Differences between Python and R !

Brief Overview of Python programming language

Python is a popular programming language that's used for many purposes, including web development, software development, data science, and machine learning. Here are some things to know about Python: 

 

Ease of use

Python is easy to learn and has a simple structure, making it developer-friendly. It has a few keywords and clearly defined syntax. 

 

Platform independence

Python runs on many different platforms and integrates well with all types of systems. 

 

Free to download

Python software is free to download. 

 

History

Python was created by Guido van Rossum and first released in 1991. The name "Python" is a reference to the British comedy group Monty Python. 

 

Uses

Python has been used to create Netflix's recommendation algorithm and the software that controls self-driving cars. 

 

Installation

Python is easy to install, and many Linux and UNIX distributions already include it. Some Windows computers also come with Python pre-installed. 

 

Debugging

Python has a source level debugger that allows you to inspect variables, evaluate expressions, set breakpoints, and step through code. You can also add print statements to the source to debug a program. 

Brief Overview of R programming language 

R is a free, open-source programming language and environment for statistical computing and graphics: 

 

Features: R is a comprehensive programming language that supports procedural and object-oriented programming. It can handle complex operations with vectors, arrays, and data frames. R also provides a wide variety of statistical techniques, including linear and non-linear modeling, time-series analysis, and classification. 

 

Uses: R is used by machine learning professionals, database administrators, geo statisticians, financial analysts, machine learning scientists, quantitative analysts, and statisticians. 

 

Development: R was developed in 1993 by Ross Ihaka and Robert Gentleman. It's similar to the S language and environment, which was developed at Bell Laboratories. 

 

Compatibility: R is available for Windows, Linux, Mac OS X, and other UNIX platforms. 

 

Integration: R can be easily integrated with many other technologies and frameworks like Hadoop and Spark. 

 

IDE: R is usually run in an integrated development environment (IDE) such as RStudio. 

 

Code: R can be coded at the command line or using scripts. 

 

Python and R  : Which is best?

Python and R are both programming languages that can be used for data analysis, but they have different strengths and are best suited for different purposes: 

 

Python

A general-purpose language that's good for a wide range of tasks, including data science, machine learning, and artificial intelligence. Python is also used for web development and scripting. Python is faster than R, which makes it better for production, building pipelines, and large-scale production. 

 

R

A language that's primarily designed for statistical computing and graphics. R is good for data analysis, hypothesis testing, regression modeling, and data visualization. R is popular among researchers and scientists. 

Differences between Python and R: 

 

Here are some other differences between Python and R: 

Python and R are both programming languages with different strengths and uses, but they can be complementary to each other. Here are some ways Python and R differ: 

 

Purpose

Python is a general-purpose language that can be used for a wide range of tasks, while R is primarily a statistical programming language. 

 

Data handling

R is known for its efficient data handling capabilities, including data cleaning and preprocessing. Python is more versatile and can collect data from a variety of formats. 

 

Data visualization

R is ideal for visualizing data in graphics, while Python has libraries that can be used for data visualization. 

 

Machine learning

Python is a better choice for machine learning, especially for data analysis in web applications. 

 

Coding conventions

R uses curly braces and parentheses, while Python uses indentation and columns. 

 

IDEs

Python uses IDEs such as Spyder, Eclipse+Pydev, and Atom, while R uses IDEs such as Rstudio, RKward, and R commander. 

 

Community

R has a robust community that's focused on analysis. 

 

Some say that knowing both Python and R can make you a more flexible job candidate in the data science world.