Firstly, by itself Python is one of the most popular tools for data analysis. With 35% of data scientists using Python. Python originated as an open source scripting language and though not initially used to conduct data analysis. Pandas and other specialized libraries are beginning to change that.

General Purpose Programming

Despite there being other very popular and great computing tools used for analyzing data (e.g. R, SAS), Python is the only true general purpose programming language. The fact that Python is a general purpose programming language means that knowledge of Python can be useful for all types of programming work.

Popular Programming Language

In addition, Python is one the most popular programming languages, when compared with other general purpose languages (e.g. Java, C++, PHP).

Free and open source

Python is totally free of cost and it has open contributions. So, there are chances of errors in latest developments.

Ease of learning

Python is known for its simplicity in the programming world. This remains true for data analysis as well. Documentation is improving.

Employment Scenario

Python is often considered the better option for start-ups and companies looking for cost efficiency.

Some limitations

Since the core language is small and excludes many standard scientific operations, such
duties fall on third party libraries such as Pandas More work is still needed to make Python a first class statistical modeling environment, but it is on its way.

Note: I don’t recommend that you only learn Python and forget about the rest. However, learning Python is one of the best things you can do for your career. 🙂