Data Management for Retail Dataset using Python and Pandas

Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. This Python course will get you up and running with using Python for data analysis and visualization.
This course has a project that will be based on Data Analytics with Data Exploration Case Study. In this project, we will be using the concepts covered in the course to develop the solution. You will get to learn about various new concepts in this project and will also master the topics that revolve around data analytics.

Panda and NumPy is a library for Python, where NumPy helps by contributing to numerical work lads and computation works. Panda, on the other hand, is preferred for data wrangling and data manipulation-related works. Both the NumPy and Panda constitute Pythons being a scientific language. Its possibility to encounter Matrix and Vector manipulation is possible with NumPy and Panda’s library (rather we call an essential). NumPy means Numerical Python and is an open-source structure for mathematical needs. A must-have array for high-level mathematical functions. Panda, on the other hand, offers similar features in Machine learning and is the most widely-used Python library. It is easy to use, easy to structure, delivers high performance, and is a great data analysis tool.