Data Management for Retail Dataset using Python and Pandas

Develop the data management based solution | Data Management for Retail Dataset using Python and Pandas.

What you’ll learn

Data Management for Retail Dataset using Python and Pandas

You will get to learn about the approach that is used to develop the data management-based solution. To complete the projects, you will be working using python and all the libraries that we got covered in this training.
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

Requirements for Data Management for Retail Dataset.

Basic understanding of Computer Programming terminologies.
A basic understanding of any of the programming languages is a plus.
Basic knowledge of Python and Mathematics
No prior information for machine learning is needed.

Description for Data Management for Retail Dataset.

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.

Who Data Management for Retail Dataset course is for:

Anyone who wants to learn the basics and various functions of Pandas.
Data Engineers, Architects, Analysts, Software Engineers, IT operations, Technical Managers, Data Scientists
Last updated 7/2021

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