Top 5 best programming languages for data science and analytics: We are living in the information era, Where data is going to be oxygen of everyone we generate millions of data every day. these data are really very helpful in our personal and professional life. To control and maintain this, industries are working in the field of data analytics and data science. These days data science provides a means through which businesses can convert the wide amounts of data available to them into usable information through an analytical approach.
Data scientists have much information to convert statistical algorithms to make sense of large sets of data. These mathematical algorithms have been applied in many programming languages.
I am going to show you 5 programming languages for data science and data analytics, which if you learn well and did master in any one of language from one of them, you could be much more money in your job industry.
Best Programming Languages For Data Science
Let’s have a look at 5 of the best programming languages for data science and data analytics. These are the languages in which you can start learning today and can start the sexiest job in data science.
In the list of programming languages for data science tool, python will be the best language. This programming language is not so much complicated as others. The main use of python is in general programming tasks such as desktop and web applications development. Its readability and productivity really make it very attractive to work on python.
Python package index helps you to access data analytics libraries. The two most popular packages are NumPy and SciPy modules. With the help of these two modules, you can easily implement numerical routines on multi-dimensional arrays and matrices and perform computations of signals and images which are common tasks in data analysis. The other numerous Python libraries are Natural Language Toolkit (NLTK). It allows for statistical analysis of natural languages and makes data analysis easy.
It is really good for beginners and professional data scientists.
2. R Programming
This programming Language is designed by Ross Ihaka and Robert Gentleman. The main purpose of designing this language is to design a better and user-friendly way of doing data analysis, statistical and visualization computation on large sets of data.
It has become a popular and reputed name in the field of data analysis and commercial analysis so this could be the best option for you to learn this language for data scientists. To know more about R language you can join the community of the folks who are working for this language.
This language is Developed by Jack Little, Moler, and Steve Bangert. Steve Bangert is the founder of MathWorks. Matlab has their own reputation in the world of technical computing. When the all the feature of MATLAB comes together then it is more than a programming language.
It is really a good experience to work when features of MATLAB computation, visualization, and programming come together into a single environment. These qualities of MATLAB makes it an excellent language.