R Studio For Macos

For Unix and MacOS, ODBC drivers should be compiled againstunixODBC. Drivers compiled against iODBCmay also work, but are not fully supported.

R-Studio 4.6 – Powerful data recovery, RAID and dynamic disks supported. R-Studio is powerful and cost-effective data recovery software for Apple lovers. R-Studio for Mac is specially designed for Mac OS X environment and recovers files from. Download the R-3.2.3.pkg, which is the latest version as of this blog post. The package will download and double click to install. The installation is straight forward, select ‘Continue’ and follow the prompts. The R backend is now installed and we can move to installing RStudio. Step 2 – Installing R Studio.

After installation of the driver manager and driver, you will have toregister the driver in a odbcinst.ini file for it to appear in odbc::odbcListDrivers().

Microsoft Windows

Database Drivers

Windows is bundled with ODBC libraries; however, drivers for each databaseneed to be installed separately. Windows ODBC drivers typically include aninstaller that must be run to install the drivers in the properlocations.

Administration

The ODBC Data Source Administratorapplication is used to manage ODBC data sources on Windows.

Apple MacOS

Installation

1. Install homebrew to install database drivers easily on MacOS

2. Install UnixODBC, which is required for all databases

3. Install common DB drivers (optional)

Setting up database connections

See the section with the same name in the Linux section.

Linux Debian / Ubuntu

Installation

The apt-get command can be used to install databasedrivers easily on Linux distributions that support it, such as Debian and Ubuntu.

1. Install UnixODBC, which is required for all databases

2. Install common DB drivers (optional)

Setting up database connections

On MacOS and Linux, there are two separate text files that need to be edited.UnixODBC includes a command-line executable called odbcinst, which can be used toquery and modify the DSN files. However, these are plain text files youcan also edit by hand if desired.

There are two different files used to set up the DSN information:

• odbcinst.ini defines driver options

• odbc.ini defines connection options

odbcinst.ini

This file contains the driver information, particularly the name of the driver library.Multiple drivers can be specified in the same file.

odbc.ini

This file contains the connection information, particularly the username, password, databaseand host information. The Driver line corresponds to the driver defined inodbcinst.ini.

See also: unixODBC without the GUI for more information and examples.

Location

The DSN configuration files can be defined globally for all users of thesystem, often at/etc/odbc.ini or /opt/local/etc/odbc.ini. The file location depends onwhat option was used when compiling unixODBC; odbcinst -j can be used to findthe exact location. Alternatively, the ODBCSYSINI environment variable can beused to specify the location of the configuration files. Ex. ODBCSYSINI=~/ODBC

A local DSN file can also be used with the files ~/.odbc.ini and ~/.odbcinst.ini.

Connecting to a Database in R

Databases can be connected by specifying a connection string directly, or withDSN configuration files.

Connection Strings

Pass the connection parameters as arguments to the dbConnect() function.

For database-specific settings, go to the Databases section in the menu and look for the page that matches the desired database type.

DSN Configuration files

ODBC configuration files are another option to specify connection parameters; theyallow you to use a Data Source Name (DSN) to make it easier to connect to a database.

For more information about how DSN can be used, check out the following articles in this site:

I have fallen in love with the R language and tool set over the last few weeks. I find that getting outside my comfort zone and learning new tools can always spur creativity and the open source community has a great many tools just waiting to be discovered. The fact that there is a free option for RStudio provides a powerful analysis tool to organizations without taking a large hit to the budget.

R is a statistical computing and graphics language and is available as free software under the GNU general public license. RStudio is a free and open source integrated development environment that puts a user interface over the R command line back end. The combination of the two provides a powerful data analysis toolset.

The tools are more command line and have a programming style rather than a point and click tool such as Microsoft’s Excel. This tool would appeal to the power user analyst or a user with more of a programming background.

R has a Very Active Community

The trouble with adding open source software to your workflow is making sure that the tool is active and being updated on a regular basis. The main criteria I look for is based on how large and active the community around the tool is.

• Do people have a passion for the software?
• Is there an active community?
• When was the last update?
• How often has the software been updated?

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. You can install a desktop or server version, however I find for personal use the desktop install and user experience easier to manage.

Step 1 – Installing R

RStudio requires R version 2.11.1 or higher which can be downloaded here; http://cran.rstudio.com/ . There will be 3 versions listed, select the “Download the R for (Mac) OS X” version by first selecting the option below.

This will take you to the binaries page. Download the R-3.2.3.pkg, which is the latest version as of this blog post.

The package will download and double click to install. The installation is straight forward, select ‘Continue’ and follow the prompts.

The R backend is now installed and we can move to installing RStudio.

Step 2 – Installing R Studio

The RStudio desktop version can be found here, https://www.rstudio.com/products/rstudio/#Desktop . There is an open source version and a purchased version that includes various options and support.

The icon above takes you to the various desktop versions, select the Mac OS X version.

Once Downloaded, double click on the RStudio package.

Drag the RStudio icon to the Application Folder

On my machine, I have an older version, you can select ‘Replace’ to only keep the new version.

In Launch Pad, Type in R in finder, you will see both R and RStudio. Select RStudio and the following message is displayed, Select Open to run RStudio

Step3 – Try it out

RStudio is now displayed. You get the option to see a demo which will allow us to see if all is working correctly.
Type the following 2 lines of code in the console and press enter;

X = rnorm(200)
Plot(x)


RStudio is now installed and ready for your analysis.

Resources available

There are many resources and tutorials that can be used to learn more about using the R language, I have listed a few below.

R Project for Statistical Computing, https://www.r-project.org

RStudio, https://www.rstudio.com/resources/training/online-learning/#R How to install crack office on macbook air 2.

I hope you find these useful.

Steve

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