Python or R? The answer in this match in 5 rounds
First of all, it must be understood that no programming language is better than another. However, the fact that Python is more widely used in academia and therefore predominant later in industry is a considerable advantage if you want to train yourself in Data Science and Machine Learning.
Python VS R : 1 - 0
Depending on the field you work in, there are real differences between Python and R that you need to know in order to choose your programming language.
- Machine Learning: it consists of two main steps: the model design and the prediction phase. The first one is done upstream by quite heavy calculations while the predictions are made in real time. Nevertheless, the choice of Python or R for each of these steps does not influence a user’s execution time.
Python VS R : 2 - 1
Python VS R : 3 - 2
Python VS R : 4 - 2
- Speed: Initially, R and Python are two relatively slow languages. The emphasis on ease of programming in Python makes this language necessarily slower than low-level languages like R. In addition, R has recently updated its computationally intensive operating systems making it much faster. To make up for this delay, some Python libraries interface with the C language.
Python VS R : 4 - 3
Visualization: In Data Science, data visualization is essential in order to analyze the results, so it is an important factor in choosing your language. Python is not to be complained in this domain but the R ggplot2 package gives a big advantage over Python and its Matplotlib package for its diversity and ease of use.