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R vs Python
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  • Nov 08, 2018
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It's HARD to know whether to use Python or R for data analysis. And this is especially true if you're a newbie data analyst looking for the right language to start with. It turns out that there are many good resources that can help you to figure out the strengths and weaknesses of both languages. They often go into great detail, and provide a tailored answer to questions such as "What should I use for Machine Learning?",or "I need a fast solution, should I go for Python or R?".

In this post, I have tried our best to answer the question for you…

R or Python? R is the best-suited choice for data scientists over the past years because the functionality of  R was designed keeping data science in mind. Also, it is compatible with languages like C++ and Java. R is used by Google and hence, it is considered a reliable data science language.

When it comes to Python, it is relatively new in the field of data science and has yet to make a lasting mark. However, Python provides many benefits which have led to data scientists to choose Python as their language of choice in data science.

The financial sector switched its data science language to Python after Bank of America started using Python, mainly because it is more versatile and easier to implement. However, some people still prefer R because of its long heritage.

How to Decide :

There are a lot of factors which can help you decide which programming language is bestsuited for you. Data science requires immense programming language proficiency and hence it is important that you choose wisely.

Versatility:

R is considered the best by many because of all the customized packages it offers especially for data science. Python, however, is easy to learn and has a more refined syntax. In case a person is just starting out as a data scientist, it is better to opt for python.

Data visualization support:

Data visualization is of utmost importance in data science and it is at this stage that R proves to be a better alternative than Python. Options like ggplot2 and googleVis

visualization tools simply expand the utility value of visualization. Python is not as versatile as R in this matter, but it still provides visualization tools like Plot.ly or Matplotlib.

Deep Learning support :

Data scientists are required to know about deep learning in order to mine data and Python is the more superior language here. Python provides data scientists with various packages like Theano and TensorFlow, which makes it one of the best languages for deep learning. R can also use some of these packages but Python does have an upper hand here.

To wrap up, we have provided all the important factors which can help you decide which programming language will suit you better as a data scientist.

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