Abou,
I believe I addressed this issue in a private message the other day.
As a general rule, truncating can leave a remainder. If
M = length(whatever)/3
Then M is no longer an integer. It can be a number ending in .333... or .666...
as well as 0.
Now R may silently truncate somethi
I have a more general problem for you.
Given n items and 2 <=g < wrote:
>
> Dear Thomas:
>
>
> Thank you very much for your input in this matter.
>
>
> The core part of this R code(s) (please see below) was written by *Richard
> O'Keefe*. I had three examples with different sample sizes.
>
>
>
> *
Hello,
And another way, with geom_jitter
p + geom_jitter(
mapping = aes(shape = NMP_cat, group = Software),
position = position_dodge2(width = 1)
)
Hope this helps,
Rui Barradas
Às 17:22 de 04/09/21, Rui Barradas escreveu:
Hello,
The problem is that you have two grouping aesthetics, c
Dear Thomas:
Thank you very much for your input in this matter.
The core part of this R code(s) (please see below) was written by *Richard
O'Keefe*. I had three examples with different sample sizes.
*First sample of size n1 = 204* divided randomly into three groups of sizes
68. *No problems
Thomas,
There are many approaches tried over the years to do partitioning along the
lines you mentioned and others. R already has many built-in or in packages
including some that are quite optimized. So anyone doing serious work can
often avoid doing this the hard way and build on earlier work.
N
Hello,
The problem is that you have two grouping aesthetics, color and shape.
In geom_point make the group explicit:
p <- ggplot(my_data, aes(x = Diet, y = value, color = Software))
p <- p + geom_boxplot(outlier.shape = NA)
p + geom_point(
mapping = aes(shape = NMP_cat, group = Software),
Duncan,
> x[] <- lapply(...) says "set the values in x to the values in the list
> on the RHS", so x retains its class.
thanks!
cheers, Greg
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I was wondering if this is a good alternative method to split a data column
into distinct groups.
Let's say I want my first group to have 4 elements selected randomly
mydata <- LETTERS[1:11]
random_grp <- sample(mydata,4,replace=FALSE)
Now random_grp is:
> random_grp
[1] "H" "E" "A" "D"
# How's
Literal translation...
aggregate( mydf$value
, mydf[ , "year_month", drop=FALSE ]
, function( x ) if ( all( is.na( x ) ) ) NA else sum( x, na.rm = TRUE )
)
On September 4, 2021 9:06:57 AM PDT, Stefano Sofia
wrote:
>Dear R-list users,
>I encountered a silly problem usi
Dear R-list users,
I encountered a silly problem using aggregate, but I am not able to get rid of
it.
I read the manual quite carefully, probaby not enough.
Suppose I have the following data frame:
mydf <- data.frame(year_month=rep(c("2003-12", "2004-12", "2005-12"), 3),
station_number=c(rep(181
On Fri, 3 Sep 2021, Jeff Newmiller wrote:
The fact that your projects are in a single time zone is irrelevant. I am
not sure how you can be so confident in saying it does not matter whether
the data were recorded in PDT or PST, since if it were recorded in PDT
then there would be a day in March
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