https://github.com/ahsankhizar5/retail-sales-analysis-python-powerbi
A complete retail sales analytics project using Python for data cleaning and EDA, and Power BI for dashboard visualization. Built as a capstone for the Business Analytics Bootcamp by CourseMea.
https://github.com/ahsankhizar5/retail-sales-analysis-python-powerbi
business-analytics capstone-project coursemea dashboard data-visualization eda exploratory-data-analysis powerbi python python3 retail-data
Last synced: 18 days ago
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A complete retail sales analytics project using Python for data cleaning and EDA, and Power BI for dashboard visualization. Built as a capstone for the Business Analytics Bootcamp by CourseMea.
- Host: GitHub
- URL: https://github.com/ahsankhizar5/retail-sales-analysis-python-powerbi
- Owner: ahsankhizar5
- Created: 2025-07-21T07:23:25.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-07-21T07:54:00.000Z (11 months ago)
- Last Synced: 2025-07-21T09:29:45.166Z (11 months ago)
- Topics: business-analytics, capstone-project, coursemea, dashboard, data-visualization, eda, exploratory-data-analysis, powerbi, python, python3, retail-data
- Language: Python
- Homepage:
- Size: 2.75 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Retail Sales Analysis & Power BI Dashboard
An end-to-end data analysis and dashboarding project using **Python** and **Power BI**. This project performs detailed Exploratory Data Analysis (EDA) on retail sales data and visualizes key trends and insights through an interactive Power BI dashboard.
📊 Includes a full `.pbix` Power BI file, EDA Python scripts, and visual assets.
**📦 Repository:** [https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI](https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI)
---
## 📊 Dashboard Preview
Explore 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.
---
## ✨ Features
* 🧹 **Data Cleaning**: Handled missing values and duplicates for clean insights
* 📈 **Exploratory Data Analysis (EDA)**: Python-based EDA using `pandas`, `matplotlib`, and `seaborn`
* 📊 **Interactive Dashboard**: Built with Power BI for dynamic KPI viewing and slicing
* 📌 **Key Insights Highlighted**: Includes business-level summaries from sales and customer trends
* 🖼️ **Dashboard Screenshot**: Visual preview inside README
* 📁 **Organized Structure**: Includes `data/`, `code/`, `graphs/`, and `powerbi/` folders for clarity
* 📄 Includes: `Retail_Sales_Dashboard.pbix`, EDA script, and optional PDF report
---
## 🧠 Key Insights
- **Top Performing Category**: *Clothing* led both in revenue and quantity sold
- **Sales Pattern**: Clear cyclical/seasonal trends identified in monthly data
- **Customer Behavior**: Most purchases are frequent and small-quantity based
- **Gender Split**: Nearly equal male-female purchase behavior, indicating broad product appeal
---
## 🚀 Getting Started
### 1. **Clone the Repository**
```bash
git clone https://github.com/ahsankhizar5/Retail-Sales-Analysis-Python-PowerBI.git
cd Retail-Sales-Analysis-Python-PowerBI
````
### 2. **Install Python Requirements**
```bash
pip install pandas matplotlib seaborn
```
> ✅ Requires Python 3.x and Power BI Desktop installed.
### 3. **Run the EDA Script**
```bash
python code/eda.py
```
### 4. **Open the Power BI Dashboard**
* Launch Power BI Desktop
* Open `powerbi/Retail_Sales_Dashboard.pbix`
* Make sure `data/cleaned_retail_sales_dataset.csv` is in place
---
## 🗂 Folder Structure
```
Retail-Sales-Analysis-Python-PowerBI/
├── data/
│ ├── retail_sales_dataset.csv # Raw data
│ └── cleaned_retail_sales_dataset.csv # Processed data
├── code/
│ └── eda.py # Python script for EDA
├── powerbi/
│ ├── Retail_Sales_Dashboard.pbix # Power BI file
│ └── Retail_Sales_Dashboard.pdf # Exported dashboard as PDF
├── docs/
│ └── power_bi_guide.md # Optional documentation
├── graphs/
│ └── Dashboard Overview.png # Dashboard preview image
└── README.md
```
---
## 🛠️ Tech Stack
* **Python** – Data manipulation & visualization
* **Pandas, Matplotlib, Seaborn** – For EDA
* **Power BI Desktop** – For dashboard building
* **CSV** – Flat-file based data storage
---
## 🤝 Want to Contribute?
1. **Fork this repository**
2. **Create a new feature branch**
```bash
git checkout -b feature/your-feature
```
3. **Commit your changes**
```bash
git commit -m "Add your feature"
```
4. **Push and submit a pull request**
```bash
git push origin feature/your-feature
```
---
## 📄 License
MIT License — free to use, reuse, and adapt with credit.
---
## 🌟 Give a Star
If you found this project useful, insightful, or inspiring — feel free to ⭐ it on GitHub!
---
> 💡 *"Great dashboards don’t just tell you what happened — they help you see what to do next."*
```