The Supermarket Sales dataset provides a detailed record of transactions made across three major branches of a retail store. The dataset includes information such as customer demographics, type of products purchased, pricing, quantity, taxes, total sales amount, gross income, and customer ratings. Descriptive analysis helps summarize and interpret these variables so that important trends and behaviors can be understood.

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The data set used in this project is the IBM HR Analytics Employee Attrition & Performance data set from Kaggle. It contains data on 1,470 employees with 35 variables related to demographics, job satisfaction, performance, and work conditions. The main objective is to analyze factors influencing employee attrition and identify patterns that contribute to turnover. This analysis includes data cleaning, visualization, and predictive modeling to help HR teams understand and reduce employee attrition.

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