Helping Yourself
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Before asking others for help, it’s generally a good idea for you to try to help yourself. R includes extensive facilities for accessing documentation and searching for help. There are also specialized search engines for accessing information about R on the internet, and general internet search engines can also prove useful (see below).
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- Build and/or document how to use packages such as: dplyr, DBI, odbc, keyring and pool. This website is the main channel to provide support in this area. RStudio is also working through other delivery channels, such as upcoming webinars and in-person training during our RStudio conferences.
L e a r n m o r e. S i g n i n to see your search history on different browsers and computers.
R Help: help() and ?
The help() function and ? help operator in R provide access to the documentation pages for R functions, data sets, and other objects, both for packages in the standard R distribution and for contributed packages. To access documentation for the standard lm (linear model) function, for example, enter the command help(lm) or help('lm'), or ?lm or ?'lm' (i.e., the quotes are optional).
To access help for a function in a package that’s not currently loaded, specify in addition the name of the package: For example, to obtain documentation for the rlm() (robust linear model) function in the MASS package, help(rlm, package='MASS').
Standard names in R consist of upper- and lower-case letters, numerals (0-9), underscores (_), and periods (.), and must begin with a letter or a period. To obtain help for an object with a non-standard name (such as the help operator ?), the name must be quoted: for example, help('?') or ?'?'.
You may also use the help() function to access information about a package in your library — for example, help(package='MASS') — which displays an index of available help pages for the package along with some other information.
Help pages for functions usually include a section with executable examples illustrating how the functions work. You can execute these examples in the current R session via the example() command: e.g., example(lm).
Vignettes and Code Demonstrations: browseVignettes(), vignette() and demo()
Many packages include vignettes, which are discursive documents meant to illustrate and explain facilities in the package. Domus 3d keygen torrent. You can discover vignettes by accessing the help page for a package, or via the browseVignettes() function: the command browseVignettes() opens a list of vignettes from all of your installed packages in your browser, while browseVignettes(package=package-name) (e.g., browseVignettes(package='survival')) shows the vignettes, if any, for a particular package. vignette() is employed similarly, but displays a list of vignettes in text form.
You can also use the vignette('vignette-name') command to view a vignette (possibly specifying the name of the package in which the vignette resides, if the vignette name is not unique): for example, vignette('timedep') or vignette('timedep', package='survival') (which are, in this case, equivalent).
Vignettes may also be accessed from the CRAN page for the package (e.g. survival), if you wish to review the vignette for a package prior to installing and/or using it.
Packages may also include extended code demonstrations (“demos”). The command demo() lists all demos for all packages in your library, while demo(package='package-name') (e.g., demo(package='stats')) lists demos in a particular package. To run a demo, call the demo() function with the quoted name of the demo (e.g., demo('nlm')), specifying the name of the package if the name of the demo isn’t unique (e.g., demo('nlm', package='stats'), where, in this case, the package name need not be given explicitly).
Searching for Help Within R
The help() function and ? operator are useful only if you already know the name of the function that you wish to use. There are also facilities in the standard R distribution for discovering functions and other objects. The following functions cast a progressively wider net. Use the help system to obtain complete documentation for these functions: for example, ?apropos.
apropos()
The apropos() function searches for objects, including functions, directly accessible in the current R session that have names that include a specified character string. This may be a literal string or a regular expression to be used for pattern-matching (see ?'regular expression'). By default, string matching by apropos() is case-insensitive. For example, apropos('^glm') returns the names of all accessible objects that start with the (case-insensitive) characters 'glm'.
help.search() and ??
The help.search() function scans the documentation for packages installed in your library. The (first) argument to help.search() is a character string or regular expression. For example, help.search('^glm') searches for help pages, vignettes, and code demos that have help “aliases,” “concepts,” or titles that begin (case-insensitively) with the characters 'glm'. The ?? operator is a synonym for help.search(): for example, ??'^glm'.
RSiteSearch()
RSiteSearch() uses an internet search engine (also see below) to search for information in function help pages and vignettes for all CRAN packages, and in CRAN task views (described below). Unlike the apropos() and help.search() functions, RSiteSearch() requires an active internet connection and doesn’t employ regular expressions. Braces may be used to specify multi-word terms; otherwise matches for individual words are included. For example, RSiteSearch('{generalized linear model}') returns information about R functions, vignettes, and CRAN task views related to the term 'generalized linear model' without matching the individual words 'generalized', 'linear', or 'model'.
findfn() and ??? in the sos package, which is not part of the standard R distribution but is available on CRAN, provide an alternative interface to RSiteSearch().
help.start()
help.start() starts and displays a hypertext based version of R’s online documentation in your default browser that provides links to locally installed versions of the R manuals, a listing of your currently installed packages and other documentation resources.
R Help on the Internet
There are internet search sites that are specialized for R searches, including search.r-project.org (which is the site used by RSiteSearch) and Rseek.org.
Ulead photoimpact 7 kostenlos download. It is also possible to use a general search site like Google, by qualifying the search with “R” or the name of an R package (or both). It can be particularly helpful to paste an error message into a search engine to find out whether others have solved a problem that you encountered.
CRAN Task Views
CRAN Task Views are documents that summarize R resources on CRAN in particular areas of application, helping your to navigate the maze of thousands of CRAN packages. A list of available Task Views may be found on CRAN.
R FAQs (Frequently Asked Questions)
There are three primary FAQ listings which are periodically updated to reflect very commonly asked questions by R users. There is a Main R FAQ, a Windows specific R FAQ and a Mac OS (OS X) specific R FAQ.
Asking for Help
If you find that you can’t answer a question or solve a problem yourself, you can ask others for help, either locally (if you know someone who is knowledgeable about R) or on the internet. In order to ask a question effectively, it helps to phrase the question clearly, and, if you’re trying to solve a problem, to include a small, self-contained, reproducible example of the problem that others can execute. For information on how to ask questions, see, e.g., the R mailing list posting guide, and the document about how to create reproducible examples for R on Stack Overflow.
Stack Overflow
Stack Overflow is a well organized and formatted site for help and discussions about programming. It has excellent searchability. Topics are tagged, and “r” is a very popular tag on the site with almost 150,000 questions (as of summer 2016). To go directly to R-related topics, visit http://stackoverflow.com/questions/tagged/r. For an example both of the value of the site’s organization and information that is very useful to R users, see “How to make a great R reproducible example?”, which is also mentioned above.
R Email Lists
The R Project maintains a number of subscription-based email lists for posing and answering questions about R, including the general R-help email list, the R-devel list for R code development, and R-package-devel list for developers of CRAN packages; lists for announcements about R and R packages; and a variety of more specialized lists. Before posing a question on one of these lists, please read the R mailing list instructions and the posting guide.
RStudio makes it as easy to work with databases in R. This work focuses on three key areas:
1. RStudio products
- The new RStudio Connections Pane makes it possible to easily connect to a variety of data sources, and explore the objects and data inside the connection
- To RStudio commercial customers, we offer RStudio Professional ODBC Drivers, these are data connectors that help you connect to some of the most popular databases.
2. R packages
Build and/or document how to use packages such as: dplyr, DBI, odbc, keyring and pool
3. Education
R&l Tracking
This website is the main channel to provide support in this area. RStudio is also working through other delivery channels, such as upcoming webinars and in-person training during our RStudio conferences.