Which is Best for Data Science: R or Python
Getting to know which languages are best for data science between Python and R has been one of the most difficult things for beginners who want to begin learning and also land a career in data science.
You’ve probably been wondering as to which languages are best for data science; this article aims at making things clear for beginners. By the end of this article, you should be one step away from beginning your career in data science.
Before starting to state the differences for you, lets quickly dive into the overview of the languages.
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991. Python is absolutely one of the most wanted programming languages out there. It became popular due to its simple syntax and its great versatility. It is highly useful with great applications in Automation, Web design, Data Analysis, Machine Learning also Artificial Intelligence, etc.
R was developed by Ross Ihaka and Robert in 1993. It possesses an extensive catalog of statistical and graphical methods. It includes machine learning algorithm, linear regression, time series, statistical inference to name a few
Since we’ve got a good grasp of what the two languages are about, let’s start to tell the differences between the two.
With the calculation of large data set by computers, speed is important in order to achieve the objective of the calculation by making use of a faster language for the creation of the model. Python is faster than R so it takes the lead here.
Learning programming especially for beginners can be a little tasking with each programming language. Some programming languages are generally not suitable for beginners because of many reasons may be their syntax or for some other reason. Python is more good for beginners as it has more understandable syntax than R and it is easy to learn thereby making it more okay for first-timers.
Python has many libraries like matplotlib and seaborn for visualization and the likes of TensorFlow to make data science a lot easier. While R also has many libraries, it doesn’t have as much as python.
Python is a general language mainly used to integrate with other languages, it has been useful for data science by experts in the field. R is mainly created for statistical analysis and data analysis but it has not been famous until now.
We’ve now got the difference part covered, which is best for data science between R and Python is now left for you to decide according to your opinion based on the article above. Python is generally more advisable to be learned by first-timers in programming while if you are an expert, you may go with R. But it isn’t advisable to go with the two. I hope you are on your way to starting to learn data science. If you enjoy this article, kindly share and also make a comment down below as it makes for more great articles like this.