R is a high-level programming language and a software environment for statistical analysis and reporting. Python is a high-level, general-purpose programming language. So, the key difference between R and Python is that R is a statistical oriented programming language while Python is a general-purpose programming language. R can be used for statistical computing, machine learning, and data analytics. Python can be used for machine learning, web development, networking, scientific computing, and many more.
CONTENTS
1. Overview and Key Difference
2. What is R
3. What is Python
4. Similarities Between R and Python
5. Side by Side Comparison – R vs Python in Tabular Form
6. Summary
What is R?
R is a programming language and a software environment for statistical analysis, reporting for representing graphics. The main advantage of using R is that it can be used to implement statistical concepts such as linear and non-linear modelling, time series analysis, clustering etc.
R is an interpreted language, so each line is read one after the other by the interpreter. It is a high-level programming language. There is a command-line interpreter so the programmer can directly, enter commands in the command line. RStudio is the common Integrated Development Environment (IDE) to make R programming easier. It includes code editor, debugging and visualization tools. There are also packages such as ggplot2 and dplyr that extends the R features further.
While programming, it is necessary to store values. R can store different type of values. It can store logical data types such as true and false. It can also store numeric values, characters, and complex numbers. R has different data structures such as vectors, lists, matrices, arrays, factors and data frames. A vector can be used to store more than one element. A list can contain many different data types of elements like vectors or another list. A matrix can be used to store two-dimensional data set. Arrays are used to store a dataset of any number of dimensions. Factors are the r-objects that are created using a vector. The data frames are used to store tabular data objects. Those are the main data structures in R.
It is possible to read and write into various file formats like csv, excel, xml and JSON using R. It can also be integrated with databases such as MySQL, Oracle, etc. It is a mostly used for statistics, data analytics, and machine learning.
What is Python?
Python is a high-level, general-purpose programming language. It is the cross-platform and open source. It is one of the most popular programming languages for beginners because of its simplicity. The python programs are easy to read, write, test and debug. Similar to R, Python is also an interpreted language. The programmer can directly give commands using the command line or can use an IDE. The most common IDE for Python is PyCharm and Eclipse. They contain the code editor, debugging features, etc. to develop Python applications.
Different data types can be stored using Python. They can be numerical values or strings. Python supports data structures such as lists, tuples, and dictionaries. A list can be used to store multiple data elements of different types. A list is mutable so it can be changed. A tuple is also used to store multiple elements of the same type. A tuple is an immutable Python object. Dictionaries are used to store key, value pairs. Those are the main data structures in Python.
Python can be used to make Graphical User Interfaces and can be integrated with databases such as MySQL, MSSQL, etc. It is useful for a variety of applications. It can be used for machine learning, web development, networking, scientific computing, automation, natural language processing and many more.
What are the Similarities Between R and Python?
- Both are multi-paradigm programming languages. They support Object-Oriented Programming, Imperative programming, Procedural programming etc.
- Both are interpreted languages.
- Both can be used to develop algorithms.
- Both are high-level programming languages.
- Both are the free and open source.
- Both can be integrated with databases such as MySQL, Oracle etc.
- Both support different files such as CSV files, excel files, XML files and JSON files.
- Both languages are easy to use and learn.
What is the Difference Between R and Python?
R vs Python |
|
| R is a programming language and software environment for statistical computing, graphics representation and reporting. | Python is an interpreted high-level programming language for general purpose programming. |
| Developed By | |
| R is supported by the R Foundation for Statistical Computing. | Python is supported by the Python Software Foundation. |
| Data Structures | |
| R supports data structures such as vectors, lists, matrices, arrays, factors and data frames. | Python supports data structure such as lists, dictionaries and tuples. |
| Switch Statement | |
| R supports switch statement. | Python does not support switch statement. |
| Scripts | |
| R scripts end with. R extension. | Python scripts end with .py extension. |
| IDE | |
| The common IDE for R programming is RStudio. | The common IDEs for Python programming are PyCharm and Eclipse. |
| Applications | |
| R can be used for statistical computing, machine learning and data analytics. | Python can be used for multiple applications such as machine learning, web development, networking, scientific computing, automation, natural language processing, etc. |
Summary – R vs Python
R and Python are two programming languages. This article discussed the difference between R and Python. The difference between R and Python is that R is a statistical oriented programming language while Python is a general-purpose programming language.
Reference:
1.“R Overview.” , Tutorials Point, 8 Jan. 2018. Available here
2.“Python Overview.” , Tutorials Point, 5 Oct. 2017. Available here
3.“Python (Programming Language).” Wikipedia, Wikimedia Foundation, 29 Mar. 2018. Available here
4.“R (Programming Language).” Wikipedia, Wikimedia Foundation, 28 Mar. 2018. Available here
Image Courtesy:
1.’R logo’By Hadley Wickham and others at RStudio (CC BY-SA 4.0) via Commons Wikimedia
2.’2024210’by OpenClipart-Vectors (Public Domain) via pixabay