We can say this question the most discussed questions in the world of data science! So today our discussion will remain in the entire article, why it really needs Python or why R is needed or which is better. The question might have arisen in our mind, but the question is many data scientists, especially those in the new Data Science field!

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Those who have taken the first step in data science, that means they have to be masters of any language in the first place. Then you can move to any language. An example can be given that you have trained from the Marine Academy to become a sailor, then you can choose any ship as a sailor. Because, it is actually the processor of your process and technique, and if you master any language, you can easily switch to any other language. But you have to learn a lot better than your first programming language.

Both Python and R at the Data Science are now leading from the front. If the question arises, which one is better then I will say "it depends on your prestige". Then what will we pick up?

For some years now, R is the first choice for data science. Although it was created for statisticians, there are thousands of public packages and C, C ++, Java etc.

Integrate with language can work very well. As we understand the rises of R, see the widespread use of it. Companies like Google, Facebook and Silicon Valley from Wall Street are used everywhere as a good alternative to R, Matlab and SAS.

On the other hand, Python and the difference is different case, many people have chosen Python for their work. As a result, Python is now at the top level in the market trends. Python is the best choice of tech people as well as in data science and a widespread use is going on. Python is basically taking the financial sector into its own right. Similarly, R is challenging me, I'm going to boss!

If we see statistically, if a person is a mathematician or works with statisticians and does not have extensive knowledge in computer science, then he is going to R and the Better options.
If I or someone who works in a computer or software field like us, then I would love Python.

Because, Python is a General Purpose language and specialized language. So, if I once learned Python then for the hasoop, spark for big data, for scikit-image image processing, for tkinter desktop applications, server site scripting and list in mongdibi will increase ....

Why would you choose Python? 5 strong reasons to check out:

✔1. Easy to Use

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Python itself has earned a reputation for itself, so it is very easy to flip. Let's read the syntax easily. If you want to use Predictive Analysis in Data Science, there are many data mining tools for many Predictive Analysis.

You are a software engineer or a data analyst or data analyst, or you start new Python for you. Because it's easy to pick up.

✔2. Python is Versatile

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We know Python is a General Purpose Language This is how Web, desktop apps are created. Likewise, data mining or any problem can be solved. End-to-End solution for data processing solution is solved.

✔3. Python is better for building analytics tools

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R and Python are both good if you want to find a dataset outliers. But when you want to find web services outliers, then Python is ahead. Python does not have a pair for self-service analysis.

✔4. Data Visualization

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Now I have to agree to the meaning of Python! Because, R visualization and ahead of the Python in the field. R is also some impresive tools such as Ggplot2, rCharts, and googleVis. And Python Naturalization can not visualize, but there are some libraries that do not have any -Matplotlib, Plot.ly, or Seaborn.

✔5. Growing Python Community

Python is better for deep learning:

There are many packages to create a deep neural network in Python, such as Theano, Keras, and tensorFlow. Some packages work on R.

So, do you use python for data science? Python is a powerful language and a lot of time saving work. And R is a specially designed language, which is special for data analysis. But you can also use R for your work, as well as Python.

My personal opinion about Python, I can choose Python. Because, scalability.

When you save the data science as a carrier, at the end of the day you have to work with big data. The popular framework for Big Data Processing, Apache Spark is an open source that supports Python (supports R but not as comprehensive as Python). And Python has many MacCur data processing tools

Such as sklearn .... I'd definitively decide Python

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