Github Ayishaliya Ecom Sales Analysis Data Analysis Project Using An

Leo Migdal

-Nov 18, 2025, 9:49 AM

github ayishaliya ecom sales analysis data analysis project using an

This project analyzes an online retail dataset to uncover sales trends, top products, best customers, and other actionable business insights. It demonstrates key data science skills: This project presents a comprehensive analysis of an e-commerce dataset using Python and popular data analysis libraries. It includes data cleaning, exploration, and a wide range of visualizations to uncover key insights about sales performance, customer behavior, and product trends. The dataset is located in the dataset folder and contains order-level transactional data, including: Key insights and visualizations generated:

Ammar Afzal 🎓 BS Computer Science | Python & Data Science Enthusiast 🔗 LinkedIn This project analyzes real-world online retail sales data using Python. It includes data cleaning, exploration, visualization, and insights. ecommerce-sales-analysis/ │ ├── README.md # Project overview and instructions ├── requirements.txt # Required Python libraries ├── data/ │ └── online_retail_II.csv # Real dataset used in the analysis ├── src/ │ └── analysis.py # Main... git clone https://github.com/your-username/ecommerce-sales-analysis.git cd ecommerce-sales-analysis python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt python src/analysis.py The dataset used is the Online Retail II dataset from the UCI Machine Learning Repository.

Youssef Ahmed Mohamed Shehata 📍 Cairo, Egypt 📧 youssefahmedshehata9@gmail.com 🔗 LinkedIn This project analyzes customer segmentation and behavior using data science and cohort analysis. Key metrics like CRR, NRR, CLR, and CLV are examined through detailed charts, including the cohort layer cake and CLR vs. CLV cost efficiency analysis. Exploratory Data Analysis and systematic data manipulation reveal actionable insights. Analyzed 49K+ sales records using Pandas & Matplotlib.

Identified top products and customer trends with visual insights. The Coffee Orders and Sales Dashboard uses Excel to visualize key data, including sales by country, top customers, roast type, and order date, helping optimize operations and boost sales through data-driven insights. This project involves analyzing a sizable sales dataset to identify patterns, best-selling items, and key revenue indicators. The goal is to provide data-driven insights to support business decision-making and improve sales strategies. This project involves analyzing sales data for a company to gain insights into sales trends, customer behavior, and business performance. The dataset used for this project contains information about orders, customers, products, and sales transactions.

This project analyzes an e-commerce dataset to uncover key business insights and provide actionable recommendations. The analysis follows the data analytics process: Ask → Prepare → Process → Analyze → Share → Act. Here are some example charts generated in the analysis: This project simulates an Analyst request to evaluate the performance of an E-Commerce platform across established and new markets, identifying key growth drivers, customer loyalty trends, and actionable recommendations. Goal: To provide executive-level insights that maximize Average Order Value (AOV) and customer retention. The project focused on answering the following strategic questions (https://github.com/ANSHEENA-KACHINIKKAD/ECommerce-Sales-Customer-Insight-Analysis/blob/main/PowerBI_Dashboard.png):

│ └── E_Commerce_Analysis_Scripts.sql https://github.com/ANSHEENA-KACHINIKKAD/ECommerce-Sales-Customer-Insight-Analysis/blob/main/E_Commerce_Analysis_Scripts.sql │ ├── ECommerce_Dashboard.pbix (https://github.com/ANSHEENA-KACHINIKKAD/ECommerce-Sales-Customer-Insight-Analysis/blob/main/ECommerce_Dashboard.pbix) In this project, I conducted an in-depth analysis of an e-commerce supply chain using Python and interactive visualization libraries like Plotly. The analysis aimed to uncover insights into product pricing, sales trends, revenue distribution, shipping costs, and product defects. Here's an overview of the key objectives and findings: This analysis provided actionable insights into optimizing supply chain efficiency, reducing shipping costs, and improving product defect rates during transit.

The project also demonstrated the potential for using advanced data visualization tools to make complex data more accessible and insightful for decision-makers. There was an error while loading. Please reload this page. This project involves analyzing e-commerce data using SQL, Excel, and Power BI to derive insights and visualize key metrics. The main objectives are to identify trends, track sales performance, and provide a comprehensive overview of business operations. This dashboard provides a comprehensive analysis of sales and net profit.

This dashboard focuses on a more detailed analysis of net profit. This project showcases the use of SQL, Excel, and Power BI to analyze and visualize e-commerce data effectively. The insights derived can help in making informed business decisions. A comprehensive sales analysis project using Excel, featuring data cleaning, visualization, and trend analysis. This project includes key sales metrics, pivot tables, dashboards, and insights to support data-driven decision-making. 1.

Generate a Customer Performance Report to analyze customer sales trends in three consecutive years. 2. Conduct an in-depth Market Performance vs Target Analysis to evaluate actual sales against business goals. 3. Identify high-revenue products with a Top 10 Products Report to optimize inventory and marketing strategies. 1.

Develop Profit & Loss Reports categorized by Year, Month, and Market to assess financial health.

Github Ayishaliya Ecom Sales Analysis Data Analysis Project Using An

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Youssef Ahmed Mohamed Shehata 📍 Cairo, Egypt 📧 Youssefahmedshehata9@gmail.com 🔗

Identified Top Products And Customer Trends With Visual Insights. The

This Project Analyzes An E-commerce Dataset To Uncover Key Business