Python VS R: What Are The Key Differences Between These Two Languages?

Both R and Python are languages ​​used in the fields of data analysis and statistical analysis. However, both are different programming languages ​​, and each has different strengths. It is generally said that the R language is suitable for data science, and Python is suitable for machine learning and application development.

A recent survey shows that 57% of data scientists used Python, while only 17% used R. According to the 2021 GitHub Octoverse Report, Python is the 3rd most popular language and R is the 15th most popular language on GitHub in terms of the number of pull requests.

Many people have different opinions about whether to use R or Python for data analysis. Although the number of Python users has increased recently, it is also true that there are more than a few people who use R as their main language.

Increasingly, the question is not which one to choose but how to make the best use of both programming languages ​​for your specific use cases. Python and R are the most popular and convenient programming languages ​​in the field of data analysis. In this blog, you will look at the differences between R and Python and explain how they fit into data analysis and statistics.

What Is The R Language?

Developed at the University of Auckland in 1995 and open-sourced in 2000, it has been used mainly for research in academic institutions and R&D departments.

For example, “vector processing,” which is one of the features of the R language, demonstrates strengths that general-purpose programming languages ​​do not have, such as inputting complex data groups as they are into variables and applying them to nests. Libraries are also available for statistical analysis.

Furthermore, the R language is also strong in visualization, and you can display a line graph simply by entering arbitrary values ​​for the vertical and horizontal axes. Reporting can also be done efficiently by using “R Markdown,” so it is a very useful language when summarizing statistical analysis results in an intuitive and easy-to-understand form.

Data compatibility is also high, and data used in external tools such as CSV and text can be read without problems using standard functions.

By the way, application development is also possible in the R language by using a library called “Shiny.” It’s a little different from the original usage, but remember that you can also use it like a general-purpose programming language.

In recent years, it has been pushed by emerging languages ​​such as Python, but in terms of “manipulating numbers, investigating causes, and visualizing for an explanation,” it can be said that it is a very strong language even as of 2021.

What Is Python?

Next, let’s take a look at the overview and features of Python.

“Python” with high versatility for data analysis and implementation

Python is an object-oriented programming language developed in 1991 by Dutchman Guido van Rossum. The syntax is simple, the amount of description is small, and it can perform a lot of processing with the minimum description. AGS’s Dedicated Python Developer for hire deploys the latest technologies and delivers exceptional solutions to get the most out of leading web and mobile technologies

In addition, one of the features is that many libraries, both standard and external, make it easy to implement various functions. In recent years, it has become the de facto standard in machine learning-related development and boasts a popularity unmatched by other languages.

Libraries and development environments have been enhanced in recent years

Also, compared to the R language, Python is highly evaluated as “anyone who uses it.” For example, even an IT engineer who does not have specialized knowledge of statistical analysis or data science can implement advanced calculation processing with knowledge of the library.

In particular, there seems to be a view that development costs related to machine learning have decreased due to the increase in libraries that support machine learning, which is indispensable for artificial intelligence development.

Want to know more about Python? Do you have a project in mind? Hire Dedicated Python Developers at AGS to accompany you and help you in the success of your project.

Differences Between R Language And Python

These two languages ​​have strengths in data analysis and statistical analysis, but what are the differences? Here, we will compare the R language and Python in terms of “purpose,” “versatility,” “processing speed,” and “ease of programming.”

1. Purpose

The biggest difference between the two programming languages ​​is their purpose. The R language is a language for “explaining” through statistical processing. On the other hand, Python can be said to be a language that often makes “predictions” from various data.

For example, in the R language, you can easily visualize by writing the “Plot method.” Python, on the other hand, has to import an external library to do the visualization. Ultimately, both can do the same thing, but the R language is smoother and easier to “explain.”

On the other hand, when making “predictions” while making effective use of data accumulated within a company, such as product sales and campaign results, Python is the winner. This is not only because of the abundance of libraries for machine learning but also because the latest prediction methods are often implemented in Python. Currently, it is no exaggeration to say that the “machine learning trend = Python trend” and prediction by machine learning is the biggest purpose of using Python.

2. Versatility

In terms of versatility, Python comes out on top. Python is a general-purpose scripting language that can be used for statistical analysis, machine learning, and application development.

3. Processing Speed

Python also has an advantage in terms of processing speed. It’s difficult to make a simple comparison, but in the case of similar processing, it can be as fast as 15 to 6 times faster than the R language.

4. Ease Of Programming

When compared in terms of ease of programming, Python seems to be winning. Although the R language has a reputation for being relatively easy to handle, it may be slightly inferior to Python, which is made as a general-purpose scripting language.

Python is a language that is widely used not only for statistical analysis but also for general application development. In addition, Python is overwhelmingly easier to use when it is embedded in a business system, such as “batch processing a certain process and executing it periodically.” Furthermore, the fact that the R language tends to consume more memory than Python may also lead to Python’s superiority.

Python VS. R: Which Is Better?

Both languages have their strengths and weaknesses. Which of them is suitable? It all depends on your task. Here are some questions, the answer to which will help you make the right choice:

Have you ever programmed in other languages? In that case, R can get used to it. Python is more familiar, except for some nuances.

Do you plan to work in the scientific field, or do you tend to be more educated? As python is closer to production, it is used more often in commercial projects. At the same time, the R language is more popular in research and academic circles.

Do you want to expand your horizons in machine learning technologies? Or is it enough to familiarize yourself with some of the most popular approaches and spend more time on algorithms for processing big data? For example, in the first case, R is absolutely necessary, but you can find more functionality in Python in the second case.

Do you want to implement the development and programming of something other than forecasters? If so, Python would be a better choice, but you might want something else (Java, Scala, C++, etc.) that is more advanced.

Why Choose AGS?

If Python allows you to create web applications in a professional way, it is recommended to entrust your project to an expert such as the AGS agency. Because each project is unique, we place users at the heart of our methodology. By using our Python Software Development Company, you will benefit from real expertise to develop a high-performance, scalable, and high-added-value digital product.

At AGS, we have a team of skilled Python developers with years of experience in the industry. Our Python experts combine creativity and experience to deliver exceptional python solutions that promote rapid development and clean, pragmatic design. AGS’s proficient Python Development Services Provider has extensive experience in developing products according to business needs and is dedicated to providing the best service.

Conclusion

R is a high-level programming language meant for statistical analysis and reporting, especially in research and academic circles. On the other hand, as Python is a stable language, it helps design high-performance applications in a short time. It can be used in particular for the management of important traffic and video proposal algorithms. It is also suitable for storing and sharing files on platforms, etc.

If you are looking for experienced, reliable, and qualified python developers to reduce your operational costs on time without compromising on quality, you have found it. AGS offers customized and cost-effective Python solutions that are extremely flexible, reliable, and scalable.