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Study Material

R vs. Python vs. SAS

In this section, we compare the three most commonly used programming tools for Data Analysis.

Feature	R	Python	SAS
Cost-Effectiveness	R is open-source software and free to use.	A python is open-source software and free to use.	SAS is commercial software. For most of the professionals, it is expensive and still beyond control
Learning Ease	R is a low-level programming language, but it is very easy to learn and understand due to its simple structure.	Because of its simplicity and usability, Python is very easy to learn and understand.	SAS is one of the world's easiest languages. Anyone can learn SAS without having any programming knowledge.
Data Management	R is capable of handling Big data, structured and unstructured data.	Python is suitable for structured and unstructured data. They are also a compelling language for Big Data analysis.	SAS is also efficient for Structured or unstructured data and Big data analysis.
Graphical Capabilities	R has the highest graphics capabilities due to packages such as Lattice, ggplot, RGIS, etc.	Python gives a fierce competition to R with the help of graphical packages such as VisPy, Matplotlib.	SAS provides functional graphical functionalities. But it is purely functional. We need a thorough understanding of the SAS Graph package to configure it.
Community Support	As R is an open-source language, it has a good community, and they are the best among others.	Similar to R, Python has a very good community, and they are also very active.	SAS provides an excellent technical support experience that is not available for Python and R. It also has a great community.
Application Advancements	Due to the open nature of R, the development of new features and techniques are fast as compared to SAS.	Similar to R, the development of new features and techniques are speedy.	Compared to Python and R, it is less prone to errors, but it usually takes a long-time for a new release.
Deep Learning	R has introduced KerasR and Keras packages. We can effectively generate Deep Models with R.	Python's introduction of TensorFlow and Keras has made significant advances in the area of deep learning.	SAS has recently introduced deep learning, and it is still in the development phase. There is a long road to travel for SAS for deep learning.

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