Python provides a huge number of libraries to work on Big Data. You can also work in terms of developing code using Python for Big Data much faster than any other programming language. These two aspects are enabling developers worldwide to embrace Python as the language of choice for Big Data projects.

It is extremely easy to handle any data type in python. Let us establish this with a simple example. You can see from the snapshot below that the data type of 'a' is string and the data type of 'b' is integer. The good news is that you need not worry about handling the data type. Python has already taken care of it.

The day-to-day tasks of a data scientist involves many interrelated but different activities such as accessing and manipulating data, computing statistics and creating visual reports around that data. The tasks also include building predictive and explanatory models, evaluating these models on additional data, integrating models into production systems, among others. Python has a diverse range of open source libraries for just about everything that a Data Scientist does on an average day.