Project 1 - Data Manipulation of E-commerce Platform Using MySQL
The project focuses on analyzing a dataset of users in an e-commerce platform that uses a customer-to-customer (C2C) business model. The dataset is stored in a .csv file with 98913 rows and 24 columns. The tasks involve importing the dataset into a MySQL database, analyzing the user behavior, and answering various business-related questions.
The analysis continues by checking whether male or female users have more followers, calculating the total number of users using profile pictures, ecommerce applications, Android and iOS apps. The total number of buyers and sellers for each country is calculated, and the result is sorted in descending and ascending order, respectively. The top 10 countries with the maximum products pass rate are displayed, and the number of users on the platform for different language choices is calculated.
Further analysis is done to check the choices of female and male users about product liking and buying/selling on the ecommerce platform. The maximum number of buyers is determined, and the names of the countries with zero sellers are listed. The record of the top 110 users who recently used the ecommerce platform is displayed.
The next task is to calculate the number of female users who have not logged in for the last 100 days and display the number of female and male users of each country on the platform. Finally, the average number of products sold and bought on the ecommerce platform by male users for each country is calculated.