How Companies Use Exploratory Data Analysis On Dataset To Boost Their Supermarket Sales?
Supermarket Shopping has become a routine nowadays. The wide range of the items available, low pricing, and ease of shopping will result in a large flow of customers and so there will be a significant increase in the sales income. The sales and location dataset of a supermarkets is analyzed in this blog, which spans the years 2017 through 2020. The aim is to determine the company’s strengths and weaknesses, maximize profits, loss reduction, and make future recommendations. This is a comprehensive capstone project that necessitates a working grasp of Python as well as basic statistical principles. This project’s environment comprises of: IDE- JupyterLab File Type- XLS Exploratory Data Analysis Let’s take a closer look at the information in data frame. From the above dataset we can analyze that: 21 Columns 9994 rows/ entries All are Null- values excluding Postal codes Single entry for ‘Country’ Filtering Data Deleting Unnecessary Columns Postal code • Country • R...