R or Python? Which is the better for Data Science
Data Science has gained a lot of popularity in recent years and the amount of people opting for a career in data science has increased significantly. Data science is basically an amalgam of data interpretation, algorithm design, and use of technology to solve problems.
Data scientists are provided with data which they have to mine in order to gain invaluable insights, to solve complex problems, and to provide direction to stakeholders. A data scientist should be able to dive into the given data to effectively draw helpful analysis for business decision making. This is the chief KRA of this job, thus making it slightly complex when compared to others.
If you are looking to enter the field of data science, it is important that you equip yourself with the right technical skills so that you can add value in real life corporate scenarios and carve out a lucrative career path for yourself.
Once such question that requires considerable thought is ‘which is the best language for data science, R or Python?’
In this post, we 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 best suited for you. Data science requires immense programming language proficiency and hence it is important that you choose wisely.
1. 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.
2. 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.
3. 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. Do let us know which will be your final choice. We would love to hear from you.
