ABSTRACT
Python started up as a hobby programming project. Python's emphasis on code readability and expressive syntax has made it into a general-purpose, high-level, object-oriented programming language available in multiple platforms and with a plethora of supporting packages and modules. The support that Python has for hierarchical modularity makes it possible for programmers and developers to build further functionality. It is true that Python is an interpreted language and as such code may be often slower than compiled code tailored to a particular machine architecture. Python code is flexible and portable. It is fast enough for the typical data science workflow. The iPython/Jupyter notebook supports the inclusion of text, mathematical expression and inline graphics as well as other rich media such as websites, images, video, maths, etc. NumPy extends the types supported by Python with the definition of arrays to describe a collection of objects of the same type.
