A function MUST return one object.
That one object may consist of a list of objects, but you have to separate the
parts out after the function call yourself.
--
Sent from my phone. Please excuse my brevity.
On July 27, 2017 10:54:08 PM PDT, Vijaya Kumar Regati
wrote:
>Hi,
>
>
>Can someone pl
> On 28 Jul 2017, at 07:54, Vijaya Kumar Regati
> wrote:
>
> Hi,
>
>
> Can someone please help me on below issue I am facing :
>
>
> I am trying to play with returning a dataframe+2 variables using a fn.
> But facing an issue :
>
> Error in Logic_fn(c(x, y)) : argument "y" is missing, with
Hi,
Can someone please help me on below issue I am facing :
I am trying to play with returning a dataframe+2 variables using a fn.
But facing an issue :
Error in Logic_fn(c(x, y)) : argument "y" is missing, with no default
This is the code I am using :
x <- 0
y <- 0
Logic_fn <- function(x,
Hi
I believe this is a clipping bug in the 'graphics' package.
A simpler version of the problem is this ...
plot(1:10)
mtext("margin-label", side=2, at=9, las=1, line=1, adj=0)
par(mfg=c(1,1))
## Only the text within the plot region is drawn
mtext("margin-label", side=2, at=9, las=1, line=1, ad
It's ancient history, but the idiocy was to take a perfectly fine[*] standard
file format and make it use locale dependent number formats, instead of just
standardizing on the US format for data transfer purposes.
-pd
[*] OK, less than perfect, given quoting issues and various other stuff...
Hello,
Inline.
Em 27-07-2017 20:36, peter dalgaard escreveu:
On 27 Jul 2017, at 18:03 , Jeff Newmiller wrote:
Looks like you need to pay attention to how you read in your data. In general,
you should always execute one statement at a time until you know your script is
working. All the e
True, except that the head of their file had periods in the numbers.
--
Sent from my phone. Please excuse my brevity.
On July 27, 2017 12:36:13 PM PDT, peter dalgaard wrote:
>
>> On 27 Jul 2017, at 18:03 , Jeff Newmiller
>wrote:
>>
>> Looks like you need to pay attention to how you read in yo
> On 27 Jul 2017, at 18:03 , Jeff Newmiller wrote:
>
> Looks like you need to pay attention to how you read in your data. In
> general, you should always execute one statement at a time until you know
> your script is working. All the errors after the first one are unhelpful to
> you or us.
Important to notice: this seems to be an issue only with an unordered
factor on the X axis. When the variable is numeric or an ordered factor,
then it works as described in Help.
On Thu, Jul 27, 2017 at 11:58 AM, Dimitri Liakhovitski <
dimitri.liakhovit...@gmail.com> wrote:
> Тhanks for the advic
Looks like you need to pay attention to how you read in your data. In general,
you should always execute one statement at a time until you know your script is
working. All the errors after the first one are unhelpful to you or us.
If you actually pay attention to what is in your horse.data da
Тhanks for the advice, Jeff. Will keep it in mind.
But I am anal - I shy away from using letters and words that "look
familiar" to me in R (such as mean, sd, T, etc.)
But still, it's a good advice.
On Thu, Jul 27, 2017 at 11:53 AM, Jeff Newmiller
wrote:
> I think you should be more suspicious of
I think you should be more suspicious of yourself, Dimitri. A letter T variable
can easily arise in the problem domain when you are not thinking of logical
values at all, at which point your cavalier use of T as a synonym for TRUE can
suddenly become a bug.
--
Sent from my phone. Please excuse
Hi,
Please help about the error I am getting after the h1.dat<- line :
this line worked with much more independant variables and bigger data.
This time I want to work with just 2 variables cteD & cteTh.
What is wrong ?
> setwd("C:/Rstudio/Trot")
> library(mlogit)
> horse1.data<-read.csv("cte2.csv
Good point. cc'ing Hadley.
Well geom_bar help page clearly states:
na.rm: If FALSE, the default, missing values are removed with a warning. If
TRUE, missing values are silently removed.
But they are not being removed in my example - silently or loudly.
On Thu, Jul 27, 2017 at 11:18 AM, Jeff Newm
I suspect this is by design. Questions about "why" should probably cc the
contributed package maintainer(s).
--
Sent from my phone. Please excuse my brevity.
On July 27, 2017 7:49:47 AM PDT, Dimitri Liakhovitski
wrote:
>To clarify: my question is not about "who could I exclude NAs from
>being
Thank you, Bert!
I do NOT have an object named "T" in scope (I checked - and besides, it
would never occur to me to use this name).
TRUE or T results in the same unexpected behavior:
ggplot(data = md, mapping = aes(x = a)) +
geom_bar(na.rm = TRUE)
On Thu, Jul 27, 2017 at 10:57 AM, Bert Gunte
Just a thought:
Did you try na.rm = TRUE in case you have an object named "T" in scope?
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Thu, Jul 27,
To clarify: my question is not about "who could I exclude NAs from being
counted" - I know how to do that.
My question is: Why na.rm = T is not working for geom_bar in this case?
On Thu, Jul 27, 2017 at 8:24 AM, Dimitri Liakhovitski <
dimitri.liakhovit...@gmail.com> wrote:
> Hello!
>
> I am tryin
Hi John,
Not a problem, just wanted to be sure that there was not additional confounding
due to these issues.
You may be aware that a subsetting operation to remove records in a data frame
does not by default remove the unwanted levels from the factor that was
filtered:
iris.new <- subset(iri
Marc,
Sorry for the lack of info on my part. Yes, I did use 'family =
binomial' and I did drop the 3rd level before running the model. I think
the str() that I wrote into my original email might not have
been my final step before using glm. Thank you for reminding of the
potential problem.
Hi,
Late to the thread here, but I noted that your dependent variable 'know_fin'
has 3 levels in the str() output below.
Since you did not provide a full c&p of your glm() call, we can only presume
that you did specify 'family = binomial' in the call.
Is the dataset 'knowf3' the result of a s
Michael,
Thank you for the suggestion. I will take your advice and look more
critically at the covariates.
John
On 7/27/2017 8:08 AM, Michael Friendly wrote:
Rather than go to a penalized GLM, you might be better off
investigating the sources of quasi-perfect separation and simplifying
the
Rather than go to a penalized GLM, you might be better off investigating
the sources of quasi-perfect separation and simplifying the model to
avoid or reduce it. In your data set you have several factors with
large number of levels, making the data sparse for all their combinations.
Like mult
Hello!
I am trying to understand how ggplot2's geom_bar treats NAs.
The help file says:
library(ggplot2)
?geom_bar
na.rm: If FALSE, the default, missing values are removed with a warning. If
TRUE, missing values are silently removed.
I am trying it out:
md <- data.frame(a = c(letters[1:5], lette
`vetr` implements a declarative template-based approach to verify that objects
meet structural requirements, and auto-composes error messages when they do not.
This package is intended to simplify a more formal use of S3 objects.
The template concept is borrowed from `vapply`:
>> vet(numeric(1L),
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