Python is an open-source programming language. Not only for data science tasks, but Python can also be used for web development and software development. It has an abundance of packages and libraries that can be used in various fields like data-transformation, data-filtering, data-wrangling, machine learning, predictive analysis, etc.
R programming is an open-source scripting language for statistical computation and mainly used by statisticians for performing complex mathematical and statistical calculations on data and data visualization. Due to its open-source nature, R has a huge and active community. The number of packages in R has increased and made it easy for performing all data science tasks.
SAS is a proprietary software tool that is used for statistical analytics. SAS is very expensive. So, only huge corporations use it, but not suitable for individuals and small organizations. SAS is suitable for performing complex statistical operations but not good for performing data visualization, advanced analytics, and machine learning models.
Also, watch this video on Python vs R vs SAS:
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