R Tools Technology

Introduction to the R tools technology

R tool for analytics is the most powerful and widely used programming language for computational statistics, visualization and data science. Many data scientists and statisticians use R to solve their problems in the data analysis field in all the sections like computational biology to quantitative marketing. R is a GNU project which is more like the S language. It is considered as a dialect of the S language.

R tool for data Analysis provides a wide range of statistical and graphical techniques. R is highly extensible and offers a lot of choice for research people.

R is a free software and it runs on a wide variety of platforms like MacOS, Windows, UNIX and Linux.

It is also the most popular and successful language with some powerful features. It is used by top rated companies like Google, Facebook, Shell, Merck, Bank of America, Pfizer and LinkedIn.

Installation

Here is a detailed tutorial with screenshots to install R tools technology

1. Go to the R website and click Download R under the heading “Getting started”

2. Select a destination to download R

3. Choose which R package to download based on your OS

4. Select “Install R for the first time” and download the file with the biggest font on the top

5. Click “Run” and then choose your language

6. Click “Next” to start the installation and agree to all their terms and conditions

7. Select Core files and select either 32 bit or64 bit files based on your computer system

8. You have a choice for Startup options. You can view the program in multiple windows so that you can also have an internet browser or notepad program open as well. The screen appears as below

9. If you want to get this view then you should click Yes for customized startup option in the Startup option

10. If you have clicked Yes then you will be directed to the below dialog box and select “SDI” (separate window) option

11. In this step you choose between plain text or HTML

12. Next step is to select between standard or Internet2 for internet access

13. Create a program shortcut and desktop icon by clicking Next

14. The installation will start running as shown in the figure below

15. Once the installation is complete you will get the following window. Click “Finish”

Environment

R tool is an integrated suite of software facilities developed for data analysis, statistical modelling, simulation and graphics. R is a simple and effective language which includes conditionals, loops, user-defined recursive functions, input and output facilities. R includes the following

• effective data handling and storage facility
• set of operators for calculation of arrays
• huge integrated collection of intermediate R tool for data analysis
• graphical facilities to be displayed either on screen or on hard copy
• allows users to add additional functionality
• C, C++ and Fortran code can be linked to R tools technology and called at run time
• R can be extended through packages easily
• R has its own Latex-like documentation format which supplies comprehensive documentation

Updating

Follow these simple steps to Update R

1. Load the Installr

2. Select “Update R” from the new ” Installr” menu

3. Installr will check whether there is a new version to update and click Ok

4. If you wish to check the News of the new version click Yes

5. Click Yes if you want to download and install the latest R version

6. The download will start

7. Press ‘Next’ in the R’s installation wizard

8. Wait till the R finishes its installation

9. Press Yes to copy your packages to the new R installation

10. Click Yes to keep your package in your Old R folder

11. Wait till the packages get copied

12. You can also get Rprofile .site be copied automatically to the new location

13. Click Yes to get updated packages in the new R installation

14. R needs your permission to access to the internet

15. Wait till the packages are updated and the process is run in the background

16. Final step is to Quit R

Why use R tools Technology?

There is a lot of software available for data analysis today but still, R tool stands ahead of all the other tools. There are a lot of reasons why data scientists choose R. Few reasons are listed below

• R tools technology is free

R is an open source project which you can download and use for free. You don’t have to worry about subscription fees, license fees, license renewals or user limits. As R is an open source software you can inspect and make changes to the code as you like. Lot of experts have contributed to R in such way and now it benefits millions of people who use R today.

• R is not just a statistical package, it is a language

R is an easy language to learn. In R data analysis is done by writing functions and scripts not just in simple clicks. It offers a natural and expressive way for data analysis. There are many advantages of learning this language. It is the most interactive language when compared with other programming languages. R provides innovative way of data analysis and leads to better results which otherwise would not have been done. A script records all your work which can be re-run at any time. These scripts also makes it easy for you to automate a sequence of tasks that can be integrated into other processes.

• R tool for analytics techniques at your fingertips

R contains all the traditional and recently developed data manipulation techniques. It also offers you different statistical models and charts that all the data scientists feel is essential to them. You can easily download any method at free of cost.

• Powerful graphics and Data Visualization

One of the main features of R tools technology is the visualization of data through charts and graphs. R tools technology offers special tools for producing graphics from information provided in the form of bar charts and scatter plots to multi-panel Lattice charts. Experts in data visualization like Bill Cleveland and Edward Tufte also believe in R’s graphical system. Because of its excellent graphical properties, R tools technology is used in reputed places like the New York Times, the Economist and the FlowingData Blog.

• Faster and better results

R stands ahead of the usual black-box procedures of other data analytics tool. R is designed especially for data analysis to create faster results than other statistical software programmes. It also offers you mix and match models for better results. The scripts of R are automated which helps you to deliver reproducible research.

• Cutting edge statistics with R tools technology

Leading data scientists and researchers around the world use R for statistics, machine learning, and predictive modeling. R has a lot of packages that are not available in any other statistical tool in the data analysis market. There are more than 2000 packages available in R language in every domain for free download. And more packages are added frequently. Because of such packages, R tools technology is widely used in fields like finance, genomics and a lot of other fields. One example of such package is “glmnet”. This is an exclusive modeling package which handles the prediction of interval and categorical dependent variables efficiently.

• Flexible R tool  for data analysis

R tools technology has an inbuilt standard data analysis tool which includes accessing data in various formats, data manipulation and traditional and modern statistical models. The statistical models include regression, ANOVA, GLM, tree models and others. All the statistical tools are available in an object-oriented framework that will help you to extract only the information you need from the results. It will thus reduce unwanted statistics and you don’t have to produce a cut and paste static report.

• Robust community

If you have any questions related to R then there is definitely an answer for you on the web. There are a lot of community resources available on the internet for R. R has thousands of contributors and more than two million users from around the world. This is one of the main reason you can find answers to all your questions related to R on the web.

• Unlimited possibilities

R is an open source community and a lot of people contribute directly to the R language. It does not have a predefined set of codes. You can use codes that are contributed by others to the R community. You can also extend the R functions. R gets mingled up easily with other applications like MySQL database, Apache web server, Google maps and others.

• Wide acceptance of R

R is used widely by most of the industries in India and abroad. R is becoming a leader in business analytics field. Recently SAS is also being integrated with R and is included in SAS/ML Studio 3.2 version. It is also mostly used in clinical researches by the government.

Special features

Following are some of the special features of R Tools.

• R is available for Windows, Linux and MacOS platforms
• R lets you to input data from SAS, Excel, SPSS, STATA, and others
• R is an excellent tool for creating complicated plots and charts which will be of great quality
• R lets you display statistical concepts by means of animations
• R can be embedded in Excel. This will provide you with a whole new range of statistics and graphical properties
• R has a very good community support which gives answers to all your queries. Most of the responses come from experts in the data analysis field. The community gives you a detailed insight into the R language for newbie’s
• R provides data analytics solution on the web by embedding R on a server through Apache server
• R has a lot of packages which are written for a specific purpose. All the packages are contained in CRAN and the packages are divided based on their target domain
• R contains codes to perform all the basic and advanced statistics
• R has Revolution Computing which is an enterprise R provider
• R has a blog for them which discusses the latest developments, usages of R in various fields and various other matters which are related to R

Why it gets so much attention?

There are many languages used for data analysis but most people prefer using R for their business. The reasons why R is preferred more than other languages are listed below

• More interactive language – For data analysis, two things are more important – Interactivity and Language. R in other terms is an interactive language which makes it more special than other languages.
• Data structures – It also offers you an excellent way to create data structures. You don’t need to put all your data in a set of a predefined structure. You can create your own structure and put your data in a natural form.
• Excellent graphical properties – Human brains are more attracted to pictures than numbers or text. R gives you a high-quality graphical representation of data.
• Missing values – Real data always have missing values. R has several functions that will help you deal with missing values. Missing values are an integral part of R.
• A lot of packages – R has a lot of packages that allow you to add your own functionality to make it unique. These packages help you do extraordinary things with R.
• Support and Community – R has a very supportive community which helps to improve data analysis done through R language
• First class objects – Objects here means functions like mean and median. You can shift between the functions more easily in R language.
• Vector-oriented – Objects in R are considered as a whole rather than treating it as a collection of individual numbers. For example, if you want to change the volume from liters to milliliters then a simple code change has to be done.
• Flexibility – R does not compel you to work only within its language. You can mix different tools and select the best tool for each task. You can also call C and C++ functionality
• Changes made easy – The codes that are written in R language is accessible to the users. If any minor change has to be done to the task then you can make a change to the code in a shorter period of time.

Connecting to MySQL from R

There are two ways through which you can connect to MySQL from R

1. Using RODBC library

2. Using MySQL library

Here are few steps to explain to you how MySQL is connected to R through ODBC library.

• Download the ODBC driver from the site

• To ODBC setup Go to Control Panel à Administrative tools à ODBC

• Click Add to add a new ODBC Setup for MySQL

• Click Finish. Now you will get a screen where you need to enter the IP address of the MySQL server

• After MySQL ODBS connection is done, move to R to invoke this data source and to access any one of the table in R

• Now load the library RODBC using the following command

• Once RODBC is installed, connect to the classic models database in the MySQL and test the RODBC library

An Example of creating a scatter plot with R tools technology

The following table provides you with the data. One column has Years and the other one is Total Telephones sold which is in millions.

Year	Total Telephones Sold
2004	76.53
2005	98.37
2006	142.09
2007	205.87
2008	300.49
2009	429.73
2010	621.28
2011	846.32
2012	951.35
2013	898.02

Step 1: Load this data into R using the load.csv method

Step 2: Now you have the data in my data section as shown below

Step 3: Now plot the graph using the command

Step 4: Your result will be shown as follows

Applications

R tools technology applications are used in a wide range of fields from astronomy, finance and chemistry to medicine and much more. R’s packages are dedicated to specific applications. You can also create your own R application and you don’t need to be a genius to do that. Some of the R packages for applications are listed below.

• Clinical Trials
• Cluster analysis
• Computational Physics
• Differential Equations
• Environmental Studies
• Finance
• Genetics
• Graphical Models
• Graphics and Visualization
• Machine learning
• Medical Imaging
• Natural Language Processing
• Official Statistics

R Community

R is a global community where a lot of people spend their time and effort to maintain and develop the R language and its environment. This community plays an important role in making R a high quality and transparent software. R community does the following activities

• Supports and enhances the R language
• Enlarge the scope and power of the R language
• Create new applications in different fields using R
• Talk about the benefits and advantages of R
• Provide help for the beginners to start with R

Contributors

R has thousands of contributors from different parts of the world. The heavy lifters of R are the members of the R group. They make changes, fix bugs, test the code, maintain the CRAN and keep it going on all the supported platforms.

Which you should choose this technology?

There are different versions of R available for every type of user and different type of budget. Select one that fits your need to get better results from R.

Conclusion

From this article, you can have a clear idea about R tools technology. It is also proved that it is the most important platform for the development of new statistical methods. It stands ahead of other data analysis tools. If you are a data scientist then you should definitely learn R like any other language. If you love programming then you will definitely love working with R tools technology. If you want to become a master of R language then you need to practice the language often and use it for performing important tasks.

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