Data quality is a broad concept with multiple dimensions. I detail that information in another introductory article. This tutorial explores a real-life example. We identify what we want to improve, create the code to achieve our goals, and wrap up with some comments about things that can happen in real-life situations. To follow along, you need a basic understanding of Python.
Python Data Analysis Library (pandas) is an open-source, BSD-licensed library that provides high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
You can install pandas by entering this code in a command line: python3 -m pip install — upgrade pandas.
