Python App for Treating, analyzing and visualizing Personal Financial Data on Flask and Plotly Web App
This simple Python App applies Pandas, plotly, flask and dash functionalities to create a simple yet insightfull web app for analysing expenses data:
- monthly
- by category of purchase
- by type of payment
Feel free to locally use it for your own personal data expenses analysis. :)
| Column | Description | Column-type |
|---|---|---|
| date | date of purchase on format YYYY-MM-DD | string |
| payment_type | type of payment (debit, credit..) | string |
| price | value of the purchase/expanse | string |
| category | what type of purchase/expanse? (ex: food, gasoline, rent) | string |
| subcategory | is there a sub-type worth monitoring? (ex: groceries, restaurant, transport) | string |
- Set a file .env inside app folder with a configured env var FINANCIAL_DATA_PATH=your-csv-file-path.
- Make sure all dependencies are installed:
pip install -r ./app/requirements.txt- Make sure that your data column names matches the ones on the tools.treatment.treat_data if not, adapt either script or data schema.
- To run the app:
python3 ./app/main.py- Your dashboard will be available at http://127.0.0.1:8050/.