In this discussion we know about the term how to learn R programming?. Nowadays this programming language is so popular among the students when they want to learn about this term. How is it used mostly?. And in which field this programming language is mostly used. And we are trying to know related to this term what steps are followed when we learn it. Some key points related to R programming are also discussed in this discussion. So let us start to know more about the learning way of R programming.
Note: If you are a student and enhnace you knowledge of the C Programming, then you can get help from our experts C Programming Help.
WHAT IS R PROGRAMMING LANGUAGE?
R programming language refers to an open-source programming language. It is used at a broad level as a data analysis tool and statistical software. R commonly comes up with the command-line interface. R is used on a wide variety of platforms such as Linux, windows, and mac0S. And it is the latest cutting-edge tool programming language.
Father of R programming language was Ross Ihaka and Robert Gentleman, located in University of Auckland, New Zealand, R Development Core Team is currently developing it.
This is a redefined form of S programming language. This project came in 1992, and its initial version came in 1995 and a final beta version in 2000.
In simple words R programming language, helping you to set basic Excel file analysis. This programming language and the development environment is open source and having growth in popularity.
SOME POPULAR EXAMPLE OF R PROGRAMMING LANGUAGE –
- Find Mean, Sum, and product of Vector
- Check that a number is prime or not
- Find out a Factorial of a number
- “Hello Word” programming
- Collect the input from its users
FEATURES OF R PROGRAMMING LANGUAGE
- BASIC STATISTICS – In this programming language the basic statistics points are the mean, median, and mode. These all terms are known as “Measures of Central Tendency.” So we measure the central tendency very easily when we use it.
- DATA ANALYSIS – This programming language provides the coherent, large and an integrated collection of tools for analysing the data.
- PROBABILITY DISTRIBUTION – It plays a big role in statistical tools when we use it and we can handle the various types of probability distribution like Normal Distribution, Binomial Distribution, and Chi-Squared Distribution and many or more.
- R PACKAGES – This is one of the major features of R language; it creates a broad availability of libraries. It is holding out the more then 10,000 packages.
- DISTRIBUTED COMPUTING – It is a modal in which different components of a programming system are shared with different computers to improve performance and efficiency.
HOW TO LEARN R PROGRAMMING :- Learn R in the right way to following the further steps
STEP 1. FIND OUT YOUR MOTIVATION FOR LEARNING R –
Before when you cracking a textbook, sign up for learning programme, and click played no your first tutorial video, take some time to really think about that why you want to learning R programming language, and in what you want to do like with it or not to do like with it.
What data are you taking in your interest field?
Which product do you choose to build up?
Which of the questions do you want to answer?
Find something the process motivates you. This step helps you to define your final goal, and it will help you to get the final goal without any boredom.
Select your interest of area, like as –
- Dashboard reports
- Data visualisation
- Data science
- Data Analysis
- Machine learning
STEP 2. LEARNING THE BASIC SYNTAX
In this way there is no way to purely ignore this step. It is a programming language and it is more important than in human language. If you say that learning syntax is boring, then what is your goal? You must spend as little time as possible doing syntax learning.
There are some of the resources for learning the basics of R programming :
- Codecademy – it’s a good job of teaching the basic syntax.
- R for Data Science – It is one of the most usefulling resources for learning R.
- RStudio Cloud Primers – without installing any type of software with cloud-based you can start the coding.
- RStudio Education – its resources including the book, webinars, and tutorials contains the education page for the beginners.
STEP 3. WORKING ON THE STRUCTURED PROJECTS
When you complete the step to get efficient syntax under your range, now you are moving to the next step to work on structure projects more independently. In structured projects, it’s a great way for how to learn R programming. Rather than looking for structured projects you can build more experience and rise up your comfortable level.
STEP 4. BUILDING YOUR PROJECT ON YOUR OWN
After finishing some of your structured programmes, now you have to move on to the next stage of learning R programming. In this stage you are trying to know how much till now you learned, and try to do something new. Working on some of the new unique projects you are working on as of now. So take up a new project sometimes it means you are learning a new R package.
You think your project in which you are working is like a series of steps – in a series it is one should set every step a little higher, and it be a little more challenging than one before.
STEP 5. – RAMP UP ALL THE DIFFICULTY
Working on projects is great, but you need to learn R if you want to ensure that you keep learning. You can do more with only data visualisation.
At last if you are n’t sure exactly how to do that, you are surely going to ask some of the questions which are related to it. You can ask yourself and apply for more difficulty and complexity to any project you are considering.
This is all about how to learn R programming.
LET’S SUM UP
As of now we reach the final point about how to learn R programming? In this discussion we learned all the necessary points related to R programming. Now we are able to understand some of the steps followed in the R learning programming to perform smoothly. In R programming it includes jobs in R programming, online courses, and with the help of this you can expand your skill set with the R programming for Data Science.