Python and R are both popular languages in the programming industry. They can help you with daily data analysis tasks and perform difficult tasks and challenges. Furthermore, both languages also help you with statistical tasks. However, you should keep some differences in mind before choosing the language. For instance, programmers popularly use Python due to its easy and understandable syntax. However, others use R because it has advanced functions for statistical minds. Today, we will discuss both programming languages and evaluate the differences.
What is R
R is a GNU project and is an environmental language that helps in graphical representation and statistical computation. You can consider R as a different application of S. Even though there are some differences in both. Still, developers use various codes in S that also run under R without alteration.
With R, you can perform various statistical tasks such as classical statistical tests, nonlinear and linear modeling, classification, analysis, and clustering of time-series, and much more. Moreover, S also has a wide collection of graphical techniques. The route of all these activities is Open Source in R.
What is Python
It doesn’t matter if a professional belongs to the programming industry or not; if they know the basics about languages, they may know of the python language. This is an interpreted language and a popular and modern choice for application and software development. But why do so many developers use python language? The first reason is that this is a modular language. That means you can easily integrate this language with other solutions and technologies. Secondly, this is an open-source language. It means that the community of developers can contribute to this language. Many developers are a part of this community, and Python Software Foundation has complete control over the language’s quality.
Another reason for the popularity of this language is that it is interpreted. This language was already transferred to machine code before developers launched this language. That is why you can write this language on universal and portable programs and use it on any operating system.
Now let’s understand each language’s benefits in detail and understand why each language is better than the other.
Benefits of R
1. Open Source
You can easily use this programming language with minimum or no fee because it is an open-source language. This means that anyone can use the source code and make changes to the program. This helps in increasing the quality of the problem resolving feature of this language.
2. Wide Range of Packages
R has a huge variety of packages that you can use for your solutions. The number of R packages is consistently growing. R has more than 10,000 packages only in the CRAN repository. Almost every industry can use these packages.
3. High Compatibility
You can pair this language with many different programming languages such as Python, Java, C, or C++. This makes this language highly compatible. You can also integrate R with database management software such as Hadoop.
4. High Graph and Plotting Quality
R also helps in graphing and plotting. To bring visual appeal and attraction, you can integrate plotty and ggplot2. This makes this language different than other programming languages.
5. Mind-Blowing Reports
You can easily create easy and extensive results while reporting. R supports packages such as Markdown and Shiny. R also includes scripts, plots, and data that will help you make reports through embedding. With R, you can create an interactive application, and your users can play with the data and the result on the web.
6. Machine Learning Supportive
You can also perform machine learning activities with the R programming language. For instance, this language can perform regression and classification of the data through an artificial neural network.
7. Constant Growth
This language is currently growing drastically. One of the reasons for the growth of this program is that it is open-source. This language uses state of the art technology and provides instant updates whenever this language adds new features.
Benefits of Python
1. Improved Productivity
This language is very productive and allows you to solve complicated problems. Not only that, this language is very simple. You do not have to spend months to understand the behavior and syntax of the language. You can perform more tasks by writing fewer codes with Python language.
2. Interpreted Language
Python has the ability to execute every code line by line. This means that Python is an interpreted language. If this language finds any error, it stops right away and reports back. So you do not have to look for errors. You can easily debug as this language only shows a single error. Even if there are multiple errors, you will only receive one error.
3. Easy to Learn, Read, and Write
You can easily understand and read the coding in this programming language because it has a high language quality. The syntax is similar to English, which allows you to learn it even faster. Many people use Python because they easily understand the language. Furthermore, there are fewer lines with similar code as Java and C++ making it easier.
4. Open Source and Free
Just like the R programming language, Python is also an open-source language and approved by OSI. You can freely use and distribute this language. The best part is you can download, modify, and distribute the python versions as your own modifications.
Python has a unique benefit. You can use the same codes for multiple platforms. This means that you do not have to write different coding for different platforms. This saves a lot of time and effort.
6. Huge Libraries
Python has an extensive quantity of libraries; this makes it perfect for performing various tasks. That makes you less dependent on external libraries.
It is challenging to find the best programming language in R VS Python. When Python is a versatile and simple language, R is a highly compatible and statistical language. In the end, it is up to your choice of what you want to do. However, Python is more popular than the R programming language, but it depends on your personal preferences.