Hi
Others gave you more fundamental answers. To check the possible distribution
you could use package
https://cran.r-project.org/web/packages/fitdistrplus/index.html
Cheers
Petr
> -Original Message-
> From: R-help On Behalf Of Bogdan Tanasa
> Sent: Wednesday, February 8, 2023 5:35 PM
>
Also try
apply(Filter(is.numeric, mydf), 1, sum)
On Tue, Feb 7, 2023 at 8:42 AM PIKAL Petr wrote:
>
> Hi Naresh
>
> If you wanted to automate the function a bit you can use sapply to find
> numeric columns
> ind <- sapply(mydf, is.numeric)
>
> and use it in apply construct
> apply(mydf[,ind], 1,
Hi,
How to split a overflow slide content to slides automatically using revealjs or
other html representation creator in rmarkdown, the effects like beamer "allow
frame breaker" option with subsection number added?
And the main section number (slide title) will not be increased?
Thanks.
How to split a overflow slide content to slides automatically using revealjs or
other html representation creator in rmarkdown, the effects like beamer "allow
frame breaker" option with subsection number added?
And the main section number (slide title) will not be increased?
Thanks.
__
Jorgen is correct that for many purposes, viewing a data.frame as a
collection of vectors of the same length allows you to code fairly complex
logic using whichever vectors you want and result in a vector answer, either
externally or as a new column. Text columns used to make some decisions in
the
Naresh,
This is a common case where the answer to a question is to ask the right
question.
Your question was how to make apply work. My question is how can you get the
functionality you want done in some version of R.
Apply is a tool and it is only one of many tools and may be the wrong one
On 2/8/23 12:06 PM, Ebert,Timothy Aaron wrote:
IMO) The best approach is to develop a good understanding of the individual
processes that resulted in the observed values. The blend of those processes
then results in the distribution of the observed values. This is seldom done,
and often not
IMO) The best approach is to develop a good understanding of the individual
processes that resulted in the observed values. The blend of those processes
then results in the distribution of the observed values. This is seldom done,
and often not possible to do. The alternatives depend on why you
1. This is a statistical question, which usually is inappropriate here:
this list is about R language (including packages) programming.
2. IMO (so others may disagree), your question indicates a profound
misunderstanding of basic statistical issues. While maybe you phrased it
poorly or I misunders
Dear all,
I do have dataframes with numerical values such as 1,9, 20, 51, 100 etc
Which way do you recommend to use in order to identify the type of the
distribution of the data (normal, poisson, bernoulli, exponential,
log-normal etc ..)
Thanks so much,
Bogdan
[[alternative HTML versi
What are you trying to do? Why use apply when there is already a vector
addition operation?
df$x+df$y or as.numeric(df$x)+as.numeric(df$y) or
rowSums(as.numeric(df[c('x','y')])).
As noted in other answers, apply will coerce your data frame to a matrix, and
all entries of a matrix must have the
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