what is the package of the car() function in R - r

I'm actually developping in R using RStudio. I just want to know in which package is located the function called car() which is used to extract the first element of a list .
Thanks

I don't know what package it's in. But here's how I'd go about finding out...
RSiteSearch("car", restrict = "functions")
or
library(sos)
findFn("car", sortby = "Function")
apropos() and help.search() are also worth looking into.
By the way, in general the first element in a list can be extracted with [[1]]

Related

can't find Objects using pubmed.mineR package

I have downloaded abstracts of interest from pubmed.com then read them using pubmed.mineR package with readabs() function. which is supposed to create object of class "Abstracs", but when I type in ls(), it gives me character(0).
I want to search abstracts using searchabsL(Object,include="protein"),though i don't know how?
mystery solved x = readabs("downloaded file")
thanks Dr.Ramachandran for providing the answer.

Choose function to load from an R package

I like using function reshape from the matlab package, but I need then to specify base::sum(m) each time I want to sum the elements of my matrix or else matlab::sum is called, which only sums by columns..
I need loading package gtools to use the rdirichlet function, but then the function gtools::logit masks the function pracma::logit that I like better..
I gess there are no such things like:
library(loadOnly = "rdirichlet", from = "gtools")
or
library(loadEverythingFrom = "matlab", except = "sum")
.. because functions from the package matlab may internaly work on the matlab::sum function. So the latter must be loaded. But is there no way to get this behavior from the point of view of the user? Something that would feel like:
library(pracma)
library(matlab)
library(gtools)
sum <- base::sum
logit <- pracma::logit
.. but that would not spoil your ls() with all these small utilitary functions?
Maybe I need defining my own default namespace?
To avoid spoiling your ls, you can do something like this:
.ns <- new.env()
.ns$sum <- base::sum
.ns$logit <- pracma::logit
attach(.ns)
To my knowledge there is no easy answer to what you want to achieve. The only dirty hack I can think of is to download the source of the packages "matlab", "gtools", "pracma" and delete the offending functions from their NAMESPACE file prior to installation from source (with R CMD INSTALL package).
However, I would recommend using the explicit notation pracma::logit, because it improves readability of your code for other people and yourself in the future.
This site gives a good overview about package namespaces:
http://r-pkgs.had.co.nz/namespace.html

R Functions require package declaration when they are included from another file?

I am writing some data manipulation scripts in R, and I finally decided to create an external .r file and call my functions from there. But it started giving me some problems when I try calling some functions. Simple example:
This one works with no problem:
change_column_names <- function(file,new_columns,seperation){
new_data <- read.table(file, header=TRUE, sep=seperation)
colnames(new_data) <- new_columns
write.table(new_data, file=file, sep=seperation, quote=FALSE, row.names = FALSE)
}
change_column_names("myfile.txt",c("Column1", "Column2", "Cost"),"|")
When I crate a file "data_manipulation.r", and put the above change_column_names function in there, and do this
sys.source("data_manipulation.r")
change_column_names("myfile.txt",c("Column1", "Column2", "Cost"),"|")
it does not work. It gives me could not find function "read.table" error. I fixed it by changing the function calls to util:::read.table and util:::write.table .
But this kinda getting frustrating. Now I have the same issue with the aggregate function, and I do not even know what package it belongs to.
My questions: Which package aggregate belongs to? How can I easily know what packages functions come from? Any cleaner way to handle this issue?
The sys.source() by default evaluates inside the base environment (which is empty) rather than the global environment (where you usually evaluate code). You probably should just be using source() instead.
You can also see where functions come from by looking at their environment.
environment(aggregate)
# <environment: namespace:stats>
For the first part of your question: If you want to find what package a function belongs to, and that function is working properly you can do one of two (probably more) things:
1.) Access the help files
?aggregate and you will see the package it belongs to in the top of the help file.
Another way, is to simply type aggregate without any arguments into the R console:
> aggregate
function (x, ...)
UseMethod("aggregate")
<bytecode: 0x7fa7a2328b40>
<environment: namespace:stats>
The namespace is the package it belongs to.
2.) Both of those functions that you are having trouble with are base R functions and should always be loaded. I was not able to recreate the issue. Try using source instead of sys.source and let me know if it alleviates your error.

N Choose K function in R not working--what am I missing?

I was trying to acquaint myself with R's nChooseK function but I can't get it to work. I thought it was part of the standard setup (i.e. no additional package needed).
Please help. Here is what I tried:
> nChooseK(10,2)
Error: could not find function "nChooseK"
> n<-4;k<-2
> print(nChooseK(n,k))
Error in print(nChooseK(n, k)) : could not find function "nChooseK"
the last one was an example I saw here: R basic nChooseK
The function is in the R.basic package which is not part of the default R installation. You probably meant to use just choose().
As joran mentions the function nChooseK is a part of R.basic. You can tell this from the example you posted by looking at the top of the page:
You'll notice the "R.basic" in the curley braces which tells you that that function is a part of the "R.basic" package. So to use nChooseK you'll first need to load that package
library(R.basic)
If you don't have R.basic installed yet then you'll need to install it
install.packages("R.basic", contriburl="http://www.braju.com/R/repos/")
library(R.basic)
But as noted the choose function in base R does the same thing
choose(37, 12)
#[1] 1852482996
nChooseK(37, 12)
#[1] 1852482996

Data inside a function (package creation)

If I need to use a data set inside a function (as a lookup table) inside of a package I'm creating do I need to explicitly load the data set inside of the function?
The function and the data set are both part of my package.
Is this the correct way to use that data set inside the function:
foo <- function(x){
x <- dataset_in_question
}
or is this better:
foo <- function(x){
x <- data(dataset_in_question)
}
or is there some approach I'm not thinking of that's correct?
There was a recent discussion about this topic (in the context of package development) on R-devel, numerous points of which are relevant to this question:
If only the options you provide are applicable to your example R himself (i.e., Brian Ripley) tells you to do:
foo <- function(x){
data("dataset_in_question")
}
This approach will however throw a NOTE in R CMD check which can be avoided in upcoming versions of R (or currently R devel) by using the globalVariables() function, added by John Chambers
The 'correct' approach (i.e., the one advocated by Brian Ripley and Peter Dalgaard) would be to use the LazyData option for your package. See this section of "Writing R Extensions".
Btw: I do not fully understand how your first approach should work. What should x <- dataset_in_question do? Is dataset_in_question a global Variable or defined previously?
For me it was necessary to use get() additionally to LazyData: true in DESCRIPTION file (see postig by #Henrik point 3) to get rid of the NOTE no visible binding for global variable .... My R version is 3.2.3.
foo <- function(x){
get("dataset_in_question")
}
So LazyData makes dataset_in_question directly accessible (without using data("dataset_in_question", envir = environment())) and get() is to satisfy R CMD check
HTH
One can just place the data set as a .rda file in the R folder as described by Hadley here: http://r-pkgs.had.co.nz/data.html#data-sysdata
Matthew Jockers uses this approach in the syuzhet package for data sets including the bing data set as seen at ~line 452 here: https://github.com/mjockers/syuzhet/blob/master/R/syuzhet.R
bing is not available to the user but is to the package as demonstrated by: syuzhet:::bing
Essentially, the command devtools::use_data(..., internal = TRUE) will set everything up in the way it's needed.

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