Welcome to the Sales Data Analysis Repository! This repository contains SQL queries and their Python pandas equivalents to analyze various aspects of sales data using the pandas library. The repository covers a wide range of analyses, utilizing tables such as customers, employees, order_details, orders, shippers, products, and more.
This repository serves as a resource for data analysts, developers, and anyone interested in exploring and analyzing sales data. The provided SQL queries and their corresponding Python pandas code showcase how to extract insights from sales-related databases.
The repository includes SQL queries and their equivalent Python pandas code for various analyses, utilizing tables such as:
- customers: Contains customer information.
- employees: Stores employee data and roles.
- order_details: Holds details of products within orders.
- orders: Contains order information and timestamps.
- shippers: Stores shipping company data.
- products: Contains product details and prices.
The analyses cover a wide range of topics, such as calculating sales metrics per product, category, and customer; identifying frequently used discounts and shipping services; analyzing customer behavior and employee distribution; assessing order processing time and delivery performance; investigating product pricing and order revenues.
Each query answers specific business questions related to sales data, helping you gain insights into customer preferences, product performance, and operational efficiency.