R vs Python for Data Science. The epic battle
If you are a machine learning enthusiast and once understood the fundamentals, the next big question ? to Python or R ?
Both Python and R are popular open source programming languages for statistics. While R’s functionality is developed with statisticians in mind (think of R's strong data visualization capabilities!), Python is often praised for its easy-to-understand syntax and robustness
Python vs R in popularity:
By number of jobs:
Core differences between Python and R:
| Use case | Python | R |
| Objective | Real world production implementations | Data analysis and statistics |
| Target users | Programmers and developers | Scholar and R&D |
| Learning curve | Smooth and linear | Difficult at the beginning |
| Popularity | 21% | 4% |
| Integration | easy integration with apps | Runs locally |
| IDE options | Spyder, Ipthon Notebook | R Studio |
| Efficiency | Python is faster | R Packages are slow |
I personally use python for my machine learning projects. What do you use in your machine learning projects ? Tell us in the comment
nVector
posted on 16 Sep 18Enjoy great content like this and a lot more !
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