Introduction to Pandas, NumPy and RegEx in Python

Python has literally 100s of libraries that make a Data Scientist’s life easier. It can be overwhelming for a beginner to think about learning all of these.

Pandas

Unlike the obvious hunch, Pandas stands for ‘Panel Data’ and not a cute round animal. Widely used for handling data with multiple attributes, Pandas provides extremely handy commands to handle such data smoothly. Let’s move on to the coding exercises to get friendly with Pandas.

NumPy

NumPy is a powerful package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

RegEx

A regular expression is a special text string for describing a search pattern. For example, we can define a special string to find all the uppercase characters in a text. Or we can define a special string that checks the presence of any punctuation in a text.

Read more about the Python Libraries with example in the given link below:

https://dimensionless.in/complete-tutorial-learn-data-science-in-python/