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| # KPI Correlation Analysis Gradio App Usage Guide | |
| ## Overview | |
| This Gradio app provides a simple web interface for analyzing correlations between IPM scores and axiia scores (problem_score and ability_score). | |
| ## How to Run the App | |
| 1. **Navigate to the app directory:** | |
| ```bash | |
| cd data-analysis/kpi_score_analysis | |
| ``` | |
| 2. **Run the app:** | |
| ```bash | |
| python3 kpi_correlation_app.py | |
| ``` | |
| 3. **Access the app:** | |
| - The app will start and display a URL (typically `http://127.0.0.1:7860`) | |
| - Open this URL in your web browser | |
| ## Using the App | |
| 1. **Upload KPI File:** | |
| - Click on the "Upload KPI File" area | |
| - Select your KPI file (supports .csv, .xls, .xlsx formats) | |
| - The file should contain: | |
| - Email column | |
| - FY23/24 IPM column | |
| - FY24/25 IPM column | |
| 2. **Analyze:** | |
| - Click the "Analyze Correlations" button | |
| - The app will process the data and match emails with the scores file | |
| 3. **View Results:** | |
| - **Analysis Results:** Text output showing: | |
| - Data quality report (number of records, matched emails) | |
| - Correlation analysis for each pair (AC, AD, BC, BD) | |
| - Pearson and Spearman correlation coefficients | |
| - P-values and sample sizes | |
| - **Correlation Plots:** Four scatter plots showing: | |
| - AC: Problem Score vs FY23/24 IPM | |
| - AD: Problem Score vs FY24/25 IPM | |
| - BC: Ability Score vs FY23/24 IPM | |
| - BD: Ability Score vs FY24/25 IPM | |
| ## Example Files | |
| You can test the app with these files: | |
| - `test_kpi.csv` (in the same directory) | |
| - `../../data/lenovo_kpi.csv` | |
| - `../../data/Copy of 联想 kpi copy.xlsx` | |
| ## Technical Details | |
| - The app uses a fixed scores file (`lenovo-scores-0603.csv`) that must be in the same directory | |
| - Handles both CSV and Excel files for KPI data | |
| - Automatically converts percentage strings to numeric values | |
| - Only analyzes records with matching emails and complete data | |
| - Shows trend lines and correlation coefficients on plots | |
| ## Troubleshooting | |
| - **"Error: scores file not found"**: Ensure `lenovo-scores-0603.csv` is in the same directory as the app | |
| - **"No matching emails found"**: Check that email addresses in KPI file match those in scores file | |
| - **Empty plots**: This indicates insufficient data points for that correlation pair | |
| ## Requirements | |
| - Python 3.x | |
| - Required packages: gradio, pandas, numpy, scipy, matplotlib, seaborn | |
| - All dependencies should already be installed in the lenovo-reports environment |