As we all know we all live in a digital era and it is mainly dominated by software. Have you ever thought about how these softwares are built? Yes, it is very much clear that all these software are built with the help of different programming languages. In this module let us compare three programming languages “ R, Python, and SAS” and let us find out which language is best among these three for studying data science. All languages have their own pros and cons. So now let us compare the languages R, Python, and SAS based on the cost, difficulty in studying, capabilities in data handling, capabilities in graphics, what are advanced tools, and job scenarios, let us find out in which fields these languages are frequently used and support is given for customers. Apart from that in this module, we will also discuss the applications of Python, R, and SAS.
When we are comparing R, python, and SAS it is understood that SAS is a kind of commercial software. SAS is very expensive compared to R and python. Because of its cost, this cant is used by an individual whereas some private organizations hold the highest market share by investing in SAS. So if you are a part of such organizations it will be very easy to access or else it is very difficult. R and python are not expensive which means they are completely free.
Language | COST |
---|---|
Python | Low |
R | Low |
SAS | High |
SAS is very easy to learn compared to Python and R. On many websites, so many tutorials are available which are provided by different universities. Comprehensive documentation is available for SAS. R is a kind of low-level language because of that itself even for simple procedures longer codes are needed. Learning code is very important. Learning python is easy when it is compared with R and difficult when it is compared with SAS.
Language | Difficulty in learning |
---|---|
Python | Very easy compared to python and R |
R | Very difficult compared to SAS and Python |
SAS | Very easy compared to R and it is difficult when it is compared with SAS |
R, Python, and SAS are very good at handling data. Now we all have advanced versions of these languages and when we are comparing these languages based on their data handling capabilities all 3 languages have the same capabilities for handling data.
Python and R is having very high graphical capabilities compared to SAS. The graphical packages in SAS is very difficult to understand as well as less graphical capabilities compared to R and Python.
Language | Difficulty in learning |
---|---|
SAS | SAS is mainly used by big organizations. Small companies never use SAS because of its cost. It is very expensive and start-up companies cant afford it. |
R and Python | These two languages are mainly used by small and start-up companies |
Language | Difficulty in learning |
---|---|
SAS | SAS is having less advanced tools compared to R and Python. |
R and Python | R and Python is having more advanced tools compared to SAS |
The programming languages which are mainly used for data science are Python, JavaScript, SAS, Scala, R, and SQL. All these languages are good for data science still among this python is the best programming language for data science. Among all these languages more scalable is python which means python is more flexible for the programs not only that it contains many varieties of libraries that are very suitable for data science.
Main reasons why python is considered the best programming language for data science.