R vs Python 2023
R and Python are popular options for Data Science, Machine Learning, and Data Analytics.
R is used by scientists, economists, programmers, and mathematicians for machine learning, data mining, data analysis, bioinformatics, and statistics.
R can also be used to develop and build statistical software and web applications. If you are interested in statistical computing, data mining, data analysis, bioinformatics, data science, and machine learning, you should learn R.
On the other hand, Python is a general-purpose programming language that focuses on simplicity and readability.
Rather than building all of its functionality into its core, Python was designed to be highly extensible through modules.
Python is commonly used for web development, GUI development, system administration, software development, automation, testing tools, machine learning, and data science.
If you are interested in working on web development, machine learning, automation tools, and data science, you should learn Python.
Comparing programming languages and choosing which one to learn or use for your next project can be tricky, there are many factors to consider in order to choose the right programming language for the job you want to do.
Popularity, opportunities, type of projects, salaries, resources, learning curve, etc. are some of the factors that many people consider when comparing programming languages and choosing which one to learn or use.
Here are some of the comparisons and considerations you should make when choosing to learn a new programming language.
R VS PYTHON POPULARITY
Comparing the popularity of programming languages is not an easy task because each programming language is different.
Although the usage of many programming languages may intersect, different fields and projects may require the use of different programming languages.
Plus, other programming languages have been around for a longer time than others, giving them more time to be tried and tested, so, bear that in mind.
If you want to learn a programming language or framework solely for its popularity among developers, you should learn Python over R.
Generally, Python is more popular than R. According to a Stack Overflow survey of 2022, Python is the 4th most commonly used programming language, it is used by 43.51% of professional developers.
On the other hand, R is the 22nd most commonly used programming language, it is used by 3.56% of professional developers according to the same survey.
Python is also loved by many developers compared to R. Python is loved by 67.34% of developers versus 32.66% of developers who dreaded it.
On the other hand, R is loved by 41.60% of developers vs 58.40% of developers who dreaded it.
Further, The TIOBE index 2023 ranks Python as the number one most popular programming language where as R is ranked 16th.
Ultimately, if your choice of which programming language to learn depends on popularity, you should learn Python.
R VS PYTHON SALARIES
Another popular criterion that many people use to compare programming languages and as an incentive to learn a new programming language is salary.
Salaries for developers differ from one company to the other and from one country to the other.
Experience is another factor that comes into play as far as salaries are concerned. The more experience you have with a certain technology or programming language, the more likely you are of getting a higher salary.
Generally, Python developers get higher salaries than R developers. Glassdoor reported that in the United States, Python developers with 1 – 3 years of experience get an average salary of $102,196 per year.
On the other hand, R developers with 1 -3 years of experience get an average salary of $75,851 per year, about $26,000 less than Python developers.
It is worth noting that senior data scientists using R can get salaries of more than $150,000 per year.
Further, according to a Stack Overflow survey of top-paying programming languages, Python developers get an average salary of $71,105 per year.
On the other hand, R developers get an average salary of $67,734 per year, about $3,000 less than Python developers.
So, if the salary is your major incentive for learning a language or framework, you should learn Python over R, because you are more likely to get a higher salary as a Python developer than as an R developer.
Here are some of the popular jobs you can get as a Python Developer.
R VS PYTHON WHICH ONE IS EASIER
Some programming languages can be learned more easily than others. Generally, Python is easier and more beginner-friendly than R.
Python has an English-like, easy-to-understand syntax that makes it very easy to write code. It is also easy to maintain and debug Python code because it is more readable.
Getting started with Python is much easier than with R. Python is also a general-purpose language, which means it can be used for a wide range of applications beyond data science.
On the other hand, R is more specialized for data science and has a steeper learning curve. However, R’s syntax is more consistent, and its libraries are more consistent in their design and functionality.
The good news is that there are plenty of helpful resources for both Python and R to help you learn the languages.
The Python and R communities are very active and helpful, in case you get stuck with something.
FEATURES AND APPLICATIONS
Python has a large standard library that provides tools and features suited for many applications. It supports many standard protocols and formats like HTTP, MIME, and many others.
It also includes modules that can be used for relational database connection, unit testing, and manipulation of regular expressions.
Python has many amazing features, libraries, and packages that make it a popular choice for web development, scientific and numeric applications, system administration, GUI development, and more.
Python powers some of the complex applications developed by companies like Google, NASA, IBM, Microsoft, Meta, Cisco, Duolingo, Pinterest, Reddit, Pixar, Netflix, and many others.
On the other hand, R is heavily used in statistics and building machine learning models because of its flexibility.
Another strength of R is static graphics; it can produce publication-quality graphs that include mathematical symbols.
R and its libraries are used to implement various techniques such as linear, generalized linear, and nonlinear modeling, classical statistical tests, plotting, data processing, spatial and time-series analysis, classification, clustering, etc.
R is used by companies such as Amazon, Google, Flipkart, Firefox, LinkedIn, ANZ, Accenture, Infosys, BOA, HCL Technologies, Cognizant, American Express, Barclays Bank, and many others.
R VS PYTHON MACHINE LEARNING
Python has a strong advantage in machine learning due to its extensive libraries, such as PyTorch, Scikit-learn, TensorFlow, SciPy, Keras, and many others.
These libraries are widely used for developing complex machine learning models, such as neural networks, decision trees, and support vector machines
These Python libraries make it easy to develop machine learning models and provide excellent performance. Python’s syntax is also more straightforward than R’s, making it easier for beginners to learn.
However, R has a growing collection of machine learning packages, such as CARET and MLR, that provide a streamlined approach to machine learning.
These packages make it easy to create models and evaluate their performance.
R has some advantages in the field of statistics. It has an extensive collection of statistical libraries, such as ggplot2, dplyr, and tidyr, which are specifically designed for data analysis and visualization.
R VS PYTHON FOR DATA ANALYSIS
R has been the go-to language for statistical analysis and data visualization for many years. It has a vast collection of packages that are specifically designed for data analysis, such as ggplot2, dplyr, and tidyr.
These packages provide an easy-to-use syntax for data wrangling and visualization, making R an excellent tool for exploratory data analysis.
R is also great for working with large datasets and performing complex analyses.
In contrast, Python is more versatile and can be used for a wide range of applications. It has a lot of libraries for data analysis, such as Pandas, Matplotlib, and NumPy, which are easy to use and provide excellent performance.
SHOULD I LEARN R OR PYTHON
Once you have compared the languages and evaluated all the factors, you can choose which programming language to learn or use depending on the factors that are on your side and what you want to build.
If you are interested in statistical computing, data mining, data analysis, bioinformatics, data science, and machine learning, you should learn R.
If you want a popular language that you can learn easily, develop applications quickly, and work on machine learning, data science, automation tools, and web applications, you should learn Python over R.
