Python Frameworks for Data Science

Python is increasingly becoming the language of choice for technical applications such as Data Science and Machine Learning. Among its other desirable properties, its libraries have played a part in making work easier for many professionals whose jobs rely on numerical analysis and data manipulation. In this guide, I will provide you with brief descriptions of some of the most commonly used Python frameworks for data science and machine learning including their common uses to give you a rough picture of what they entail. I also hope it opens your eyes and makes your life easier if you are having trouble with your project: NumPy It is a Python library that handles most of the numerical computing done using Python. It provides support for multi-dimensional arrays and matrices and comes with an impressive collection of routines to operate the arrays. The ndarray object that deals with an n-dimensional array is the core functionality of NumPy.