Python - A Snake or a Ladder ?

Let me start with something like this :
"If you want to survive in analytics then you need to hunt Python".
Don't be afraid. Learning Python is not as difficult as hunting one. But, it needs considerable effort to be a master in Python.

Python is a high level,interpreted,interactive and object oriented language.Python is most familiar and commonly used programming language in the field of  analytics. What makes Python different from other languages is it is open source. Anyone can just download Python and can start learning it. Moreover,Python is a dynamic and strongly typed programming language that is designed to emphasize usability. To download Python please click here.

Features of Python :

- As Python is an interpreted language , it does not have compiler to pre-proccess the instructions as the instructions are processed at run time.

- Supports Functional,Procedural as well as Object Oriented Programming technique.

- Easily Integrated with C, C++ , COM, Active X, Java.

- Automatic garbage collection.

- High level dynamic data types.

- Can be used as scripting language or can be compiled to byte code for building large applications.


Before starting with Python, let us first know why Python is preferred for data analytics over other languages such as C#, Java, C++, etc. .

Every sector of business is being transformed by the modern deluge of data. This spells doom for some, and creates massive opportunity for others. Those who thrive in this environment will do so only by quickly converting data into meaningful business insights and competitive advantage. Business analysts and data scientists need to wield agile tools, instead of being enslaved by legacy information architectures.

Python is easy for analysts to learn and use, but powerful enough to tackle even the most difficult problems in virtually any domain. It integrates well with existing IT infrastructure, and is very platform independent. Among modern languages, its agility and the productivity of Python-based solutions is legendary. Companies of all sizes and in all areas - from the biggest investment banks to the smallest social/mobile web app startups - are using Python to run their business and manage their data.