Python vs. R vs. SAS

We will compare the three languages based on the following aspects:

1. Availability / Cost
2. Ease of learning
3. Data handling capabilities
4. Graphical capabilities
5. Advancements in tool
6. Job scenario
7. Deep Learning Support
8. Customer service support and Community

SAS : SAS has been the undisputed market leader in commercial analytics space. The software offers huge array of statistical functions, has good GUI (Enterprise Guide & Miner) for people to learn quickly and provides awesome technical support. However, it ends up being the most expensive option and is not always enriched with latest statistical functions.

R : R is the Open source counterpart of SAS, which has traditionally been used in academics and research. Because of its open source nature, latest techniques get released quickly. There is a lot of documentation available over the internet and it is a very cost-effective option.

Python : With origination as an open source scripting language, Python usage has grown over time. Today, it sports libraries (numpy, scipy and matplotlib) and functions for almost any statistical operation / model building you may want to do. Since introduction of pandas, it has become very strong in operations on structured data.

We see the market slightly bending towards Python in today’s scenario. It will be pre-mature to place bets on what will prevail, given the dynamic nature of industry. Depending on your circumstances (career stage, financials etc.) you can add your own weights and come up with what might be suitable for you. Here are a few specific scenarios:

• If you are a fresher entering in analytics industry (specifically so in India), I would recommend to learn SAS as your first language. It is easy to learn and holds highest job market share.
• If you are some one who has already spent time in industry, you should try and diversify your expertise be learning a new tool.
• For experts and pros in industry, people should know at least 2 of these. That would add a lot of flexibility for future and open up new opportunities.
• If you are in a start-up / freelancing, R / Python is more useful.

Strategically, corporate setups that require more hands-on assistance and training choose SAS as an option.

Researchers and statisticians choose R as an alternative because it helps in heavy calculations. As they say, R was meant to get the job done and not to ease your computer.

Python has been the obvious choice for startups today due to its lightweight nature and growing community. It is the best choice for deep learning as well.