One of the biggest questions in the data analyst / science community is: Should I use Python or R? Well let’s hit on some of the reasons why R maybe a better language than Python. FYI, I will be making the same article on why Python is better than R which will be linked here if you want to read it! Let’s get started!
Arguably better graphs / outputs
R has a ton of functionality within it, and one of the best thing about R are the graphs / visuals you can create with this language! First off, Python has a lot of functionality with outputs, but R does some crazy outputs for sure:
Great for statistical analysis
Since R is a statistical programming language, any type of statistical computations your going to create will end up being more efficient using R. In my experience, data processing maybe overall better using R, but if your doing a lot of Machine Learning tasks, Python maybe better. But ultimately, the packages that R has (dplyr, tidyverse, etc.) maybe better than Python’s offering (Pandas).
IDE Is great for Data processing
One of my favorite things about R is the IDE. R Studio is such a beautiful IDE that allows so much functionality for data processing. First off, the variable explorer is amazing, being able to see the variables, data sets, etc. from your project helps out so much during project creation. Some Python IDE’s have it (Spyder and Pycharm) but since R is mainly used for statistical projects anyways, it allows for a better environment for someone who is creating a project related to any type of data processing.
Data processing maybe faster
Another big advantage for R is the speed of data processing. Depending on what packages you are using / the amount of data, it maybe beneficial to use a language like R to process the data vs Python. As stated before, since R is a statistical language, it puts focus on data related tasks, which ultimately help speed up different portions when handling your data sets.
So those are some of my favorite reasons to use R over Python, but I would HIGHLY recommend learning both languages!