Python vs R: which is better? We always get this question from everyone. Being a college graduate or a person who wants to switch their career towards data science or data analytics, I always have a question: should I learn Python or R? Which is better for data science? Which one should I learn to get jobs in or excel in my field? This question has been there for ages, and with this post, we will try to help you with what you need to learn to succeed in your field.
Python and R both has its own significance. Python and R both are extensively used in Data Science. Both are useful and open-source languages. R is never going to replace Python and similarly Python is never going to replace R, both languages have their own importance and will be their in the market for many more years.
Topics covered in this Python vs R – Which is better for data science? post –
- Why are where?
- Which is better in Data Science, ML and LLM?
- Disadvantages
- Conclusion – Which is better for you?
Python vs R – Which is better for data science?
Let’s first understand where Python is being used and where R is being used, as well as their real-time use cases and scope. Both of these languages are being used in many big MNCs, and almost every data scientist in this world uses either Python or R. Both R and Python have their own advantages and disadvantages. Let’s first understand why and where these languages are being used.
Python
- Python is widely being used as a programming language across multiple sectors.
- Python is widely used in software development, web development and game development.
- Python is also used in the field of data science, model development, LLM development, Artificial intelligence and also for visualization developments.
- Python has very vast and active user community and you will get lots of articles and help on almost all topics of Python.
- Python has c.3L+ packages available.
- Python is also known for its ecosystem and integration, Jupyter notebook is very famous for python.
R Language
- R is a language built for math and statistics. R is also know as statistic language, if you are some one who is from math/stat background and looking for the career in stat or math then R is the language for you.
- R is very popular in academic areas and research, finance, visualization and data science. R is majorly used in the domains like Healthcare, pharma, BPO etc.
- R is also known for its data visualization capabilities, R shiny is very popular and power to create dashboards or tools. R has many visualization libraries and they are highly customizable and powerful.
- R has c.20k packages available in the Comprehensive R Archive Network (CRAN).
- R’s most popular IDE is R Studio, it is very powerful and you can see your charts parallelly while writing code in the R studio window itself. Also R studio is very useful in creating R shiny dashboards.
R and Python in Machine Learning and LLM
Python has extensive libraries for machine learning and deep learning. Python is widely used for model creation, forecasting, clustering, deep learning etc. Today when we AI is taking over the work and every one is taking about GPT models or LLMs, Python is always better than R for the development of machine learning models, LLMs or GPT models. Python has lots of packages for deep learning and LLMs and the community support we get from Python is awesome and which is very crucial.
Disadvantages of Python and R
Python – Python usually experience week performance on very huge data (big data) but wise use of packages and code optimization can solve this problem up to a limit. Also when it comes to statistics and math, R has an upper edge over python. Also in terms of visualizations R is better than python. We are not saying that python is not good for visualization or reporting, Python also has lost of packages for visualization but R has an upper hand.
R Language – R also has many disadvantages and limited user community and limited packages are the major one. User community of R is not as big as python so help from community may also be not as fast as python. R has limited packages for machine learning, so if you are a person who is looking for machine learning or deep learning R is not the best language. R is computationally slower language compared to Python.
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Conclusion – Python vs R – Which is better?
Choose Python over R, if you are looking for a versatile language that can handle multiple tasks or if your key focus in on machine learning, deep learning, development of LLMs, artificial intelligence or if you want a production grade solution the Python is for you.
Choose R over Python, if you are looking a career on statistics or mathematics and you need specialized statistical tools or you want to become a BI developer or dashboard developer and you need powerful and customable data visualization capabilities.