NA exists

I have used dataset<-na.omit(dataset)

But that time also i cannot able to run clustering

Please help me to find this answer

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[R] Restricting Decimal Places in the Output

[Shivi82]

Good Morning All,

I have working on a data set where I am finding mean and median for weight
variable on a daily basis. 
The code:

aggr<-aggregate(retail$weight,list(retail$ship.date),mean)
This is giving me an accurate result however with 4 decimal places for the
mean weight. In order to restrict it i used the following syntax:

format(aggr,digits=2,justify = c("right"))
After the execution of this code i have mean weight but now there are no
decimal places. Could you please advice what is incorrect in the syntax.

Thank you, Shivi



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Re: [R] Exporting from R to Excel or .csv

[Jeff Newmiller]

A CSV with multiple data frames would not conform to the standard definition of 
a CSV file.

The XLConnect package can be used to generate Excel workbooks. There are other 
packages also, but they are mostly either too simplified to allow filling 
multiple sheets or too finicky for my taste. That said, I avoid creating such 
complex output formats as much as possible... one data frame = one file is much 
more portable.
---
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Sent from my phone. Please excuse my brevity.

On June 16, 2015 6:31:11 PM CDT, Kevin Kowitski  wrote:
>Hello, 
>
>  Does anyone have some insight on how to; or where I can find better
>information on how to, export multiple data.frames of different
>dimensions to the same .csv or excel file?
>
>-Kevin
>__
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>and provide commented, minimal, self-contained, reproducible code.

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[R] Exporting from R to Excel or .csv

[Kevin Kowitski]

Hello, 

  Does anyone have some insight on how to; or where I can find better 
information on how to, export multiple data.frames of different dimensions to 
the same .csv or excel file?

-Kevin
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[R] hash::hash(...) assignment & clearing

[Murat Tasan]

The hash package implements hashmaps which must be cleared prior to
removal to free memory, e.g.:

> x <- hash(some_long_list_of_keys_and_values_here)
> clear(x)
> rm(x)

I first assumed this held for re-assignment, too... e.g. one should:

> x <- hash(some_long_list_of_keys_and_values_here)
> clear(x)
> x <- hash(some_other_long_list_of_keys_and_values_here)

With the clear(x) between the re-assignment of x to prevent memory leaks.

After some testing, though, I'm now not so sure.
I basically repeated this cycle:

> x <- hash(randomly_generated_long_list_of_keys_and_values_here)
> gc()

Memory usage grew only in the first few (3) cycles of this, but then
remained stable as x continued to be re-assigned.
Does anyone know if the assignment operator for a hash object has been
written to force a clear() operation?

Cheers,

-m

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Re: [R] problem with nlme, environments, and packages

[Greg Hather]

Thank you, Duncan!  Your suggestion worked!

Greg

On Tue, Jun 16, 2015 at 12:20 PM, Duncan Murdoch 
wrote:

> On 16/06/2015 10:34 AM, Greg Hather wrote:
> > Hi Duncan,
> >
> > I checked the global environment, and it was empty, so I think that
> > rules out the second possibility.  I posted a tarball at
> >
> >
> https://drive.google.com/file/d/0B8hBX90jtuLcaGtOUktqV2V4UUU/view?usp=sharing
> >
> > Thank you for your help!
> >
> > Greg
> >
>
> The problem is that nlme does a lot of evaluation of formula objects
> without taking their associated environment into account.  Fixing it
> doesn't look easy, because the evaluation happens in a lot of places.
>
> One workaround is to put the appropriate environment(s) on the search
> list before calling nlme().  This isn't perfect, because the search
> order will be wrong, but it will get you something.
>
> For example, your main_function could be
>
> main_function <- function(x){
>
>   library(nlme)
>   attach(parent.env(env=environment()))
>   result <- nlme(height ~ SSasymp(age, Asym, R0, lrc) +
> nonlinear_function(age),
>  data = Loblolly,
>  fixed = Asym + R0 + lrc ~ 1,
>  random = Asym ~ 1,
>  start = c(Asym = 103, R0 = -8.5, lrc = -3.3))
>   detach()
>   result
> }
>
> Duncan
>

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Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Bert Gunter]

Yes, indeed. Thanks, David.

But if you check, tapply, aggregate(), by(), etc. are all basically
wrappers to lapply() .So it's all a question of what syntax one feels most
comfortable with. However note that data.table, plyR stuff and perhaps
others are different in that they re-implement the underlying engines,
thereby gaining efficiencies that some folks may want as well as new syntax.


Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 1:22 PM, David L Carlson  wrote:

> Not in base, but in stats:
>
> > aggregate(md[,-4]==5, list(device=md$device), sum, na.rm=TRUE)
>   device a b c
> 1  1 1 2 0
> 2  2 0 1 0
> 3  3 1 0 2
>
> -
> David L Carlson
> Department of Anthropology
> Texas A&M University
> College Station, TX 77840-4352
>
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Bert
> Gunter
> Sent: Tuesday, June 16, 2015 3:02 PM
> To: Hadley Wickham
> Cc: r-help
> Subject: Re: [R] dplyr - counting a number of specific values in each
> column - for all columns at once
>
> ... my bad! -- I filed to read carefully.
>
> A base syntax version is:
>
> dat <- data.frame (a=sample(1:5,10,rep=TRUE),
>b=sample(3:7,10,rep=TRUE),
>g = sample(7:9,10,rep=TRUE))
>
> dev <- sample(1:3,10,rep=TRUE)
>
> sapply(dat,function(x)
>   tapply(x,dev,function(x)sum(x==5,na.rm=TRUE)))
>
>   a b g
> 1 2 0 0
> 2 1 3 0
> 3 2 1 0
>
> I think, no matter what, that there are 2 loops here: An outer one by
> column and an inner one by device within each column.
>
> Being both old and lazy, I have found it easier and more natural to stick
> with the basic functional syntax of the "apply" family of functions rather
> than to learn an alternative database type syntax (and semantics). My
> applications were never so large that the possible execution inefficiency
> mattered. However, it certainly might for others.  And of course, what is
> "natural" for me might not be for others.
>
> Cheers,
> Bert
>
> Bert Gunter
>
> "Data is not information. Information is not knowledge. And knowledge is
> certainly not wisdom."
>-- Clifford Stoll
>
> On Tue, Jun 16, 2015 at 12:47 PM, Hadley Wickham 
> wrote:
>
> > On Tue, Jun 16, 2015 at 12:24 PM, Dimitri Liakhovitski
> >  wrote:
> > > Hello!
> > >
> > > I have a data frame:
> > >
> > > md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
> > c(1,3,4,3,5,5),
> > >   device = c(1,1,2,2,3,3))
> > > myvars = c("a", "b", "c")
> > > md[2,3] <- NA
> > > md[4,1] <- NA
> > > md
> > >
> > > I want to count number of 5s in each column - by device. I can do it
> > like this:
> > >
> > > library(dplyr)
> > > group_by(md, device) %>%
> > > summarise(counts.a = sum(a==5, na.rm = T),
> > >   counts.b = sum(b==5, na.rm = T),
> > >   counts.c = sum(c==5, na.rm = T))
> > >
> > > However, in real life I'll have tons of variables (the length of
> > > 'myvars' can be very large) - so that I can't specify those counts.a,
> > > counts.b, etc. manually - dozens of times.
> > >
> > > Does dplyr allow to run the count of 5s on all 'myvars' columns at
> once?
> >
> > md %>%
> >   group_by(device) %>%
> >   summarise_each(funs(sum(. == 5, na.rm = TRUE)))
> >
> > Hadley
> >
> > --
> > http://had.co.nz/
> >
> > __
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> and provide commented, minimal, self-contained, reproducible code.
>

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Re: [R] reading daily snow depth data

[Alemu Tadesse]

Thank you Jim and Bob. This is really big help for me.

Jim, this is your second time to help me out.
Best

Alemu


On Tue, Jun 16, 2015 at 1:50 PM, boB Rudis  wrote:

> This look similar to snow data I used last year:
> https://github.com/hrbrmstr/snowfirst/blob/master/R/snowfirst.R
>
> All the data worked pretty well.
>
> On Tue, Jun 16, 2015 at 3:21 PM, jim holtman  wrote:
> > Here is an example of reading in the data.  After that it is a data frame
> > and should be able to process it with dplyr/data.table without much
> trouble:
> >
> >> x <- readLines("
> >
> http://www1.ncdc.noaa.gov/pub/data/snowmonitoring/fema/06-2015-dlysndpth.txt
> > ")
> >> writeLines(x, '/temp/snow.txt')  # save for testing
> >> head(x)
> > [1]
> > ""
> >
> > [2] "State:
> > AL"
> >
> > [3] "   Lat Lon  COOP# StnID State City/Station Name
> > County Elev  Jun 1  Jun 2  Jun 3  Jun
> > 4  Jun 5  Jun 6  Jun 7  Jun 8  Jun 9  Jun10
> > Jun11  Jun12  Jun13  Jun14  Jun15  Jun16"
> > [4] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
> > CALHOUN  594  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> > [5] " 33.83  -85.78 014209  AL JACKSONVILLE
> > CALHOUN  608  -.000  -.000  -.000
> > -.000  -.000  0.000  0.000  -.000  -.000
> > -.000  -.000  -.000  -.000  -.000  -.000
> -.000"
> > [6] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
> > COLBERT  540  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> >> z <- grepl("(^$)|(^State)|(^   Lat)", x)  # get lines to discard
> >> xm <- x[!z]  # remove info lines
> >> head(xm)
> > [1] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
> > CALHOUN  594  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> > [2] " 33.83  -85.78 014209  AL JACKSONVILLE
> > CALHOUN  608  -.000  -.000  -.000
> > -.000  -.000  0.000  0.000  -.000  -.000
> > -.000  -.000  -.000  -.000  -.000  -.000
> -.000"
> > [3] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
> > COLBERT  540  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> > [4] " 31.32  -85.45 012372  AL DOTHAN FAA AIRPORT
> > DALE 374  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> > [5] " 32.70  -87.58 013511  AL GREENSBORO
> > HALE 220  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> > [6] " 33.57  -86.74 010831  AL BIRMINGHAM AP ASOS
> > JEFFERSON615  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000
> > 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> >>
> >> # read in the data
> >> xf <- textConnection(xm)
> >> snow <- read.fwf(xf
> > + , width = c(6,8,7,10,3,32,26,6,rep(11,16))
> > + , comment.char = ''
> > + , as.is = TRUE
> > + )
> >> str(snow)
> > 'data.frame':   3067 obs. of  24 variables:
> >  $ V1 : num  33.6 33.8 34.7 31.3 32.7 ...
> >  $ V2 : num  -85.9 -85.8 -87.6 -85.5 -87.6 ...
> >  $ V3 : int  10272 14209 15749 12372 13511 10831 11225 14064 12245 15478
> ...
> >  $ V4 : chr  "  " "  " "  " "  " ...
> >  $ V5 : chr  "AL " "AL " "AL " "AL " ...
> >  $ V6 : chr  "ANNISTON ARPT ASOS  "
> > "JACKSONVILLE" "MUSCLE SHOALS AP"
> > "DOTHAN FAA AIRPORT  " ...
> >  $ V7 : chr  "CALHOUN   " "CALHOUN   "
> > "COLBERT   " "DALE  " ...
> >  $ V8 : int  594 608 540 374 220 615 461 624 100 215 ...
> >  $ V9 : num  0 - 0 0 0 ...
> >  $ V10: num  0 - 0 0 0 ...
> >  $ V11: num  0 - 0 0 0 ...
> >  $ V12: num  0 - 0 0 0 ...
> >  $ V13: num  0 - 0 0 0 ...
> >  $ V14: num  0 0 0 0 0 ...
> >  $ V15: num  0 0 0 0 0 ...
> >  $ V16: num  0 - 0 0 0 ...
> >  $ V17: num  0 - 0 0 0 ...
> >  $ V18: num  0 - 0 0 0 ...
> >  $ V19: num  0 - 0 0 0 ...
> >  $ V20: num  0 - 0 0 0 ...
> >

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[David Winsemius]

On Jun 16, 2015, at 11:18 AM, Clint Bowman wrote:

> Thanks, Dimitri.  Burt is the real wizard here--I'll bet he can conjure up an 
> elegant solution.

This would be base method:

> by( md[-4]==5, md[4], colSums)
device: 1
a b c 
1 2 0 
- 
device: 2
a b c 
1 1 0 
- 
device: 3
a b c 
1 0 2 

You could adapt that to use myvars:

> by(md[myvars]==5, md[!names(md) %in% myvars],colSums)
device: 1
a b c 
1 2 0 
- 
device: 2
a b c 
1 1 0 
- 
device: 3
a b c 
1 0 2 

And if you want them smushed into a matrix then use rbind:

> do.call( rbind, by(md[myvars]==5, md[!names(md) %in% myvars],colSums))
  a b c
1 1 2 0
2 1 1 0
3 1 0 2

> 
> For me, just reaching a desired endpoint is enough.
> 
> Clint
> 
> Clint Bowman  INTERNET:   cl...@ecy.wa.gov
> Air Quality Modeler   INTERNET:   cl...@math.utah.edu
> Department of Ecology VOICE:  (360) 407-6815
> PO Box 47600  FAX:(360) 407-7534
> Olympia, WA 98504-7600
> 
>USPS:   PO Box 47600, Olympia, WA 98504-7600
>Parcels:300 Desmond Drive, Lacey, WA 98503-1274
> 
> On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:
> 
>> Thank you, Clint.
>> That's the thing: it's relatively easy to do it in base, but the
>> resulting code is not THAT simple.
>> I thought dplyr would make it easy...
>> 
>> On Tue, Jun 16, 2015 at 2:06 PM, Clint Bowman  wrote:
>>> May want to add headers but the following provides the device number with
>>> each set fo sums:
>>> 
>>> for (dev in (unique(md$device)))
>>> {cat(colSums(subset(md,md$device==dev)==5,na.rm=T),dev,"\n")}
>>> 
>>> Clint BowmanINTERNET:   cl...@ecy.wa.gov
>>> Air Quality Modeler INTERNET:   cl...@math.utah.edu
>>> Department of Ecology   VOICE:  (360) 407-6815
>>> PO Box 47600FAX:(360) 407-7534
>>> Olympia, WA 98504-7600
>>> 
>>>USPS:   PO Box 47600, Olympia, WA 98504-7600
>>>Parcels:300 Desmond Drive, Lacey, WA 98503-1274
>>> 
>>> On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:
>>> 
 Except, of course, Bert, that you forgot that it had to be done by
 device. Your solution ignores the device.
 
 md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
 c(1,3,4,3,5,5),
 device = c(1,1,2,2,3,3))
 myvars = c("a", "b", "c")
 md[2,3] <- NA
 md[4,1] <- NA
 md
 vapply(md[myvars], function(x) sum(x==5,na.rm=TRUE),1L)
 
 But the result should be by device.
 
 On Tue, Jun 16, 2015 at 1:56 PM, Dimitri Liakhovitski
  wrote:
> 
> Thank you, Bert.
> I'll be honest - I am just learning dplyr and was wondering if one
> could do it in dplyr.
> But of course your solution is perfect...
> 
> On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter 
> wrote:
>> 
>> Well, dplyr seems a bit of overkill as it's so simple with plain old
>> vapply() in base R :
>> 
>> 
>>> dat <- data.frame (a=sample(1:5,10,rep=TRUE),
>> 
>> +b=sample(3:7,10,rep=TRUE),
>> +g = sample(7:9,10,rep=TRUE))
>> 
>>> vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)
>> 
>> 
>> a b g
>> 5 4 0
>> 
>> 
>> 
>> Cheers,
>> Bert
>> 
>> Bert Gunter
>> 
>> "Data is not information. Information is not knowledge. And knowledge is
>> certainly not wisdom."
>>   -- Clifford Stoll
>> 
>> On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
>>  wrote:
>>> 
>>> 
>>> Hello!
>>> 
>>> I have a data frame:
>>> 
>>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
>>> c(1,3,4,3,5,5),
>>>  device = c(1,1,2,2,3,3))
>>> myvars = c("a", "b", "c")
>>> md[2,3] <- NA
>>> md[4,1] <- NA
>>> md
>>> 
>>> I want to count number of 5s in each column - by device. I can do it
>>> like
>>> this:
>>> 
>>> library(dplyr)
>>> group_by(md, device) %>%
>>> summarise(counts.a = sum(a==5, na.rm = T),
>>>  counts.b = sum(b==5, na.rm = T),
>>>  counts.c = sum(c==5, na.rm = T))
>>> 
>>> However, in real life I'll have tons of variables (the length of
>>> 'myvars' can be very large) - so that I can't specify those counts.a,
>>> counts.b, etc. manually - dozens of times.
>>> 
>>> Does dplyr allow to run the count of 5s on all 'myvars' columns at
>>> once?
>>> 
>>> 
>>> --
>>> Dimitri Liakhovitski
>>> 
>>> __
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEA

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[David L Carlson]

Not in base, but in stats:

> aggregate(md[,-4]==5, list(device=md$device), sum, na.rm=TRUE)
  device a b c
1  1 1 2 0
2  2 0 1 0
3  3 1 0 2

-
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter
Sent: Tuesday, June 16, 2015 3:02 PM
To: Hadley Wickham
Cc: r-help
Subject: Re: [R] dplyr - counting a number of specific values in each column - 
for all columns at once

... my bad! -- I filed to read carefully.

A base syntax version is:

dat <- data.frame (a=sample(1:5,10,rep=TRUE),
   b=sample(3:7,10,rep=TRUE),
   g = sample(7:9,10,rep=TRUE))

dev <- sample(1:3,10,rep=TRUE)

sapply(dat,function(x)
  tapply(x,dev,function(x)sum(x==5,na.rm=TRUE)))

  a b g
1 2 0 0
2 1 3 0
3 2 1 0

I think, no matter what, that there are 2 loops here: An outer one by
column and an inner one by device within each column.

Being both old and lazy, I have found it easier and more natural to stick
with the basic functional syntax of the "apply" family of functions rather
than to learn an alternative database type syntax (and semantics). My
applications were never so large that the possible execution inefficiency
mattered. However, it certainly might for others.  And of course, what is
"natural" for me might not be for others.

Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 12:47 PM, Hadley Wickham 
wrote:

> On Tue, Jun 16, 2015 at 12:24 PM, Dimitri Liakhovitski
>  wrote:
> > Hello!
> >
> > I have a data frame:
> >
> > md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
> c(1,3,4,3,5,5),
> >   device = c(1,1,2,2,3,3))
> > myvars = c("a", "b", "c")
> > md[2,3] <- NA
> > md[4,1] <- NA
> > md
> >
> > I want to count number of 5s in each column - by device. I can do it
> like this:
> >
> > library(dplyr)
> > group_by(md, device) %>%
> > summarise(counts.a = sum(a==5, na.rm = T),
> >   counts.b = sum(b==5, na.rm = T),
> >   counts.c = sum(c==5, na.rm = T))
> >
> > However, in real life I'll have tons of variables (the length of
> > 'myvars' can be very large) - so that I can't specify those counts.a,
> > counts.b, etc. manually - dozens of times.
> >
> > Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>
> md %>%
>   group_by(device) %>%
>   summarise_each(funs(sum(. == 5, na.rm = TRUE)))
>
> Hadley
>
> --
> http://had.co.nz/
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Bert Gunter]

... my bad! -- I filed to read carefully.

A base syntax version is:

dat <- data.frame (a=sample(1:5,10,rep=TRUE),
   b=sample(3:7,10,rep=TRUE),
   g = sample(7:9,10,rep=TRUE))

dev <- sample(1:3,10,rep=TRUE)

sapply(dat,function(x)
  tapply(x,dev,function(x)sum(x==5,na.rm=TRUE)))

  a b g
1 2 0 0
2 1 3 0
3 2 1 0

I think, no matter what, that there are 2 loops here: An outer one by
column and an inner one by device within each column.

Being both old and lazy, I have found it easier and more natural to stick
with the basic functional syntax of the "apply" family of functions rather
than to learn an alternative database type syntax (and semantics). My
applications were never so large that the possible execution inefficiency
mattered. However, it certainly might for others.  And of course, what is
"natural" for me might not be for others.

Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 12:47 PM, Hadley Wickham 
wrote:

> On Tue, Jun 16, 2015 at 12:24 PM, Dimitri Liakhovitski
>  wrote:
> > Hello!
> >
> > I have a data frame:
> >
> > md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
> c(1,3,4,3,5,5),
> >   device = c(1,1,2,2,3,3))
> > myvars = c("a", "b", "c")
> > md[2,3] <- NA
> > md[4,1] <- NA
> > md
> >
> > I want to count number of 5s in each column - by device. I can do it
> like this:
> >
> > library(dplyr)
> > group_by(md, device) %>%
> > summarise(counts.a = sum(a==5, na.rm = T),
> >   counts.b = sum(b==5, na.rm = T),
> >   counts.c = sum(c==5, na.rm = T))
> >
> > However, in real life I'll have tons of variables (the length of
> > 'myvars' can be very large) - so that I can't specify those counts.a,
> > counts.b, etc. manually - dozens of times.
> >
> > Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>
> md %>%
>   group_by(device) %>%
>   summarise_each(funs(sum(. == 5, na.rm = TRUE)))
>
> Hadley
>
> --
> http://had.co.nz/
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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[R] rdde : DDE connections on R

[Juan Manuel Truppia]

Hi all, I'm building a new package for DDE connections on R. It's called
rdde and lives in https://bitbucket.org/juancentro/rdde.
It's in alpha stage, but operational. It has a very simple vignette which
explains the main reason you should try rdde vs tcltk2 (the only other
option available) : performance.
rdde allows the user to reuse connections (conversations). Establishing a
conversation is the most expensive operation in DDE.

Hope someone finds it useful

Regards

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[R] mlogit error

[mikebarr]

Hello,

I am trying to run a mixed logit model (panel form) with the mlogit package.
I am running into the following error: "Error in random.nb[, sel, drop = F]
: subscript out of bounds".

I have searched the R Help forum (and online) and see no instances of this
error. Below is the coding that I used which follows along with
"Discrete-Choice Logit Models with R" by Philip A. Viton
(http://facweb.knowlton.ohio-state.edu/pviton/courses2/crp5700/5700-mlogit.pdf).
My dataset consists of 244 individuals each answering 8 choices between 3
alternatives. 

> clogit <- read.csv("/Users/name/Desktop/DCEinR/R365.csv")
> save(clogit,file="/Users/name/Desktop/DCEinR/clogit.rdata")
> load("/Users/name/Desktop/DCEinR/clogit.rdata")
> clogit$mode.ids<-factor(rep(1:3,244))
> clogit$mode.ids<-factor(rep(1:3, 244), labels=c("c1","c2","sq"))
> clogit$indivs<-factor(rep(1:244,each=24))
> CLOGIT<-mlogit.data(clogit,shape="long",
> choice="choice",alt.var="mode.ids", id.var="indivs")
> CLOGIT.mxl <- mlogit(Choice~-1+ASC+Price+Payment+Penalty+Length+Local|0,
> CLOGIT, rpar=c(ASC='n', Price='n', Payment='n', Penalty='n', Length='n',
> Local='n'), R=100, halton=NA, print.level=0, panel=TRUE)

Are there any suggestions on: 1) what does this error mean; and 2) how to
fix this issue?

Thanks in advance.



--
View this message in context: 
http://r.789695.n4.nabble.com/mlogit-error-tp4708706.html
Sent from the R help mailing list archive at Nabble.com.

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Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

Thank you guys - it's a great learning: 'summarise_each' and 'funs'

On Tue, Jun 16, 2015 at 3:47 PM, Hadley Wickham  wrote:
> On Tue, Jun 16, 2015 at 12:24 PM, Dimitri Liakhovitski
>  wrote:
>> Hello!
>>
>> I have a data frame:
>>
>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
>>   device = c(1,1,2,2,3,3))
>> myvars = c("a", "b", "c")
>> md[2,3] <- NA
>> md[4,1] <- NA
>> md
>>
>> I want to count number of 5s in each column - by device. I can do it like 
>> this:
>>
>> library(dplyr)
>> group_by(md, device) %>%
>> summarise(counts.a = sum(a==5, na.rm = T),
>>   counts.b = sum(b==5, na.rm = T),
>>   counts.c = sum(c==5, na.rm = T))
>>
>> However, in real life I'll have tons of variables (the length of
>> 'myvars' can be very large) - so that I can't specify those counts.a,
>> counts.b, etc. manually - dozens of times.
>>
>> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>
> md %>%
>   group_by(device) %>%
>   summarise_each(funs(sum(. == 5, na.rm = TRUE)))
>
> Hadley
>
> --
> http://had.co.nz/



-- 
Dimitri Liakhovitski

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Re: [R] reading daily snow depth data

[boB Rudis]

This look similar to snow data I used last year:
https://github.com/hrbrmstr/snowfirst/blob/master/R/snowfirst.R

All the data worked pretty well.

On Tue, Jun 16, 2015 at 3:21 PM, jim holtman  wrote:
> Here is an example of reading in the data.  After that it is a data frame
> and should be able to process it with dplyr/data.table without much trouble:
>
>> x <- readLines("
> http://www1.ncdc.noaa.gov/pub/data/snowmonitoring/fema/06-2015-dlysndpth.txt
> ")
>> writeLines(x, '/temp/snow.txt')  # save for testing
>> head(x)
> [1]
> ""
>
> [2] "State:
> AL"
>
> [3] "   Lat Lon  COOP# StnID State City/Station Name
> County Elev  Jun 1  Jun 2  Jun 3  Jun
> 4  Jun 5  Jun 6  Jun 7  Jun 8  Jun 9  Jun10
> Jun11  Jun12  Jun13  Jun14  Jun15  Jun16"
> [4] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
> CALHOUN  594  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> [5] " 33.83  -85.78 014209  AL JACKSONVILLE
> CALHOUN  608  -.000  -.000  -.000
> -.000  -.000  0.000  0.000  -.000  -.000
> -.000  -.000  -.000  -.000  -.000  -.000  -.000"
> [6] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
> COLBERT  540  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
>> z <- grepl("(^$)|(^State)|(^   Lat)", x)  # get lines to discard
>> xm <- x[!z]  # remove info lines
>> head(xm)
> [1] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
> CALHOUN  594  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> [2] " 33.83  -85.78 014209  AL JACKSONVILLE
> CALHOUN  608  -.000  -.000  -.000
> -.000  -.000  0.000  0.000  -.000  -.000
> -.000  -.000  -.000  -.000  -.000  -.000  -.000"
> [3] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
> COLBERT  540  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> [4] " 31.32  -85.45 012372  AL DOTHAN FAA AIRPORT
> DALE 374  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> [5] " 32.70  -87.58 013511  AL GREENSBORO
> HALE 220  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> [6] " 33.57  -86.74 010831  AL BIRMINGHAM AP ASOS
> JEFFERSON615  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000
> 0.000  0.000  0.000  0.000  0.000  0.000  -.000"
>>
>> # read in the data
>> xf <- textConnection(xm)
>> snow <- read.fwf(xf
> + , width = c(6,8,7,10,3,32,26,6,rep(11,16))
> + , comment.char = ''
> + , as.is = TRUE
> + )
>> str(snow)
> 'data.frame':   3067 obs. of  24 variables:
>  $ V1 : num  33.6 33.8 34.7 31.3 32.7 ...
>  $ V2 : num  -85.9 -85.8 -87.6 -85.5 -87.6 ...
>  $ V3 : int  10272 14209 15749 12372 13511 10831 11225 14064 12245 15478 ...
>  $ V4 : chr  "  " "  " "  " "  " ...
>  $ V5 : chr  "AL " "AL " "AL " "AL " ...
>  $ V6 : chr  "ANNISTON ARPT ASOS  "
> "JACKSONVILLE" "MUSCLE SHOALS AP"
> "DOTHAN FAA AIRPORT  " ...
>  $ V7 : chr  "CALHOUN   " "CALHOUN   "
> "COLBERT   " "DALE  " ...
>  $ V8 : int  594 608 540 374 220 615 461 624 100 215 ...
>  $ V9 : num  0 - 0 0 0 ...
>  $ V10: num  0 - 0 0 0 ...
>  $ V11: num  0 - 0 0 0 ...
>  $ V12: num  0 - 0 0 0 ...
>  $ V13: num  0 - 0 0 0 ...
>  $ V14: num  0 0 0 0 0 ...
>  $ V15: num  0 0 0 0 0 ...
>  $ V16: num  0 - 0 0 0 ...
>  $ V17: num  0 - 0 0 0 ...
>  $ V18: num  0 - 0 0 0 ...
>  $ V19: num  0 - 0 0 0 ...
>  $ V20: num  0 - 0 0 0 ...
>  $ V21: num  0 - 0 0 0 ...
>  $ V22: num  0 - 0 0 0 ...
>  $ V23: num  0 - 0 0 0 ...
>  $ V24: num  - - - - - ...
>> table(snow$V5)  # tally up the states
> AK  AL  AR  AZ  CA  CO  CT  DE  FL  GA  HI  IA  ID  IL  IN  KS  KY  LA  MA
> MD  ME  MI  MN  MO  MS  MT
>  72  18  65  55  99 128  10   1  30  33   6 112  57 103  85  90  49  29

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Hadley Wickham]

On Tue, Jun 16, 2015 at 12:24 PM, Dimitri Liakhovitski
 wrote:
> Hello!
>
> I have a data frame:
>
> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
>   device = c(1,1,2,2,3,3))
> myvars = c("a", "b", "c")
> md[2,3] <- NA
> md[4,1] <- NA
> md
>
> I want to count number of 5s in each column - by device. I can do it like 
> this:
>
> library(dplyr)
> group_by(md, device) %>%
> summarise(counts.a = sum(a==5, na.rm = T),
>   counts.b = sum(b==5, na.rm = T),
>   counts.c = sum(c==5, na.rm = T))
>
> However, in real life I'll have tons of variables (the length of
> 'myvars' can be very large) - so that I can't specify those counts.a,
> counts.b, etc. manually - dozens of times.
>
> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?

md %>%
  group_by(device) %>%
  summarise_each(funs(sum(. == 5, na.rm = TRUE)))

Hadley

-- 
http://had.co.nz/

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Re: [R] reading daily snow depth data

[jim holtman]

Here is an example of reading in the data.  After that it is a data frame
and should be able to process it with dplyr/data.table without much trouble:

> x <- readLines("
http://www1.ncdc.noaa.gov/pub/data/snowmonitoring/fema/06-2015-dlysndpth.txt
")
> writeLines(x, '/temp/snow.txt')  # save for testing
> head(x)
[1]
""

[2] "State:
AL"

[3] "   Lat Lon  COOP# StnID State City/Station Name
County Elev  Jun 1  Jun 2  Jun 3  Jun
4  Jun 5  Jun 6  Jun 7  Jun 8  Jun 9  Jun10
Jun11  Jun12  Jun13  Jun14  Jun15  Jun16"
[4] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
CALHOUN  594  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
[5] " 33.83  -85.78 014209  AL JACKSONVILLE
CALHOUN  608  -.000  -.000  -.000
-.000  -.000  0.000  0.000  -.000  -.000
-.000  -.000  -.000  -.000  -.000  -.000  -.000"
[6] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
COLBERT  540  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
> z <- grepl("(^$)|(^State)|(^   Lat)", x)  # get lines to discard
> xm <- x[!z]  # remove info lines
> head(xm)
[1] " 33.59  -85.86 010272  AL ANNISTON ARPT ASOS
CALHOUN  594  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
[2] " 33.83  -85.78 014209  AL JACKSONVILLE
CALHOUN  608  -.000  -.000  -.000
-.000  -.000  0.000  0.000  -.000  -.000
-.000  -.000  -.000  -.000  -.000  -.000  -.000"
[3] " 34.74  -87.60 015749  AL MUSCLE SHOALS AP
COLBERT  540  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
[4] " 31.32  -85.45 012372  AL DOTHAN FAA AIRPORT
DALE 374  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
[5] " 32.70  -87.58 013511  AL GREENSBORO
HALE 220  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
[6] " 33.57  -86.74 010831  AL BIRMINGHAM AP ASOS
JEFFERSON615  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000
0.000  0.000  0.000  0.000  0.000  0.000  -.000"
>
> # read in the data
> xf <- textConnection(xm)
> snow <- read.fwf(xf
+ , width = c(6,8,7,10,3,32,26,6,rep(11,16))
+ , comment.char = ''
+ , as.is = TRUE
+ )
> str(snow)
'data.frame':   3067 obs. of  24 variables:
 $ V1 : num  33.6 33.8 34.7 31.3 32.7 ...
 $ V2 : num  -85.9 -85.8 -87.6 -85.5 -87.6 ...
 $ V3 : int  10272 14209 15749 12372 13511 10831 11225 14064 12245 15478 ...
 $ V4 : chr  "  " "  " "  " "  " ...
 $ V5 : chr  "AL " "AL " "AL " "AL " ...
 $ V6 : chr  "ANNISTON ARPT ASOS  "
"JACKSONVILLE" "MUSCLE SHOALS AP"
"DOTHAN FAA AIRPORT  " ...
 $ V7 : chr  "CALHOUN   " "CALHOUN   "
"COLBERT   " "DALE  " ...
 $ V8 : int  594 608 540 374 220 615 461 624 100 215 ...
 $ V9 : num  0 - 0 0 0 ...
 $ V10: num  0 - 0 0 0 ...
 $ V11: num  0 - 0 0 0 ...
 $ V12: num  0 - 0 0 0 ...
 $ V13: num  0 - 0 0 0 ...
 $ V14: num  0 0 0 0 0 ...
 $ V15: num  0 0 0 0 0 ...
 $ V16: num  0 - 0 0 0 ...
 $ V17: num  0 - 0 0 0 ...
 $ V18: num  0 - 0 0 0 ...
 $ V19: num  0 - 0 0 0 ...
 $ V20: num  0 - 0 0 0 ...
 $ V21: num  0 - 0 0 0 ...
 $ V22: num  0 - 0 0 0 ...
 $ V23: num  0 - 0 0 0 ...
 $ V24: num  - - - - - ...
> table(snow$V5)  # tally up the states
AK  AL  AR  AZ  CA  CO  CT  DE  FL  GA  HI  IA  ID  IL  IN  KS  KY  LA  MA
MD  ME  MI  MN  MO  MS  MT
 72  18  65  55  99 128  10   1  30  33   6 112  57 103  85  90  49  29
35  14  40  86  90 124  27 113
NC  ND  NE  NH  NJ  NM  NV  NY  OH  OK  OR  PA  RI  SC  SD  TN  TX  UT  VA
VT  WA  WI  WV  WY
 45  19 136  22  13  53  65  76  31 106  51  84   2  30  79  64 185  68
70  18  56 103  36  84
>


Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.

On Tue, Jun 16, 2015 

[R] Polysomnographic data analysis with R?

[Charles Novaes de Santana]

Dear all,

Do you know if there is any R package or function we can use to analyze
polysomnographic data?

For example, something that can import an EDF file (or in a different
format) and can give some properties of the polysomnographic records like
periods of different sleep phases, etc.

I looked for it in the web and I didn't find. But maybe I used the wrong
key-words.

Any help will be much appreciated!

Best,

Charles
-- 
Um axé! :)

--
Charles Novaes de Santana, PhD
http://www.imedea.uib-csic.es/~charles

[[alternative HTML version deleted]]

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and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

Thank you, Clint.
That's the thing: it's relatively easy to do it in base, but the
resulting code is not THAT simple.
I thought dplyr would make it easy...

On Tue, Jun 16, 2015 at 2:06 PM, Clint Bowman  wrote:
> May want to add headers but the following provides the device number with
> each set fo sums:
>
> for (dev in (unique(md$device)))
> {cat(colSums(subset(md,md$device==dev)==5,na.rm=T),dev,"\n")}
>
> Clint BowmanINTERNET:   cl...@ecy.wa.gov
> Air Quality Modeler INTERNET:   cl...@math.utah.edu
> Department of Ecology   VOICE:  (360) 407-6815
> PO Box 47600FAX:(360) 407-7534
> Olympia, WA 98504-7600
>
> USPS:   PO Box 47600, Olympia, WA 98504-7600
> Parcels:300 Desmond Drive, Lacey, WA 98503-1274
>
> On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:
>
>> Except, of course, Bert, that you forgot that it had to be done by
>> device. Your solution ignores the device.
>>
>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
>> c(1,3,4,3,5,5),
>>  device = c(1,1,2,2,3,3))
>> myvars = c("a", "b", "c")
>> md[2,3] <- NA
>> md[4,1] <- NA
>> md
>> vapply(md[myvars], function(x) sum(x==5,na.rm=TRUE),1L)
>>
>> But the result should be by device.
>>
>> On Tue, Jun 16, 2015 at 1:56 PM, Dimitri Liakhovitski
>>  wrote:
>>>
>>> Thank you, Bert.
>>> I'll be honest - I am just learning dplyr and was wondering if one
>>> could do it in dplyr.
>>> But of course your solution is perfect...
>>>
>>> On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter 
>>> wrote:

 Well, dplyr seems a bit of overkill as it's so simple with plain old
 vapply() in base R :


> dat <- data.frame (a=sample(1:5,10,rep=TRUE),

 +b=sample(3:7,10,rep=TRUE),
 +g = sample(7:9,10,rep=TRUE))

> vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)


 a b g
 5 4 0



 Cheers,
 Bert

 Bert Gunter

 "Data is not information. Information is not knowledge. And knowledge is
 certainly not wisdom."
-- Clifford Stoll

 On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
  wrote:
>
>
> Hello!
>
> I have a data frame:
>
> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
> c(1,3,4,3,5,5),
>   device = c(1,1,2,2,3,3))
> myvars = c("a", "b", "c")
> md[2,3] <- NA
> md[4,1] <- NA
> md
>
> I want to count number of 5s in each column - by device. I can do it
> like
> this:
>
> library(dplyr)
> group_by(md, device) %>%
> summarise(counts.a = sum(a==5, na.rm = T),
>   counts.b = sum(b==5, na.rm = T),
>   counts.c = sum(c==5, na.rm = T))
>
> However, in real life I'll have tons of variables (the length of
> 'myvars' can be very large) - so that I can't specify those counts.a,
> counts.b, etc. manually - dozens of times.
>
> Does dplyr allow to run the count of 5s on all 'myvars' columns at
> once?
>
>
> --
> Dimitri Liakhovitski
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



>>>
>>>
>>>
>>> --
>>> Dimitri Liakhovitski
>>
>>
>>
>>
>> --
>> Dimitri Liakhovitski
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>



-- 
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Clint Bowman]

Thanks, Dimitri.  Burt is the real wizard here--I'll bet he can conjure up 
an elegant solution.


For me, just reaching a desired endpoint is enough.

Clint

Clint BowmanINTERNET:   cl...@ecy.wa.gov
Air Quality Modeler INTERNET:   cl...@math.utah.edu
Department of Ecology   VOICE:  (360) 407-6815
PO Box 47600FAX:(360) 407-7534
Olympia, WA 98504-7600

USPS:   PO Box 47600, Olympia, WA 98504-7600
Parcels:300 Desmond Drive, Lacey, WA 98503-1274

On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:


Thank you, Clint.
That's the thing: it's relatively easy to do it in base, but the
resulting code is not THAT simple.
I thought dplyr would make it easy...

On Tue, Jun 16, 2015 at 2:06 PM, Clint Bowman  wrote:

May want to add headers but the following provides the device number with
each set fo sums:

for (dev in (unique(md$device)))
{cat(colSums(subset(md,md$device==dev)==5,na.rm=T),dev,"\n")}

Clint BowmanINTERNET:   cl...@ecy.wa.gov
Air Quality Modeler INTERNET:   cl...@math.utah.edu
Department of Ecology   VOICE:  (360) 407-6815
PO Box 47600FAX:(360) 407-7534
Olympia, WA 98504-7600

USPS:   PO Box 47600, Olympia, WA 98504-7600
Parcels:300 Desmond Drive, Lacey, WA 98503-1274

On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:


Except, of course, Bert, that you forgot that it had to be done by
device. Your solution ignores the device.

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
c(1,3,4,3,5,5),
 device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md
vapply(md[myvars], function(x) sum(x==5,na.rm=TRUE),1L)

But the result should be by device.

On Tue, Jun 16, 2015 at 1:56 PM, Dimitri Liakhovitski
 wrote:


Thank you, Bert.
I'll be honest - I am just learning dplyr and was wondering if one
could do it in dplyr.
But of course your solution is perfect...

On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter 
wrote:


Well, dplyr seems a bit of overkill as it's so simple with plain old
vapply() in base R :



dat <- data.frame (a=sample(1:5,10,rep=TRUE),


+b=sample(3:7,10,rep=TRUE),
+g = sample(7:9,10,rep=TRUE))


vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)



a b g
5 4 0



Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
 wrote:



Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
c(1,3,4,3,5,5),
  device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it
like
this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
  counts.b = sum(b==5, na.rm = T),
  counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at
once?


--
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.








--
Dimitri Liakhovitski





--
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.







--
Dimitri Liakhovitski



__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Clint Bowman]

May want to add headers but the following provides the device number with 
each set fo sums:


for (dev in (unique(md$device))) 
{cat(colSums(subset(md,md$device==dev)==5,na.rm=T),dev,"\n")}


Clint BowmanINTERNET:   cl...@ecy.wa.gov
Air Quality Modeler INTERNET:   cl...@math.utah.edu
Department of Ecology   VOICE:  (360) 407-6815
PO Box 47600FAX:(360) 407-7534
Olympia, WA 98504-7600

USPS:   PO Box 47600, Olympia, WA 98504-7600
Parcels:300 Desmond Drive, Lacey, WA 98503-1274

On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:


Except, of course, Bert, that you forgot that it had to be done by
device. Your solution ignores the device.

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
 device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md
vapply(md[myvars], function(x) sum(x==5,na.rm=TRUE),1L)

But the result should be by device.

On Tue, Jun 16, 2015 at 1:56 PM, Dimitri Liakhovitski
 wrote:

Thank you, Bert.
I'll be honest - I am just learning dplyr and was wondering if one
could do it in dplyr.
But of course your solution is perfect...

On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter  wrote:

Well, dplyr seems a bit of overkill as it's so simple with plain old
vapply() in base R :



dat <- data.frame (a=sample(1:5,10,rep=TRUE),

+b=sample(3:7,10,rep=TRUE),
+g = sample(7:9,10,rep=TRUE))


vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)


a b g
5 4 0



Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
 wrote:


Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
c(1,3,4,3,5,5),
  device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it like
this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
  counts.b = sum(b==5, na.rm = T),
  counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at once?


--
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.







--
Dimitri Liakhovitski




--
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.



__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

Except, of course, Bert, that you forgot that it had to be done by
device. Your solution ignores the device.

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
  device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md
vapply(md[myvars], function(x) sum(x==5,na.rm=TRUE),1L)

But the result should be by device.

On Tue, Jun 16, 2015 at 1:56 PM, Dimitri Liakhovitski
 wrote:
> Thank you, Bert.
> I'll be honest - I am just learning dplyr and was wondering if one
> could do it in dplyr.
> But of course your solution is perfect...
>
> On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter  wrote:
>> Well, dplyr seems a bit of overkill as it's so simple with plain old
>> vapply() in base R :
>>
>>
>>> dat <- data.frame (a=sample(1:5,10,rep=TRUE),
>> +b=sample(3:7,10,rep=TRUE),
>> +g = sample(7:9,10,rep=TRUE))
>>
>>> vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)
>>
>> a b g
>> 5 4 0
>>
>>
>>
>> Cheers,
>> Bert
>>
>> Bert Gunter
>>
>> "Data is not information. Information is not knowledge. And knowledge is
>> certainly not wisdom."
>>-- Clifford Stoll
>>
>> On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
>>  wrote:
>>>
>>> Hello!
>>>
>>> I have a data frame:
>>>
>>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
>>> c(1,3,4,3,5,5),
>>>   device = c(1,1,2,2,3,3))
>>> myvars = c("a", "b", "c")
>>> md[2,3] <- NA
>>> md[4,1] <- NA
>>> md
>>>
>>> I want to count number of 5s in each column - by device. I can do it like
>>> this:
>>>
>>> library(dplyr)
>>> group_by(md, device) %>%
>>> summarise(counts.a = sum(a==5, na.rm = T),
>>>   counts.b = sum(b==5, na.rm = T),
>>>   counts.c = sum(c==5, na.rm = T))
>>>
>>> However, in real life I'll have tons of variables (the length of
>>> 'myvars' can be very large) - so that I can't specify those counts.a,
>>> counts.b, etc. manually - dozens of times.
>>>
>>> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>>>
>>>
>>> --
>>> Dimitri Liakhovitski
>>>
>>> __
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>
>
> --
> Dimitri Liakhovitski



-- 
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

Thank you, Bert.
I'll be honest - I am just learning dplyr and was wondering if one
could do it in dplyr.
But of course your solution is perfect...

On Tue, Jun 16, 2015 at 1:50 PM, Bert Gunter  wrote:
> Well, dplyr seems a bit of overkill as it's so simple with plain old
> vapply() in base R :
>
>
>> dat <- data.frame (a=sample(1:5,10,rep=TRUE),
> +b=sample(3:7,10,rep=TRUE),
> +g = sample(7:9,10,rep=TRUE))
>
>> vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)
>
> a b g
> 5 4 0
>
>
>
> Cheers,
> Bert
>
> Bert Gunter
>
> "Data is not information. Information is not knowledge. And knowledge is
> certainly not wisdom."
>-- Clifford Stoll
>
> On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
>  wrote:
>>
>> Hello!
>>
>> I have a data frame:
>>
>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
>> c(1,3,4,3,5,5),
>>   device = c(1,1,2,2,3,3))
>> myvars = c("a", "b", "c")
>> md[2,3] <- NA
>> md[4,1] <- NA
>> md
>>
>> I want to count number of 5s in each column - by device. I can do it like
>> this:
>>
>> library(dplyr)
>> group_by(md, device) %>%
>> summarise(counts.a = sum(a==5, na.rm = T),
>>   counts.b = sum(b==5, na.rm = T),
>>   counts.c = sum(c==5, na.rm = T))
>>
>> However, in real life I'll have tons of variables (the length of
>> 'myvars' can be very large) - so that I can't specify those counts.a,
>> counts.b, etc. manually - dozens of times.
>>
>> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>>
>>
>> --
>> Dimitri Liakhovitski
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>



-- 
Dimitri Liakhovitski

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Bert Gunter]

Well, dplyr seems a bit of overkill as it's so simple with plain old
vapply() in base R :


> dat <- data.frame (a=sample(1:5,10,rep=TRUE),
+b=sample(3:7,10,rep=TRUE),
+g = sample(7:9,10,rep=TRUE))

> vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)

a b g
5 4 0



Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski <
dimitri.liakhovit...@gmail.com> wrote:

> Hello!
>
> I have a data frame:
>
> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
> c(1,3,4,3,5,5),
>   device = c(1,1,2,2,3,3))
> myvars = c("a", "b", "c")
> md[2,3] <- NA
> md[4,1] <- NA
> md
>
> I want to count number of 5s in each column - by device. I can do it like
> this:
>
> library(dplyr)
> group_by(md, device) %>%
> summarise(counts.a = sum(a==5, na.rm = T),
>   counts.b = sum(b==5, na.rm = T),
>   counts.c = sum(c==5, na.rm = T))
>
> However, in real life I'll have tons of variables (the length of
> 'myvars' can be very large) - so that I can't specify those counts.a,
> counts.b, etc. manually - dozens of times.
>
> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>
>
> --
> Dimitri Liakhovitski
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Clint Bowman]

It would help if I could see beyond my allergy meds.

A start could be:

colSums(subset(md,md$device==1)==5,na.rm=T)
colSums(subset(md,md$device==2)==5,na.rm=T)
colSums(subset(md,md$device==3)==5,na.rm=T)


Clint BowmanINTERNET:   cl...@ecy.wa.gov
Air Quality Modeler INTERNET:   cl...@math.utah.edu
Department of Ecology   VOICE:  (360) 407-6815
PO Box 47600FAX:(360) 407-7534
Olympia, WA 98504-7600

USPS:   PO Box 47600, Olympia, WA 98504-7600
Parcels:300 Desmond Drive, Lacey, WA 98503-1274

On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:


Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
 device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it like this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
 counts.b = sum(b==5, na.rm = T),
 counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at once?


--
Dimitri Liakhovitski

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Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

No problem at all, Clint.
I was just trying to figure out of dplyr can do it.

On Tue, Jun 16, 2015 at 1:40 PM, Clint Bowman  wrote:
> Any problem with
>
> colSums(md==5, na.rm=T)
>
> Clint BowmanINTERNET:   cl...@ecy.wa.gov
> Air Quality Modeler INTERNET:   cl...@math.utah.edu
> Department of Ecology   VOICE:  (360) 407-6815
> PO Box 47600FAX:(360) 407-7534
> Olympia, WA 98504-7600
>
> USPS:   PO Box 47600, Olympia, WA 98504-7600
> Parcels:300 Desmond Drive, Lacey, WA 98503-1274
>
>
> On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:
>
>> Hello!
>>
>> I have a data frame:
>>
>> md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
>> c(1,3,4,3,5,5),
>>  device = c(1,1,2,2,3,3))
>> myvars = c("a", "b", "c")
>> md[2,3] <- NA
>> md[4,1] <- NA
>> md
>>
>> I want to count number of 5s in each column - by device. I can do it like
>> this:
>>
>> library(dplyr)
>> group_by(md, device) %>%
>> summarise(counts.a = sum(a==5, na.rm = T),
>>  counts.b = sum(b==5, na.rm = T),
>>  counts.c = sum(c==5, na.rm = T))
>>
>> However, in real life I'll have tons of variables (the length of
>> 'myvars' can be very large) - so that I can't specify those counts.a,
>> counts.b, etc. manually - dozens of times.
>>
>> Does dplyr allow to run the count of 5s on all 'myvars' columns at once?
>>
>>
>> --
>> Dimitri Liakhovitski
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>



-- 
Dimitri Liakhovitski

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Re: [R] dplyr - counting a number of specific values in each column - for all columns at once

[Clint Bowman]

Any problem with

colSums(md==5, na.rm=T)

Clint BowmanINTERNET:   cl...@ecy.wa.gov
Air Quality Modeler INTERNET:   cl...@math.utah.edu
Department of Ecology   VOICE:  (360) 407-6815
PO Box 47600FAX:(360) 407-7534
Olympia, WA 98504-7600

USPS:   PO Box 47600, Olympia, WA 98504-7600
Parcels:300 Desmond Drive, Lacey, WA 98503-1274

On Tue, 16 Jun 2015, Dimitri Liakhovitski wrote:


Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
 device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it like this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
 counts.b = sum(b==5, na.rm = T),
 counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at once?


--
Dimitri Liakhovitski

__
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and provide commented, minimal, self-contained, reproducible code.



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and provide commented, minimal, self-contained, reproducible code.

[R] dplyr - counting a number of specific values in each column - for all columns at once

[Dimitri Liakhovitski]

Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c = c(1,3,4,3,5,5),
  device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it like this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
  counts.b = sum(b==5, na.rm = T),
  counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at once?


-- 
Dimitri Liakhovitski

__
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and provide commented, minimal, self-contained, reproducible code.

Re: [R] Question about XML package (accurately access one attribute in an multi-attribution node on the web page)

[Boris Steipe]

Humphrey -

Any "correct" method requires you to specify _uniquely_ what you are looking 
for. If the bookmark keyword is necessary and unique, it appears you have a 
working solution. Or what else where you trying to accomplish?

Cheers,
Boris


On Jun 16, 2015, at 9:01 AM, Humphrey Zhao  wrote:

> Dear Sir/Madam:
> 
> Thank you for your attention to my question. I have downloaded the source 
> code of some web pages by RCurl, and I am trying to extract the URL from 
> them. In these web pages, there are many nodes contains the same URL, such 
> like the followings:
> 
> http://cos.name/2015/05/the-data-wisdom-for-data-science/\"; 
> rel=\"bookmark\">
> 
>  href=\"http://blog.shakirm.com/2015/03/a-statistical-view-of-deep-learning-ii-auto-encoders-and-free-energy/\";
>  target=\"_blank\">
> 
>  href=\"http://cos.name/2015/05/the-data-wisdom-for-data-science/#more-10947\"; 
> class=\"more-link\">
> 
> I want to accurately choose the URL I need(the "href" in the first one), and 
> I tried many ways the most accuracy is just like the following:
> 
> library(XML)
> 
> #links<-getHTMLLinks(base.html, xpQuery = "//a/@href")
> 
> links<-getHTMLLinks(base.html, xpQuery = c("//a/href[@rel='bookmark']"))
> 
> However, I still believe that there is a correct method to do this very well, 
> but I could not find it. I wonder if you could give me some advice on solving 
> this problem. And I would be most grateful if you could reply at your 
> earliest convenience. Looking forward to hearing from you. Thank you very 
> much.
> 
>  Sincerely yours 
> 
>  Humphrey Zhao
>   [[alternative HTML version deleted]]
> 
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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and provide commented, minimal, self-contained, reproducible code.

Re: [R] Error in local package install

[Duncan Murdoch]

On 16/06/2015 1:27 PM, Uwe Ligges wrote:
> 
> 
> On 16.06.2015 16:33, Axel Urbiz wrote:
>> Thanks again Uwe. I haven't renamed the file, only in the text sent to
>> R-help. Here's the error again I'm getting. Sorry, this s a bit
>> frustrating...
> 
> No idea. Perhaps the down load failed? Can you open the file using some 
> zip software and extract the DESCRIPTION file?

It may also be a permissions problem:  perhaps the file couldn't be
unzipped, because the user doesn't have write permission.  Are you
installing to the default library?  Perhaps you should try installing to
a personal library instead.

Duncan Murdoch
> 
> Best,
> Uwe Ligges
> 
> 
>>
>> Thanks,
>> Axel
>>
>>
>> Error in read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package",
>> "Type")) :
>>cannot open the connection
>> In addition: Warning messages:
>> 1: In unzip(zipname, exdir = dest) : error 1 in extracting from zip file
>> 2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type")) :
>>cannot open compressed file 'calibr/DESCRIPTION', probable reason 'No
>> such file or directory'
>>  >
>>
>> On Tue, Jun 16, 2015 at 10:18 AM, Uwe Ligges
>> > > wrote:
>>
>>
>>
>> On 16.06.2015 15:16, Axel Urbiz wrote:
>>
>> Thanks Uwe. Actually, the problem persists in R-3.2.1.
>>
>> If it helps, the .zip file is here:
>>
>> http://win-builder.r-project.org/yC8eUu09w3Ui/
>>
>>
>>
>> Works for me, but your error message is:
>>
>>
>> "cannot open compressed file 'mypackage/DESCRIPTION'"
>>
>> which suggests you renamed the file?  You must not do that, just
>> keep the filename "calibr_0.0.0.9000.zip".
>>
>> Best,
>> Uwe Ligges
>>
>>
>> Thank you,
>> Axel.
>>
>>
>>
>> On Mon, Jun 15, 2015 at 5:41 PM, Uwe Ligges
>> > 
>> > >> wrote:
>>
>>
>>
>>  On 15.06.2015 22:32, Axel Urbiz wrote:
>>
>>  Hello,
>>
>>  I've built a windows binary package from my Mac using
>> the help
>>  from this
>>  site: http://win-builder.r-project.org
>>
>>  As expected, I got back the file "mypackage.zip". Also,
>> the logs
>>  show no
>>  errors.
>>
>>
>>  No, you got a file packagename_version.zip.
>>
>>
>>
>>  Now, when I try to install on windows using the GUI
>> "install
>>  package(s)
>>  from local zip files", I get the following error:
>>
>>  utils:::menuInstallLocal()
>>
>>  Error in read.dcf(file.path(pkgname, "DESCRIPTION"),
>>  c("Package", "Type"))
>>  :
>>  cannot open the connection
>>  In addition: Warning messages:
>>  1: In unzip(zipname, exdir = dest) : error 1 in
>> extracting from
>>  zip file
>>  2: In read.dcf(file.path(pkgname, "DESCRIPTION"),
>> c("Package",
>>  "Type")) :
>>  cannot open compressed file 'mypackage/DESCRIPTION',
>>  probable reason 'No
>>  such file or directory'
>>
>>  I've attempted to use the solutions from prior similar
>> email
>>  threats with
>>  no success. Btw - I've install all the packages
>> dependencies
>>  prior to the
>>  above. I'm on R 3.2.0.
>>
>>
>>  please try the release condadate of R-3.2.1, R-3.2.0 had a
>> bug for
>>  package installation from local zip files.
>>
>>  Best,
>>  Uwe Ligges
>>
>>
>>  Any guidance would be much appreciated.
>>
>>  Thank you.
>>
>>  Axel.
>>
>>   [[alternative HTML version deleted]]
>>
>>  __
>> R-help@r-project.org 
>> >
>> mailing list
>>  -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>>  PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>>  and provide commented, minimal, self-contained,
>> reproducible code.
>>
>>
>>
> 
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

__

Re: [R] Error in local package install

[Uwe Ligges]

On 16.06.2015 16:33, Axel Urbiz wrote:

Thanks again Uwe. I haven't renamed the file, only in the text sent to
R-help. Here's the error again I'm getting. Sorry, this s a bit
frustrating...


No idea. Perhaps the down load failed? Can you open the file using some 
zip software and extract the DESCRIPTION file?


Best,
Uwe Ligges




Thanks,
Axel


Error in read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package",
"Type")) :
   cannot open the connection
In addition: Warning messages:
1: In unzip(zipname, exdir = dest) : error 1 in extracting from zip file
2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type")) :
   cannot open compressed file 'calibr/DESCRIPTION', probable reason 'No
such file or directory'
 >

On Tue, Jun 16, 2015 at 10:18 AM, Uwe Ligges
mailto:lig...@statistik.tu-dortmund.de>> wrote:



On 16.06.2015 15:16, Axel Urbiz wrote:

Thanks Uwe. Actually, the problem persists in R-3.2.1.

If it helps, the .zip file is here:

http://win-builder.r-project.org/yC8eUu09w3Ui/



Works for me, but your error message is:


"cannot open compressed file 'mypackage/DESCRIPTION'"

which suggests you renamed the file?  You must not do that, just
keep the filename "calibr_0.0.0.9000.zip".

Best,
Uwe Ligges


Thank you,
Axel.



On Mon, Jun 15, 2015 at 5:41 PM, Uwe Ligges
mailto:lig...@statistik.tu-dortmund.de>
>> wrote:



 On 15.06.2015 22:32, Axel Urbiz wrote:

 Hello,

 I've built a windows binary package from my Mac using
the help
 from this
 site: http://win-builder.r-project.org

 As expected, I got back the file "mypackage.zip". Also,
the logs
 show no
 errors.


 No, you got a file packagename_version.zip.



 Now, when I try to install on windows using the GUI
"install
 package(s)
 from local zip files", I get the following error:

 utils:::menuInstallLocal()

 Error in read.dcf(file.path(pkgname, "DESCRIPTION"),
 c("Package", "Type"))
 :
 cannot open the connection
 In addition: Warning messages:
 1: In unzip(zipname, exdir = dest) : error 1 in
extracting from
 zip file
 2: In read.dcf(file.path(pkgname, "DESCRIPTION"),
c("Package",
 "Type")) :
 cannot open compressed file 'mypackage/DESCRIPTION',
 probable reason 'No
 such file or directory'

 I've attempted to use the solutions from prior similar
email
 threats with
 no success. Btw - I've install all the packages
dependencies
 prior to the
 above. I'm on R 3.2.0.


 please try the release condadate of R-3.2.1, R-3.2.0 had a
bug for
 package installation from local zip files.

 Best,
 Uwe Ligges


 Any guidance would be much appreciated.

 Thank you.

 Axel.

  [[alternative HTML version deleted]]

 __
R-help@r-project.org 
>
mailing list
 -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
 PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
 and provide commented, minimal, self-contained,
reproducible code.





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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] problem with nlme, environments, and packages

[Duncan Murdoch]

On 16/06/2015 10:34 AM, Greg Hather wrote:
> Hi Duncan,
> 
> I checked the global environment, and it was empty, so I think that
> rules out the second possibility.  I posted a tarball at
> 
> https://drive.google.com/file/d/0B8hBX90jtuLcaGtOUktqV2V4UUU/view?usp=sharing
> 
> Thank you for your help!
> 
> Greg
> 

The problem is that nlme does a lot of evaluation of formula objects
without taking their associated environment into account.  Fixing it
doesn't look easy, because the evaluation happens in a lot of places.

One workaround is to put the appropriate environment(s) on the search
list before calling nlme().  This isn't perfect, because the search
order will be wrong, but it will get you something.

For example, your main_function could be

main_function <- function(x){

  library(nlme)
  attach(parent.env(env=environment()))
  result <- nlme(height ~ SSasymp(age, Asym, R0, lrc) +
nonlinear_function(age),
 data = Loblolly,
 fixed = Asym + R0 + lrc ~ 1,
 random = Asym ~ 1,
 start = c(Asym = 103, R0 = -8.5, lrc = -3.3))
  detach()
  result
}

Duncan

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[R] reading daily snow depth data

[Alemu Tadesse]

Dear All,

I was going to read daily snow data  for each state and station/city from
the following link. I was not able to separate a given state's data from
the rest of the contents of the file, read the data to a data frame and
save it to file.

http://www1.ncdc.noaa.gov/pub/data/snowmonitoring/fema/06-2015-dlysndpth.txt

I really appreciate your time and help, and also appreciate any information
 for an alternative source.

Best,

Alemu

[[alternative HTML version deleted]]

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Re: [R] Boxplot using a shapefile

[Preethi Balaji]

Dear all,

Thanks very much for your help! I will keep your suggestions in mind
and will get back to you if I get stuck!



On Tue, Jun 16, 2015 at 1:28 PM, Roger Bivand  wrote:
> Boris Steipe  utoronto.ca> writes:
>
>>
>> Your workflow in principle is:
>>
>> - read the image into an object for which you can obtain values-per-pixel
> in a 2D structure;
>> - read the shapefile and convert into a polygon;
>> - determine the bounding box of the polygon;
>> - use the inout() function of the splancs package to get a list of
> booleans for the
>> points in the bounding box, TRUE if they are _inside_ the polygon;
>> - subset your image points to those for which inout() returns TRUE;
>> - plot as boxplot().
>>
>> The CRAN taskview http://cran.r-project.org/web/views/MedicalImaging.html
> has a section on general
>> image processing, guiding you to helpful packages.
>
> Actually, this is the wrong taskview if the data are as described, as
> Spatial data are covered in the Spatial task view at:
>
> http://cran.r-project.org/web/views/Spatial.html
>
> The workflow as described is also muddled: "[T]he shapefile takes the
> pixel values from the image and shows the distribution of pixels in
> the form of a boxplot" doesn't actually mean anything without further
> assumptions.
>
> A shapefile is an ESRI file format for GIS vector geometries (and
> attributes) that may be polygons, lines or points, and has an associated
> coordinate reference system; it is almost never used for other kinds of data.
>
> The "image" - presumably a GIS raster data file, should have the same
> coordinate reference system, or be transformed to the same system (use
> spTransform in the rgdal package, which is also the package you should use
> for reading the input data as it correctly reads input coordinate reference
> systems if available).
>
> The operation then needed is called an over() method in the sp package, and
> extract() in the raster package.
>
> If the shapefile contains points, the over query is asking the value(s) of
> the raster cells (pixels) at those points, given the same coordinate
> reference systems - but only one boxplot. If lines, for each line you may
> get a vector of values from raster cells intersected by the lines, and could
> make a boxplot for each line; you may wish to weight each value by the
> length of line in each cell. If polygons, as lines, with weighting by
> intersection area.
>
> The over vignette in the sp package is where you need to go to begin:
>
> http://cran.r-project.org/web/packages/sp/vignettes/over.pdf
>
> and the introduction to the raster package as a further reference:
>
> http://cran.r-project.org/web/packages/raster/vignettes/Raster.pdf
>
>>
>> Ask again if you get stuck - but(!):
>> - see here for some hints on how to ask questions productively:
>>   http://adv-r.had.co.nz/Reproducibility.html
>>
> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
>> - ... and please read the posting guide and don't post in HTML.
>>
>
> Definitely! And note that this is a question that is better suited to the
> R-sig-geo list.
>
> Hope this clarifies,
>
> Roger
>
>> B.
>>
>> On Jun 15, 2015, at 7:19 AM, Preethi Balaji 
> gmail.com> wrote:
>>
>> > Dear all,
>> >
>> > I am trying to generate boxplots by giving a shapefile and an image as
>> > input. The shapefile takes the pixel values from the image and shows
>> > the distribution of pixels in the form of a boxplot.
>> >
>> > Can somebody please tell me how I can execute this in R?
>> >
>> > Many thanks!
>> >
>> > --
>> >
>> > Regards,
>> > Preethi Malur Balaji | PhD Student
>> > University College Cork | Cork, Ireland.
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



-- 

Regards,
Preethi Malur Balaji | PhD Student
University College Cork | Cork, Ireland.

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[R] Question about XML package (accurately access one attribute in an multi-attribution node on the web page)

[Humphrey Zhao]

Dear Sir/Madam:

Thank you for your attention to my question. I have downloaded the source code 
of some web pages by RCurl, and I am trying to extract the URL from them. In 
these web pages, there are many nodes contains the same URL, such like the 
followings:

http://cos.name/2015/05/the-data-wisdom-for-data-science/\" 
rel=\"bookmark\">

http://blog.shakirm.com/2015/03/a-statistical-view-of-deep-learning-ii-auto-encoders-and-free-energy/\";
 target=\"_blank\">

http://cos.name/2015/05/the-data-wisdom-for-data-science/#more-10947\" 
class=\"more-link\">

I want to accurately choose the URL I need(the "href" in the first one), and I 
tried many ways the most accuracy is just like the following:

library(XML)

#links<-getHTMLLinks(base.html, xpQuery = "//a/@href")

links<-getHTMLLinks(base.html, xpQuery = c("//a/href[@rel='bookmark']"))

However, I still believe that there is a correct method to do this very well, 
but I could not find it. I wonder if you could give me some advice on solving 
this problem. And I would be most grateful if you could reply at your earliest 
convenience. Looking forward to hearing from you. Thank you very much.

 Sincerely yours 

 Humphrey Zhao
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[R] Error working dsm: Error in fix.by(by.x, x) : 'by' must specify a uniquely valid column

[Milagros Antun]

Hello, I`m trying to use dsm package, *(library(Distance); library(dsm)*) ,
following Miller`s Appendix (
http://onlinelibrary.wiley.com/store/10./2041-210X.12105/asset/supinfo/mee312105-sup-0001-AppendixS1.pdf?v=1&s=ced953b57365e5eb5753f0ad76dcc02c26918736
 ).

I work with three dataframes, whose str are:

*1) segdata:*
 data.frame': 193 obs. of  17 variables:
 $ Sample.Lab: int  1 2 3 4 5 6 7 8 9 10 ...
 $ Transect.Label: Factor w/ 56 levels "1","100","101",..: 36 36 36 36 36
20 56 52 52 52 ...
 $ Effort: int  1800 1800 1800 1800 1800 1800 1800 1800 1800 1800
...
 $ x : num  4443636 4437817 4442085 4440564 4439117 ...
 $ y : num  5267395 5271579 5268309 5269266 5270337 ...
 $ ID_ESTRATO: int  3 2 3 2 2 2 2 2 4 2 ...
 $ NDVI2010  : num  1813 1816 1804 1807 1816 ...
 $ NDVI2011  : num  2007 1943 1935 1894 1893 ...
 $ NDVI2012  : num  1705 1736 1686 1691 1729 ...
 $ NDVI2013  : num  2206 2305 2145 2211 2279 ...
 $ PROM_NDVI : num  2218 2313 2148 2206 2275 ...
 $ DIST_PUEST: num  959 455 2652 3194 1394 ...
 $ DIST_CUADR: num  1482.1 137.5 549.9 62.9 514.8 ...
 $ DIST_MOLIN: num  794 5022 2519 4156 5715 ...
 $ X_4326: num  -63.7 -63.8 -63.7 -63.7 -63.7 ...
 $ Y_4326: num  -42.7 -42.7 -42.7 -42.7 -42.7 ...
 $ O.KM2_2015: num  64.1 34.6 43.4 44.4 46.6 ...

*2) obsdata:*
'data.frame': 399 obs. of  6 variables:
 $ Especie.: Factor w/ 1 level "Oveja": 1 1 1 1 1 1 1 1 1 1 ...
 $ size: int  3 1 5 18 6 2 6 3 5 2 ...
 $ distance: int  210 178 65 210 250 37 72 350 380 320 ...
 $ object  : int  1 2 5 7 8 13 14 20 30 31 ...
 $ Sample.Label: int  26 26 30 30 30 29 28 27 31 31 ...
 $ Effort  : num  1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 ...

*3)disdata*
'data.frame': 399 obs. of  7 variables:
 $ x   : num  4418278 4418667 4421229 4421308 4421308 ...
 $ y   : num  5299140 5298846 5295963 5295805 5295805 ...
 $ Especie.: Factor w/ 1 level "Oveja": 1 1 1 1 1 1 1 1 1 1 ...
 $ size: int  3 1 5 18 6 2 6 3 5 2 ...
 $ distance: int  210 178 65 210 250 37 72 350 380 320 ...
 $ object  : int  1 2 5 7 8 13 14 20 30 31 ...
 $ Effort  : num  1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 ...


*First, I **fitted a detection function with the **script: *

*hr.model <-ds(distdata,truncation="10%",transect ="line",dht.group=
FALSE,key ="hr", convert.units = 1,adjustment =NULL) *

*And then, I tried to fit a  **very simple model, with the script:*


*mod1<-dsm(count ~ s(x,y, k=6), ddf.obj=hr.model, segdata, obsdata, engine
= "gam",convert.units = 1, family = quasipoisson(link = "log"),group =
FALSE,gamma = 1.4,control = list(keepData = TRUE),availability =
1,segment.area = NULL, weights = NULL)*

*Here I made a mistake, because R show me an Error: *


*Error in fix.by (by.x, x) : 'by' must specify a uniquely
valid column*

*Does anybody can help me? Thanks in advance!*


*Milagros*
-- 
Lic. Ma. de los Milagros Antún
Centro Nacional Patagónico-CONICET
Boulevard Brown 2915
9120 Puerto Madryn
Argentina
Tel. +54 (0) 280 4883184
Interno 1345
Fax +54 (0) 280 4883543

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Re: [R] problem with nlme, environments, and packages

[Bert Gunter]

An aside...

Just wanted to point out that:

fun <- function(x)log(x)

can be more simply replaced by:

fun <- log

Functions in R a full first class objects and can be treated as such. In
your example, this is still silly of course, but becomes relevant in
function calls where you can do things like

myfun <- function( FUN = log,...)

{ ...
something <- FUN(X)
...
}

Just in case this might be useful to you.

Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Mon, Jun 15, 2015 at 4:32 PM, Greg Hather  wrote:

> Hello R users,
>
> I encountered a strange problem while writing a package that uses the
> nlme function.  First, I wrote some code that uses the nlme function,
> and it ran without errors.  However, when I tried to put the code into
> a package, the nlme function was unable to locate a function that was
> used in the formula.  Could it be that nlme is looking in the wrong
> environment?  I would appreciate any suggestions.  Below is a
> reproducible example with the problem.
>
> ### BEGIN EXAMPLE ##
>
> #' Fake package to show nlme error
> #' @export
>
> main_function <- function(x){
>  library(nlme)
>  result <- nlme(height ~ SSasymp(age, Asym, R0, lrc) +
> nonlinear_function(age),
> data = Loblolly,
> fixed = Asym + R0 + lrc ~ 1,
> random = Asym ~ 1,
> start = c(Asym = 103, R0 = -8.5, lrc = -3.3))
>  result
> }
>
> nonlinear_function <- function(x){
>  log(x)
> }
>
> ### END EXAMPLE ##
>
> The above code can be installed as a package and run with the commands
>
> library(devtools)
> library(roxygen2)
> setwd("C:/test")  # or any prefered directory
> create("testPackage")
> setwd("./testPackage")
> document()
> setwd("..")
> install("testPackage")
> main_function()
>
> The output is
>
> > main_function()
> Error in eval(expr, envir, enclos) :
>  could not find function "nonlinear_function"
> >
> > sessionInfo()
> R version 3.1.3 (2015-03-09)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> Running under: Windows 8 x64 (build 9200)
> locale:
> [1] LC_COLLATE=English_United States.1252
> [2] LC_CTYPE=English_United States.1252
> [3] LC_MONETARY=English_United States.1252
> [4] LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
> attached base packages:
> [1] stats graphics  grDevices utils datasets  methods
> [7] base
> other attached packages:
> [1] nlme_3.1-120   testPackage_0.0.0.9000
> [3] roxygen2_4.1.1 devtools_1.8.0
> loaded via a namespace (and not attached):
> [1] curl_0.8digest_0.6.8git2r_0.10.1
> [4] grid_3.1.3  lattice_0.20-31 magrittr_1.5
> [7] memoise_0.2.1   Rcpp_0.11.6 rversions_1.0.1
> [10] stringi_0.4-1   stringr_1.0.0   tools_3.1.3
> [13] xml2_0.1.1
>
> Note that if I simply paste main_function and nonlinear_function into
> the R console, then main_function() runs without errors.
>
> Greg
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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Re: [R] model selection

[Bert Gunter]

Wrong list! This is about R. Post on a statistics list like
stats.stackexchange.com for statistics questions.

Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Mon, Jun 15, 2015 at 3:55 PM, bruno cid  wrote:

> Hi friends,
>
> Im trying to make a model selection comparing models built with "lm"
> function (package "stats") and "lme" function (package "nlme"). Do you know
> if there is a problem to compare these models with the function "AICtab"
> (package "bbmle).
>
> Thanks!!! Bruno Cid Crespo GuimarãesMestre em EcologiaLaboratório de
> Ecologia e Conservação de PopulaçõesUniversidade Federal do Rio de Janeiro
> [[alternative HTML version deleted]]
>
> __
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> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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Re: [R] Error in local package install

[Axel Urbiz]

Thanks again Uwe. I haven't renamed the file, only in the text sent to
R-help. Here's the error again I'm getting. Sorry, this s a bit
frustrating...

Thanks,
Axel


Error in read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type"))
:
  cannot open the connection
In addition: Warning messages:
1: In unzip(zipname, exdir = dest) : error 1 in extracting from zip file
2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type")) :
  cannot open compressed file 'calibr/DESCRIPTION', probable reason 'No
such file or directory'
>

On Tue, Jun 16, 2015 at 10:18 AM, Uwe Ligges <
lig...@statistik.tu-dortmund.de> wrote:

>
>
> On 16.06.2015 15:16, Axel Urbiz wrote:
>
>> Thanks Uwe. Actually, the problem persists in R-3.2.1.
>>
>> If it helps, the .zip file is here:
>>
>> http://win-builder.r-project.org/yC8eUu09w3Ui/
>>
>
>
> Works for me, but your error message is:
>
>
> "cannot open compressed file 'mypackage/DESCRIPTION'"
>
> which suggests you renamed the file?  You must not do that, just keep the
> filename "calibr_0.0.0.9000.zip".
>
> Best,
> Uwe Ligges
>
>
>  Thank you,
>> Axel.
>>
>>
>>
>> On Mon, Jun 15, 2015 at 5:41 PM, Uwe Ligges
>> > > wrote:
>>
>>
>>
>> On 15.06.2015 22:32, Axel Urbiz wrote:
>>
>> Hello,
>>
>> I've built a windows binary package from my Mac using the help
>> from this
>> site: http://win-builder.r-project.org
>>
>> As expected, I got back the file "mypackage.zip". Also, the logs
>> show no
>> errors.
>>
>>
>> No, you got a file packagename_version.zip.
>>
>>
>>
>> Now, when I try to install on windows using the GUI "install
>> package(s)
>> from local zip files", I get the following error:
>>
>> utils:::menuInstallLocal()
>>
>> Error in read.dcf(file.path(pkgname, "DESCRIPTION"),
>> c("Package", "Type"))
>> :
>> cannot open the connection
>> In addition: Warning messages:
>> 1: In unzip(zipname, exdir = dest) : error 1 in extracting from
>> zip file
>> 2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package",
>> "Type")) :
>> cannot open compressed file 'mypackage/DESCRIPTION',
>> probable reason 'No
>> such file or directory'
>>
>> I've attempted to use the solutions from prior similar email
>> threats with
>> no success. Btw - I've install all the packages dependencies
>> prior to the
>> above. I'm on R 3.2.0.
>>
>>
>> please try the release condadate of R-3.2.1, R-3.2.0 had a bug for
>> package installation from local zip files.
>>
>> Best,
>> Uwe Ligges
>>
>>
>> Any guidance would be much appreciated.
>>
>> Thank you.
>>
>> Axel.
>>
>>  [[alternative HTML version deleted]]
>>
>> __
>> R-help@r-project.org  mailing list
>> -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>>

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Re: [R] Error in local package install

[Uwe Ligges]

On 16.06.2015 15:16, Axel Urbiz wrote:

Thanks Uwe. Actually, the problem persists in R-3.2.1.

If it helps, the .zip file is here:

http://win-builder.r-project.org/yC8eUu09w3Ui/



Works for me, but your error message is:


"cannot open compressed file 'mypackage/DESCRIPTION'"

which suggests you renamed the file?  You must not do that, just keep 
the filename "calibr_0.0.0.9000.zip".


Best,
Uwe Ligges



Thank you,
Axel.



On Mon, Jun 15, 2015 at 5:41 PM, Uwe Ligges
mailto:lig...@statistik.tu-dortmund.de>> wrote:



On 15.06.2015 22:32, Axel Urbiz wrote:

Hello,

I've built a windows binary package from my Mac using the help
from this
site: http://win-builder.r-project.org

As expected, I got back the file "mypackage.zip". Also, the logs
show no
errors.


No, you got a file packagename_version.zip.



Now, when I try to install on windows using the GUI "install
package(s)
from local zip files", I get the following error:

utils:::menuInstallLocal()

Error in read.dcf(file.path(pkgname, "DESCRIPTION"),
c("Package", "Type"))
:
cannot open the connection
In addition: Warning messages:
1: In unzip(zipname, exdir = dest) : error 1 in extracting from
zip file
2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package",
"Type")) :
cannot open compressed file 'mypackage/DESCRIPTION',
probable reason 'No
such file or directory'

I've attempted to use the solutions from prior similar email
threats with
no success. Btw - I've install all the packages dependencies
prior to the
above. I'm on R 3.2.0.


please try the release condadate of R-3.2.1, R-3.2.0 had a bug for
package installation from local zip files.

Best,
Uwe Ligges


Any guidance would be much appreciated.

Thank you.

Axel.

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Re: [R] problem with nlme, environments, and packages

[Greg Hather]

Hi Duncan,

I checked the global environment, and it was empty, so I think that rules
out the second possibility.  I posted a tarball at

https://drive.google.com/file/d/0B8hBX90jtuLcaGtOUktqV2V4UUU/view?usp=sharing

Thank you for your help!

Greg

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Re: [R] Error in local package install

[Axel Urbiz]

Thanks Uwe. Actually, the problem persists in R-3.2.1.

If it helps, the .zip file is here:

http://win-builder.r-project.org/yC8eUu09w3Ui/

Thank you,
Axel.



On Mon, Jun 15, 2015 at 5:41 PM, Uwe Ligges  wrote:

>
>
> On 15.06.2015 22:32, Axel Urbiz wrote:
>
>> Hello,
>>
>> I've built a windows binary package from my Mac using the help from this
>> site: http://win-builder.r-project.org
>>
>> As expected, I got back the file "mypackage.zip". Also, the logs show no
>> errors.
>>
>
> No, you got a file packagename_version.zip.
>
>
>
>  Now, when I try to install on windows using the GUI "install package(s)
>> from local zip files", I get the following error:
>>
>>  utils:::menuInstallLocal()
>>>
>> Error in read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type"))
>> :
>>cannot open the connection
>> In addition: Warning messages:
>> 1: In unzip(zipname, exdir = dest) : error 1 in extracting from zip file
>> 2: In read.dcf(file.path(pkgname, "DESCRIPTION"), c("Package", "Type")) :
>>cannot open compressed file 'mypackage/DESCRIPTION', probable reason
>> 'No
>> such file or directory'
>>
>> I've attempted to use the solutions from prior similar email threats with
>> no success. Btw - I've install all the packages dependencies prior to the
>> above. I'm on R 3.2.0.
>>
>
> please try the release condadate of R-3.2.1, R-3.2.0 had a bug for package
> installation from local zip files.
>
> Best,
> Uwe Ligges
>
>
>  Any guidance would be much appreciated.
>>
>> Thank you.
>>
>> Axel.
>>
>> [[alternative HTML version deleted]]
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>

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Re: [R] Boxplot using a shapefile

[Roger Bivand]

Boris Steipe  utoronto.ca> writes:

> 
> Your workflow in principle is:
> 
> - read the image into an object for which you can obtain values-per-pixel
in a 2D structure;
> - read the shapefile and convert into a polygon;
> - determine the bounding box of the polygon;
> - use the inout() function of the splancs package to get a list of
booleans for the
> points in the bounding box, TRUE if they are _inside_ the polygon;
> - subset your image points to those for which inout() returns TRUE;
> - plot as boxplot().
> 
> The CRAN taskview http://cran.r-project.org/web/views/MedicalImaging.html
has a section on general
> image processing, guiding you to helpful packages.

Actually, this is the wrong taskview if the data are as described, as
Spatial data are covered in the Spatial task view at:

http://cran.r-project.org/web/views/Spatial.html

The workflow as described is also muddled: "[T]he shapefile takes the 
pixel values from the image and shows the distribution of pixels in 
the form of a boxplot" doesn't actually mean anything without further
assumptions. 

A shapefile is an ESRI file format for GIS vector geometries (and
attributes) that may be polygons, lines or points, and has an associated
coordinate reference system; it is almost never used for other kinds of data. 

The "image" - presumably a GIS raster data file, should have the same
coordinate reference system, or be transformed to the same system (use
spTransform in the rgdal package, which is also the package you should use
for reading the input data as it correctly reads input coordinate reference
systems if available). 

The operation then needed is called an over() method in the sp package, and
extract() in the raster package. 

If the shapefile contains points, the over query is asking the value(s) of
the raster cells (pixels) at those points, given the same coordinate
reference systems - but only one boxplot. If lines, for each line you may
get a vector of values from raster cells intersected by the lines, and could
make a boxplot for each line; you may wish to weight each value by the
length of line in each cell. If polygons, as lines, with weighting by
intersection area.

The over vignette in the sp package is where you need to go to begin:

http://cran.r-project.org/web/packages/sp/vignettes/over.pdf

and the introduction to the raster package as a further reference:

http://cran.r-project.org/web/packages/raster/vignettes/Raster.pdf

> 
> Ask again if you get stuck - but(!):
> - see here for some hints on how to ask questions productively:
>   http://adv-r.had.co.nz/Reproducibility.html
>  
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
> - ... and please read the posting guide and don't post in HTML.
> 

Definitely! And note that this is a question that is better suited to the
R-sig-geo list.

Hope this clarifies,

Roger

> B.
> 
> On Jun 15, 2015, at 7:19 AM, Preethi Balaji 
gmail.com> wrote:
> 
> > Dear all,
> > 
> > I am trying to generate boxplots by giving a shapefile and an image as
> > input. The shapefile takes the pixel values from the image and shows
> > the distribution of pixels in the form of a boxplot.
> > 
> > Can somebody please tell me how I can execute this in R?
> > 
> > Many thanks!
> > 
> > -- 
> > 
> > Regards,
> > Preethi Malur Balaji | PhD Student
> > University College Cork | Cork, Ireland.

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Re: [R] problem with nlme, environments, and packages

[Duncan Murdoch]

On 15/06/2015 8:32 PM, Greg Hather wrote:
> Hello R users,
> 
> I encountered a strange problem while writing a package that uses the
> nlme function.  First, I wrote some code that uses the nlme function,
> and it ran without errors.  However, when I tried to put the code into
> a package, the nlme function was unable to locate a function that was
> used in the formula.  Could it be that nlme is looking in the wrong
> environment?  I would appreciate any suggestions.  Below is a
> reproducible example with the problem.

I haven't tested this (I don't use the devtools stuff), but I'd say
there are two likely possibilities:

1.  nlme() isn't evaluating the formula properly.

2.  Your test isn't doing what you think it is doing, because you have a
second copy of main_function in your global environment.

Assuming you can rule out 2, could you put together a tarball of the
package that I could actually run?

Duncan Murdoch


> 
> ### BEGIN EXAMPLE ##
> 
> #' Fake package to show nlme error
> #' @export
> 
> main_function <- function(x){
>  library(nlme)
>  result <- nlme(height ~ SSasymp(age, Asym, R0, lrc) +
> nonlinear_function(age),
> data = Loblolly,
> fixed = Asym + R0 + lrc ~ 1,
> random = Asym ~ 1,
> start = c(Asym = 103, R0 = -8.5, lrc = -3.3))
>  result
> }
> 
> nonlinear_function <- function(x){
>  log(x)
> }
> 
> ### END EXAMPLE ##
> 
> The above code can be installed as a package and run with the commands
> 
> library(devtools)
> library(roxygen2)
> setwd("C:/test")  # or any prefered directory
> create("testPackage")
> setwd("./testPackage")
> document()
> setwd("..")
> install("testPackage")
> main_function()
> 
> The output is
> 
>> main_function()
> Error in eval(expr, envir, enclos) :
>  could not find function "nonlinear_function"
>>
>> sessionInfo()
> R version 3.1.3 (2015-03-09)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> Running under: Windows 8 x64 (build 9200)
> locale:
> [1] LC_COLLATE=English_United States.1252
> [2] LC_CTYPE=English_United States.1252
> [3] LC_MONETARY=English_United States.1252
> [4] LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
> attached base packages:
> [1] stats graphics  grDevices utils datasets  methods
> [7] base
> other attached packages:
> [1] nlme_3.1-120   testPackage_0.0.0.9000
> [3] roxygen2_4.1.1 devtools_1.8.0
> loaded via a namespace (and not attached):
> [1] curl_0.8digest_0.6.8git2r_0.10.1
> [4] grid_3.1.3  lattice_0.20-31 magrittr_1.5
> [7] memoise_0.2.1   Rcpp_0.11.6 rversions_1.0.1
> [10] stringi_0.4-1   stringr_1.0.0   tools_3.1.3
> [13] xml2_0.1.1
> 
> Note that if I simply paste main_function and nonlinear_function into
> the R console, then main_function() runs without errors.
> 
> Greg
> 
>   [[alternative HTML version deleted]]
> 
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] Missing Values in Table Statement

[PIKAL Petr]

Hi

actually output from dput is the most user friendly way of supplying data.

try just copy this part below

-

temp <- structure(list(dusik = c(1814L, 2844L, 3121L, 3286L, 3515L, 2478L,
1891L), kyslik = c(5224L, 8632L, 9214L, 9765L, 10428L, 7403L,
5469L), co2 = c(20188L, 32118L, 35299L, 36781L, 39340L, 28136L,
20980L), pevnost = c(6.3, 5.82, 6.89, 5.49, 8.4, 8.6, 10.6),
dlou = c(81.2, 102.6, 146.2, 87.2, 154.6, 177.1, 170.2),
adit = structure(c(4L, 2L, 2L, 3L, 3L, 1L, 1L), .Label = c("adi",
"cg100", "cg100mod", "nic"), class = "factor"), pridavek = c(0L,
3L, 5L, 3L, 5L, 3L, 5L)), .Names = c("dusik", "kyslik", "co2",
"pevnost", "dlou", "adit", "pridavek"), class = "data.frame", row.names = c(NA,
-7L))



and put it to your R console. It will create object named temp as you can 
easily check.

Cheers
Petr

> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Shivi82
> Sent: Tuesday, June 16, 2015 8:20 AM
> To: r-help@r-project.org
> Subject: Re: [R] Missing Values in Table Statement
>
> HI Petr,There is no reason for holding back the data from dput format.
> The reason for not supplying is that i tried multiple times but it the
> output what comes is not really user friendly is what i think.Not sure
> if i am missing a trick somewhere as i tried both the dput and dget
> options. Though as you highlighted below i will once again check the
> time column to see what values are empty.Thanks, Shivi
>
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Missing-
> Values-in-Table-Statement-tp4708534p4708674.html
> Sent from the R help mailing list archive at Nabble.com.
>   [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.


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