RStudio Desktop provides the RStudio IDE as a native desktop application for Windows, Mac, and Linux. This manual describes RStudio Desktop Professional Edition which adds the following enhancements to the open-source version of RStudio Desktop: A commercial license for organizations not able to use AGPL software; Access to priority RStudio support. Jul 06, 2017 r/RStudio: A place for users of R and RStudio to exchange tips and knowledge about the various applications of R and RStudio in any discipline. 'The downloaded binary packages are in'. (found for 'CentralAC')' The two indicator variables I'm trying to use are 'centralAC' and 'ElementarySchool', with centralac having two levels where.
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The R script uses rJava and RJDBC packages to load tables from database. In Mac OS X, to correctly load this packages
requires the following steps borrowed from https://github.com/snowflakedb/dplyr-snowflakedb/wiki/Configuring-R-rJava-RJDBC-on-Mac-OS-X.
Steps have been modified to reflect problems (and it's solutions) reported here.
requires the following steps borrowed from https://github.com/snowflakedb/dplyr-snowflakedb/wiki/Configuring-R-rJava-RJDBC-on-Mac-OS-X.
Steps have been modified to reflect problems (and it's solutions) reported here.
R has a large active community and provides functions and extensions to the tool set through external libraries which can be imported as you need and discover them. Installing R & RStudio on a Mac. The installation on a Mac is simple and straight forward. There are 2 installations that are required, the R language and the RStudio front end. Windows and Mac users usually do not program from a terminal window, so the Windows and Mac downloads for R come with a simple program that opens a terminal-like window for you to run R code in. This is what opens when you click the R icon on your Windows or Mac computer. We would like to show you a description here but the site won’t allow us. Worked perfectly for me. I had same issues with package nloptr. Just a caveat: windows gave me a warning stating that R was still using the files, so I had to manually go into windows Task Manager and end all processes related to R (even after closing all R windows) to delete the package files. – theforestecologist Nov 8 '16 at 21:54.
Overview
This is the list of software downloads needed in order to connect R via
RJDBC
to a database:- Xcode Command Line Tools
- Java 6
- Java 8
- R
- rJava source package
- Database JDBC jar file
- RStudio (optional)
If you have any of this software already installed, you can skip that section.
Open Terminal.app
We'll change to the Downloads directory as we'll have to download some packages from the internet.
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Just to make debugging easier if something does not go as planned, log all output.
Xcode Command Line Tools
We need Xcode Command Line Tools, by running this command we will invoke the downloader if not installed, otherwise it will report it is already installed.
Java 6
Install the legacy Java 6 runtime which is needed despite us not going to use Java 6.
Now walk through the install to complete.
Java 8
Install Java 8. Note: newer versions may be available.
Now walk through the install to complete.
We'll run these two commands to output Java installations and what the current command defaults to. They are informative only.
You should see something like this:
R for OS X
Download and install the R package for OS X.
Now walk through the install to complete.
Now we need to tell R to use our Java 8 as it's
JAVA_HOME
You should see output similar to
Now install
rJava
from source and compile it against the Java 8 JDK.The 'unset JAVA_HOME' takes care of:Now let's check that rJava can be loaded correctly and returns the correct JDK version.This command should return the string
1.8.0_111-b14
(or whatever Java 8 version you installed).Finish
Exit from the script logging.
Using RStudio.app or R.app
A common error when trying to load rJava in RStudio is:
There are three ways to get around this problem and use
rJava
with RStudio or R console (R.app) :1 - Launching from the command line
You can launch it from the command line in Terminal.app like such:
This is a known limitation with RStudio on OS X. See this link for more details:[https://support.rstudio.com/hc/communities/public/questions/200650933-rJava-fails-to-load-in-RStudio-Desktop-OS-X](https://support.rstudio.com/hc/communities/public/questions/200650933-rJava-fails-to-load-in-RStudio-Desktop-OS-X)
2 - Make a symlink to libjvm.dylib
This is an alternate solution to loading RStudio, but must be updated any time you upgrade Java
+Based on this Stack Overflow thread, one can use the following to work around the
libjvm.dylib
loading issues.3 - Load the library in the script (which is the used approach in the CohortEx R script)
Just a bit of code in your R script:
R and RStudio are both free, open-source software, available for all commonly used operating systems, including Windows, macOS, and Linux systems. R and RStudio install in the standard manner on each of these systems. System-specific instructions for installing R are given below. Regardless of your operating system, you should install R before installing RStudio.
If you wish to install the R Commander graphical user interface for R (used only in lecture 1), please consult the R Commander installation instructions.
Please read and follow these instructions carefully. Installation assistance will also be availabile from the instructor and teaching assistants during office hours.
Installing R on Windows
Visit the Comprehensive R Archive Network (CRAN) and select a mirror site; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for Windows, which appears near the top of the page; then click on install R for the first time, and subsequently on Download R x.y.z for Windows (where x.y.z is the current version of R). Once it is downloaded, double-click on the R installer. You may take all of the defaults, but I suggest that you make the following modifications:
Instead of installing R in the standard location, C:Program FilesRR-x.y.z, I suggest that you use C:RR-x.y.z. Again, x.y.z is the current version of R. This will allow you to install packages in the main R library without running R with administrator privileges and may avoid problems that sometimes occur when there are spaces in paths.
In the Startup options screen, I suggest that you select Yes (customized startup). Then select the SDI (single-document interface) in preference to the default MDI (multiple-document interface); feel free to make other changes, but you may take all the remaining defaults.
Building Packages Under Windows, etc. (Optional)
If you wish to build packages (not covered in this lecture series), or use compiled C, C++, or Fortran code in R, you will have to install some additional software and properly configure your Windows system. You do not have to be able to build R packages in order to install pre-built Windows binary packages from CRAN, so these steps are generally unnecessary unless you plan to write your own packages or use compiled code.
Click on the Rtools link on the R for Windows CRAN page. Download the current version of the Rtools installer and run it. You may take all of the other defaults, but do allow the Rtools installer to modify your system path, by checking the box to edit the system path. If you want to be able to build R packages outside of RStudio, add c:RR-z.y.zbin; to the path (assuming that you installed R in the location that I suggested), after the items added by the Rtools installer. Type this location carefully, including the terminating semicolon -- you don't want to mess up your path.
If you want to be able to build PDF help files for packages, download and install the MiKTeX LaTeX system; there is also a link to MiKTeX on the Building R for Windows page. Installing MiKTeX will also allow you to create Sweave and knitr LaTeX documents in RStudio, and to compile R Markdown documents directly to PDF files.
Installing R on macOS
Visit the Comprehensive R Archive Network (CRAN) and select a mirror site; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for MacOS X, which appears near the top of the page; then click on R-x.y.z.pkg (where x.y.z is the current version of R), which assumes that you are using macOS 10.11 (El Capitan) or higher. You'll also find older versions of R if you have an older version of macOS. Note: As a general matter, you're probably better off updating your macOS to the current version.
Once it is downloaded, double-click on the R installer. You may take all of the defaults.
Building Packages Under macOS, etc. (Optional)
If you wish to build packages (not covered in this leture series), or use compiled C, C++, or Fortran code in R, you must install the Apple Xcode developer tools. For macOS 10.7 (Lion) or higher, you can install Xcode for free from the App Store. For earlier versions of macOS, Xcode can be installed from your system DVD or downloaded from the Apple developer website. You do not need Xcode to install pre-built macOS binary packages from CRAN, so this step is unnecessary unless you plan to write your own packages or use compiled code.
Some R packages include Fortran, C, or C++ code; to build such packages, you will have to install Fortran and C compilers. You do not need the Fortran or C compiler to build most packages, nor to install pre-built macOS binary packages from CRAN. Click on the tools link on the R for Mac OS X page, and click on the link for gfortran-x.y.pkg. Double-click on this file once the download finishes and then omplete the installation. Do the same for clang-x.y.z.pkg. As above, x.y and x.y.z denote the current versions on the R for Mac website.
If you want to be able to build PDF help files, download and install the MacTeX LaTeX system. Installing MacTeX will also allow you to create Sweave and knitr LaTeX documents in RStudio, and to compile R Markdown documents directly to PDF files.
Installing X-Windows on macOS (Optional)
Some R software (e.g., my Rcmdr package) makes use of the Tcl/Tk graphical-user-interface (GUI) builder via the tcltk package to create point-and-click interfaces and to display GUI elements such as progress bars. To use the tcltk package, which is a standard part of the R distribution, you must have the X11 windowing system installed on your Mac. Some other packages that don't use Tcl/Tk, such as the rgl package for dynamic 3D graphics, also require X11.
Check to see whether the X11 windowing system (X Windows) has already been installed on your computer. If you wish, it should do no harm to skip this step and simply go to the next step to install XQuartz.
For OS X 10.6 and 10.7, the file X11.app should appear in the Utilities folder under Applications in the finder. This application should always be installed under OS X 10.7.
For OS X 10.8 or higher, the file is named XQuartz.app and is no longer included with the operating system. XQuartz.app may also be installed in OS X 10.6 or 10.7.
Note that if you upgrade macOS, you will have to reinstall XQuartz even if you installed it previously.
You may also issue the command capabilities('X11') at the R command prompt. If the response is TRUE then X11 is installed.
If neither X11.app nor XQuartz.app is installed, install XQuartz from http://xquartz.macosforge.org. As mentioned, it should do no harm to install XQuartz even if you have X11 currently installed.
1. Download the disk image (dmg) file for XQuartz.2. When you open this file by double-clicking on it, you'll find XQuartz.pkg; double-click on it to run the installer, clicking through all the defaults.3. Important: After the installer runs, you'll have to log out and back on to your macOS account, or just reboot your Mac.
Installing R on Linux Systems
Visit the Comprehensive R Archive Network (CRAN) and select a mirror site near you; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for Linux, which appears near the top of the page. R is available for several Linux distributions (Debian, RedHat, SUSE, and Ubuntu); select your distribution, and proceed as directed.
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If you have a Linux or Unix system that's not compatible with one of these distributions, you will have to compile R from source code; the procedure for doing so is described in the R FAQ (frequently asked questions) list.
Installing RStudio
Go to the RStudio download page, select the free version of RStudio Desktop, scroll down to Installers for Supported Platforms, and click on the link to the appropriate installer for your operating system (Windows, macOS, or Linux distro). Visit the RStudio home page for more information about RStudio.
Once it is downloaded, run the RStudio installer and take all of the defaults: In Windows, double-click on the RStudio installer to start the installation; in macOS, double-click on the downloaded RStudio disk-image file, and drag the RStudio icon to the Applications folder.
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When you first run RStudio, it should detect your R installation and start the R console. To configure RStudio to your taste, select Tools > Global Options (Windows) or RStudio > Preferences (macOS) from the RStudio menus. In particular, I suggest that on the General options screen you deselectRestore .RData into workspace at startup, and set Save workspace to .RData on exit to Never.
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If you encounter difficulties, consult the RStudio troubleshooting guide.
Installing R Packages for the Lecture Series
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Once you have installed R and RStudio, you can install additional packages required for the lecture series by typing the following command at the > command prompt in the R Console (and pressing the Enter or return key):
install.packages(c('car', 'effects', 'ggplot2', 'knitr', 'lme4', 'magrittr', 'rgl', 'rmarkdown', 'sfsmisc'))
You can simply copy and paste this command from these installation instructions. Alternatively, you can install packages from the RStudio Packages tab. Be aware that, depending on the speed of your internet connection, it may take some time to download and install these packages and their dependencies.
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If you wish to use the R Commander, also issue the command install.packages('Rcmdr').
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Finally, if you want to try using C++ code within R, also install the Rcpp package, install.packages('Rcpp').