You must have seen a lot of people in the data science community using Python often and promoting the use of Python for data science. So is it just their biases with Python or it is best for Data Science? Most of the developers are biased with the programming language they like. But undoubtedly, Python is the best programming language for Data Science. So if you want to know why, this article is for you. In this article, I will take you through some of the reasons why Python is best for Data Science.
Here’s Why Python is Best for Data Science
Python is Easy
Python is one of the easiest programming languages. If Python is your first programming language, once you have gone through the fundamentals of Python, you will find it easy. If you are learning Python after languages like C++ or Java, you will find Python so easy that you can master it in just a month.
There is a lot to learn in Data Science, so using an easy programming language like Python will help you focus more on problem-solving and learning all the necessary data science concepts, tools, and algorithms.
Python Libraries and Frameworks
Because of the popularity of Python, it has a vast collection of libraries and frameworks for solving every problem. Python has a very useful collection of data science libraries and frameworks used by students and professionals.
It has so many libraries and frameworks that you can use different Python libraries in each step of a data science task. Tensorflow, Scikit-learn, NumPy, Pandas, Matplotlib, and Plotly are some popular Python libraries and frameworks for data science.
Huge Community of Python
The vast community of Python ensures that Python is not going anywhere from the industry. If you go through the skills required in any job description of Data Science, you will always find Python mandatory.
As there is a vast community of Python, it also helps beginners learn everything for free, as there are millions of free resources on the internet to learn Python.