{"id":50443556,"url":"https://github.com/ahsankhizar5/retail-sales-analysis-python-powerbi","last_synced_at":"2026-05-31T20:01:33.475Z","repository":{"id":305642048,"uuid":"1023450109","full_name":"ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI","owner":"ahsankhizar5","description":"A complete retail sales analytics project using Python for data cleaning and EDA, and Power BI for dashboard visualization. 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This project performs detailed Exploratory Data Analysis (EDA) on retail sales data and visualizes key trends and insights through an interactive Power BI dashboard.\n\n📊 Includes a full `.pbix` Power BI file, EDA Python scripts, and visual assets.\n\n**📦 Repository:** [https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI](https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI)\n\n---\n## 📊 Dashboard Preview\n\n![Retail Dashboard](graphs/Dashboard%20Overview.png)\n\nExplore the full dashboard by opening the `.pbix` file in Power BI Desktop. All visuals are interactive and support filtering by region, gender, and product categories.\n\n---\n\n## ✨ Features\n\n* 🧹 **Data Cleaning**: Handled missing values and duplicates for clean insights  \n* 📈 **Exploratory Data Analysis (EDA)**: Python-based EDA using `pandas`, `matplotlib`, and `seaborn`  \n* 📊 **Interactive Dashboard**: Built with Power BI for dynamic KPI viewing and slicing  \n* 📌 **Key Insights Highlighted**: Includes business-level summaries from sales and customer trends  \n* 🖼️ **Dashboard Screenshot**: Visual preview inside README  \n* 📁 **Organized Structure**: Includes `data/`, `code/`, `graphs/`, and `powerbi/` folders for clarity  \n* 📄 Includes: `Retail_Sales_Dashboard.pbix`, EDA script, and optional PDF report\n\n---\n\n## 🧠 Key Insights\n\n- **Top Performing Category**: *Clothing* led both in revenue and quantity sold  \n- **Sales Pattern**: Clear cyclical/seasonal trends identified in monthly data  \n- **Customer Behavior**: Most purchases are frequent and small-quantity based  \n- **Gender Split**: Nearly equal male-female purchase behavior, indicating broad product appeal\n\n---\n\n\n## 🚀 Getting Started\n\n### 1. **Clone the Repository**\n```bash\ngit clone https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI.git\ncd Retail-Sales-Analysis-Python-PowerBI\n````\n\n### 2. **Install Python Requirements**\n\n```bash\npip install pandas matplotlib seaborn\n```\n\n\u003e ✅ Requires Python 3.x and Power BI Desktop installed.\n\n### 3. **Run the EDA Script**\n\n```bash\npython code/eda.py\n```\n\n### 4. **Open the Power BI Dashboard**\n\n* Launch Power BI Desktop\n* Open `powerbi/Retail_Sales_Dashboard.pbix`\n* Make sure `data/cleaned_retail_sales_dataset.csv` is in place\n\n---\n\n## 🗂 Folder Structure\n\n```\nRetail-Sales-Analysis-Python-PowerBI/\n├── data/\n│   ├── retail_sales_dataset.csv                # Raw data\n│   └── cleaned_retail_sales_dataset.csv        # Processed data\n├── code/\n│   └── eda.py                                  # Python script for EDA\n├── powerbi/\n│   ├── Retail_Sales_Dashboard.pbix             # Power BI file\n│   └── Retail_Sales_Dashboard.pdf              # Exported dashboard as PDF\n├── docs/\n│   └── power_bi_guide.md                       # Optional documentation\n├── graphs/\n│   └── Dashboard Overview.png                  # Dashboard preview image\n└── README.md\n```\n\n---\n\n## 🛠️ Tech Stack\n\n* **Python** – Data manipulation \u0026 visualization\n* **Pandas, Matplotlib, Seaborn** – For EDA\n* **Power BI Desktop** – For dashboard building\n* **CSV** – Flat-file based data storage\n\n---\n\n## 🤝 Want to Contribute?\n\n1. **Fork this repository**\n2. **Create a new feature branch**\n\n```bash\ngit checkout -b feature/your-feature\n```\n\n3. **Commit your changes**\n\n```bash\ngit commit -m \"Add your feature\"\n```\n\n4. **Push and submit a pull request**\n\n```bash\ngit push origin feature/your-feature\n```\n\n---\n\n## 📄 License\n\nMIT License — free to use, reuse, and adapt with credit.\n\n---\n\n## 🌟 Give a Star\n\nIf you found this project useful, insightful, or inspiring — feel free to ⭐ it on GitHub!\n\n---\n\n\u003e 💡 *\"Great dashboards don’t just tell you what happened — they help you see what to do next.\"*\n\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahsankhizar5%2Fretail-sales-analysis-python-powerbi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahsankhizar5%2Fretail-sales-analysis-python-powerbi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahsankhizar5%2Fretail-sales-analysis-python-powerbi/lists"}