https://github.com/ahmadrazacdx/sales-data-analysis
A comprehensive data analysis project focusing on sales data exploration, cleaning, and statistical analysis. This includes key insights into sales trends, customer behavior, product categories, delivery times, and seasonality effects. Advanced statistical tests and visualizations are added to identify relationships and make data driven decisions.
https://github.com/ahmadrazacdx/sales-data-analysis
data-cleaning data-exploration exploratory-data-analysis feature-engineering hypothesis-testing time-series-analysis time-series-forecasting
Last synced: 27 days ago
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A comprehensive data analysis project focusing on sales data exploration, cleaning, and statistical analysis. This includes key insights into sales trends, customer behavior, product categories, delivery times, and seasonality effects. Advanced statistical tests and visualizations are added to identify relationships and make data driven decisions.
- Host: GitHub
- URL: https://github.com/ahmadrazacdx/sales-data-analysis
- Owner: ahmadrazacdx
- License: other
- Created: 2024-10-22T11:18:03.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-18T04:53:53.000Z (over 1 year ago)
- Last Synced: 2025-01-18T05:28:50.780Z (over 1 year ago)
- Topics: data-cleaning, data-exploration, exploratory-data-analysis, feature-engineering, hypothesis-testing, time-series-analysis, time-series-forecasting
- Language: Jupyter Notebook
- Homepage:
- Size: 4.6 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Sales Data Analysis
A comprehensive data analysis project focusing on sales data exploration, cleaning, and statistical analysis. The project includes key insights into sales trends, customer behavior, product categories, delivery times, and seasonality effects. Advanced statistical tests and visualizations are employed to identify significant relationships and make data-driven decisions.
## 📝 Project Overview
In this project, I have analyzed a comprehensive sales dataset to uncover key insights and trends. The analysis is divided into the following steps:
1. **Data Exploration** – Initial examination of the dataset to understand its structure.
2. **Data Cleaning** – Handling missing values, outliers, and correcting data types.
3. **Feature Engineering** – Creating new features like delivery time and customer segments.
4. **Exploratory Data Analysis (EDA)** – Visualizing data to identify trends and patterns.
5. **Time Series Analysis** - Analysing Time Series Components, Trend, Seasonailty, Residue etc
6. **Time Series Forecasting** - Forecasting Sales for next quarter
7. **Hypothesis Testing** – Conducting statistical tests to validate hypothesis.
## 🛠 Technologies Used
- **Python**: Core programming language used for the analysis.
- **Pandas**: Data manipulation and analysis.
- **NumPy**: Numerical operations.
- **Matplotlib**: Data visualization.
- **Seaborn**: Enhanced data visualizations.
- **Plotly**: Ingeractive data visualizations.
- **Scipy**: Statistical hypothesis testing.
- **Others**: Some other useful utility libraries.
## 📁 Project Structure
```bash
Sales-Data-Analysis/
├── data/
│ └── sales_data.csv, header.png
├── sales_data_analysis.ipynb
└── README.md
```
## ⚙️ How to Run the Project
1. Clone the repository:
```
git clone https://github.com/ahmadrazacdx/Sales-Data-Analysis.git
```
2. Install the required dependencies:
```
pip install -r requirements.txt
```
3. Open the Jupyter notebook and run the cells:
```
jupyter notebook sales_data_analysis.ipynb
```
## 📜License
This project is licensed under a custom license. You are allowed to view, share, and use this project for non-commercial purposes, provided you give appropriate credit to the original author.
For the full context of the license, please visit [here](https://github.com/ahmadrazacdx/Sales-Data-Analysis?tab=License-1-ov-file).
## 📧 Contact
If you have any questions or suggestions, feel free to contact me at: [ahmadrazacdx@gmail.com]