Hi Ilia,
You may want to have a try of the showtext package
(https://github.com/yixuan/showtext). Below is a quick example:
library(showtext)
showtext.auto()
pdf("test.pdf")
## Use the "sans" font family provided by the showtext package
## font == 3 means italic font face
plot(1, xlab = "Unicode
Thanks Marc. It never occurred to me that I would need a ""stringsAsFactors"
expression in a data.frame. I could have sworn I never did before when mocking
up some data but clearly I was wrong or there has been a change in R v. 3.4.1
which seems unlikely.
On Friday, July 7, 2017, 10:37:29 AM
> On Jul 7, 2017, at 7:03 PM, John Kane wrote:
>
> Thanks Marc.
> It never occurred to me that I would need a ""stringsAsFactors" expression in
> a data.frame. I could have sworn I never did before when mocking up some
> data but clearly I was wrong or there has been a change in R v. 3.4.1 wh
Google is your friend.
Also rseek.org
Bert
On Jul 7, 2017 3:48 PM, "Martina Hulešová" wrote:
> Dear all,
> I am trying to learn about R. As a Phd student, I would like to use R for
> Krippendorff s alpha and later for a series of CFA. Is there any good
> introduction to these kind of analyse
Interesting. I did not have the package installed, but I did at some
point extract Helvetica from some MacOSX font files and R was using that
just fine until 3.3. This is how the plot looks in 3.4 (still using
Helvetica): https://ptpb.pw/HikX.pdf . After removing Helvetica,
installing the ttf-m
Dear all,
I am trying to learn about R. As a Phd student, I would like to use R for
Krippendorff s alpha and later for a series of CFA. Is there any good
introduction to these kind of analyses, or could you recommend me some
tutorials on youtube, for example? I am new to R, so I need something b
On Fri, Jul 07, 2017 at 07:08:52PM +0200, Ilia Kats wrote:
> Interesting. I did not have the package installed, but I did at some point
> extract Helvetica from some MacOSX font files and R was using that just fine
> until 3.3. This is how the plot looks in 3.4 (still using Helvetica):
> https://pt
Hi Ilia,
I'm running Arch Linux, R 3.4.0.
Here's my test.pdf from your minimal example: https://ptpb.pw/HxsA.pdf
It doesn't look pixelated to me...
Here's a post that I wrote when I solved my last font problem in R,
almost 2 years ago:
https://stackoverflow.com/a/40940331/5087283
I had to ins
> On Jul 6, 2017, at 2:19 PM, Dai, Shengyu wrote:
>
> Hi R helpers,
>
>
>
> I hope this email finds you well.
>
>
>
> I am having trouble with R loop function in Tableau.
>
There is no "R loop function". (There is an R `for`-function.) If you are
having trouble with code then it should
> On Jul 7, 2017, at 2:29 AM, Dhivya Narayanasamy wrote:
>
> Hi,
>
> I am doing predictive modelling of Multivariate Time series Data of a Motor
> in R using various models such as Arima, H2O.Randomforest, glmnet, lm and
> few other models.
>
> I created a function to select a model of our cho
> On Jul 7, 2017, at 6:03 AM, John Kane via R-help wrote:
>
> This is not serious problem but I just wonder if someone can explain what is
> happening.
> The same command within a dataframe is giving me a factor and as a plain
> vector is giving me a character. It's probably something simple
This is not serious problem but I just wonder if someone can explain what is
happening.
The same command within a dataframe is giving me a factor and as a plain vector
is giving me a character. It's probably something simple that I have read and
forgotten but I thought I'd ask.
Thanks
#==
Hi R helpers,
I hope this email finds you well.
I am having trouble with R loop function in Tableau. Please see the attachment
of a simple dataset. The problem is to test whether the value of columns is
match.
Because Tableau do not have iteration function, I coded “if statement” in
Hi,
I am doing predictive modelling of Multivariate Time series Data of a Motor
in R using various models such as Arima, H2O.Randomforest, glmnet, lm and
few other models.
I created a function to select a model of our choice and do prediction.
Model1 <- function(){
..
return()
}
Model2 <- fu
how about gdata functions?
set.seed(1)
(tmp <- data.frame(x = 1:10, R1 = sample(LETTERS[1:5], 10, replace = TRUE), R2
= sample(LETTERS[2:6], 10, replace = TRUE)))
tmp.orig=tmp
library(gdata)
bigMap=mapLevels(x=list(factor(tmp[,"R1"]),factor(tmp[,"R2"])),combine =
T,codes=FALSE)
mapLevels(tmp[,"
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