Last Updated on November 30, 2020
Data science is the field of exploring, manipulating, and analyzing data and using data to answer questions or make recommendations. It is changing the way we work, use data, and our approach to the world. Before learning data science, people often confused about which programming language should they learn? – Python vs R. However, Python is a very popular language for the last five years. Most programmers shifted to python from other languages because of its uses in various fields and easy to code. But since last year, a programming language R spread in the market rapidly. Data analysts, Statisticians prefer R. Here I will explain to you the difference between Python vs R.
R is an open-source programming language developed by R Foundation for statistical computing. It has become the world’s largest repository of statistical knowledge. Its purpose is to focus on performing data analysis and statistics in a better way. It is most often used by statisticians, mathematicians, and data miners for developing statistical software, graphing, and data analysis. R integrates well with other computer languages like C++, Java, C, .NET, and Python. It provides every library to perform analysis. It is memory safe language. In C and C++, there is a chance of memory corruption or bugs caused by the developer. But R is precise even with minor details or bugs. More than 15000 packages released publicly which makes it possible to conduct complex exploratory data analysis. Check out the link for R documentation and packages.
Many giant companies like IBM, Google, Facebook, Microsoft, Bank of America, Ford, Tech Crunch, Uber etc. use R language . It becomes the first choice for data analysts. If you are looking for data analysis jobs, R is the best choice for you.
Python is the most popular, general-purpose programming language suitable for tasks in machine learning. It is always known for its easy to understand syntax. Python was created by Guido van Rossum and released in 1991. It emphasizes productivity and code readability. It can do the same task as R. Python is a tool to deploy and implement machine learning on a large scale. Earlier Python didn’t have libraries for data analysis and machine learning. But now most of the data scientists are working on projects using these python libraries like Numpy(for multi-dimensional array), Scipy(for image manipulation), Scikit-learn(for data-mining & data analysis), Pandas(for data analysis), Matplotlib(for 2d plotting). Its accessibility is easier than R.
In 2019, Glassdoor reported that more than 75% of data science positions listed included Python in their job description. Python is one of the three official languages of Google. The other two programming languages are Java and C++.
Giant Companies that use Python:-
- Facebook etc.
Which programming language should I learn?
However, Python, R, and SQL are the preferable languages for data science. It depends upon your needs, the problems you are trying to solve, and who you are solving them for. It also depends on what company you work for, what role you have, and the age of your existing application.
I hope you liked this article. If you have any questions please let me know in the comment section.