If you are interested in Big Data as a career choice and are
aware of the skills required to be an expert in this field, then chances are
high that you are aware of the role of R and python programming languages for
analyzing data. In case you are confused about which language to learn first, this
blog will guide you towards making the right decision.
R and Python are free solutions which are user friendly and
can be used for data analysis. It is normal for beginners to wonder which
language to learn first; but the good thing is both are excellent choices.
Recent studies on the use of programming languages has
revealed the following:
Why You Should Choose
R?
R has an active, dedicated and thriving community which
helps beginners by resolving their queries and offering assistance on various
aspects of R. Also, R has an abundance of packages that makes it both
accessible and functioning. It is also compatible with Java, C, C++.
R programming does heavy tasks in statistical analysis and
also creates high definition graphics. R can perform complicated mathematical
operations and the array centered syntax of this language provides great help
to persons with little or no knowledge of coding.
Why You Should Choose
Python?
Unlike the specialized nature of R, Python is a language
that performs a wide range of tasks like engineering and wrangling data,
building web applications and scraping websites among others. If have knowledge
in OOP, then it is much easier to learn than R programming. Also the code in
python is robust, unlike R.
Though its data packages are limited, Python when used in
conjunction with tools like Numpy, Pandas, Scikit, it comes pretty close to the
comprehensive functionality of R. It is also being adopted for tasks like
statistical work of intermediate and basic complexity as well as machine
learning.
For more details please visit our blog at http://www.dexlabanalytics.com/blog/python-vs-r-which-you-want-to-learn-first
