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https://github.com/nomadsdev/financial-trend-analyzer
FinancialTrendAnalyzer helps analyze and visualize sales data to uncover financial trends. It uses Python to calculate total sales, track changes, and generate insightful charts for better decision-making.
https://github.com/nomadsdev/financial-trend-analyzer
business-intelligence data-analysis data-visualization financial-analysis matplotlib numpy pandas python revenue-trends sales-data seaborn time-series-analysis
Last synced: 15 days ago
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FinancialTrendAnalyzer helps analyze and visualize sales data to uncover financial trends. It uses Python to calculate total sales, track changes, and generate insightful charts for better decision-making.
- Host: GitHub
- URL: https://github.com/nomadsdev/financial-trend-analyzer
- Owner: nomadsdev
- Created: 2024-09-18T02:30:24.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-09-18T02:34:04.000Z (4 months ago)
- Last Synced: 2024-11-07T13:42:07.673Z (about 2 months ago)
- Topics: business-intelligence, data-analysis, data-visualization, financial-analysis, matplotlib, numpy, pandas, python, revenue-trends, sales-data, seaborn, time-series-analysis
- Language: Python
- Homepage:
- Size: 1.95 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# FinancialTrendAnalyzer
**FinancialTrendAnalyzer** is a comprehensive tool for analyzing financial trends and sales data. This project helps you to visualize and understand revenue patterns, changes, and averages using advanced data analysis techniques.
## Features
- **Data Loading**: Import financial data from CSV files.
- **Missing Data Handling**: Detect and handle missing data effectively.
- **Data Analysis**: Calculate total sales, percentage changes, and average sales.
- **Visualizations**: Generate insightful visualizations such as trend lines, percentage change graphs, and heatmaps.
- **Error Handling**: Robust error handling for data-related issues.
## Installation
To get started with **FinancialTrendAnalyzer**, clone the repository and install the necessary dependencies:
```bash
git clone https://github.com/nomadsdev/financial-trend-analyzer.git
cd financial-trend-analyzer
pip install numpy pandas matplotlib seaborn
```
## Usage
1. **Prepare Your Data**: Ensure your CSV file follows the format:
```
Date,Product A,Product B,Product C
2024-01-01,100,80,90
2024-02-01,150,120,110
...
```
2. **Run the Analysis**: Execute the script to perform data analysis and generate visualizations:
```bash
python analyze.py
```
## Contributing
We welcome contributions to **FinancialTrendAnalyzer**. Please submit a pull request or open an issue if you have suggestions or improvements.
## Support
For support, please contact us at [[email protected]](mailto:[email protected]).
## License
This project is licensed under the MIT License.