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.
- 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.
To get started with FinancialTrendAnalyzer, clone the repository and install the necessary dependencies:
git clone https://github.com/nomadsdev/financial-trend-analyzer.git
cd financial-trend-analyzer
pip install numpy pandas matplotlib seaborn-
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 ... -
Run the Analysis: Execute the script to perform data analysis and generate visualizations:
python analyze.py
We welcome contributions to FinancialTrendAnalyzer. Please submit a pull request or open an issue if you have suggestions or improvements.
For support, please contact us at support@jmmentertainment.com.
This project is licensed under the MIT License.