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Every quarter I would sit down topull together all the different transactions from financial instituations,unify them into a format and then try to make anoverview of different charts to understand what has happened during the last quarter to my finances.
The last part of this whole process is tackled by this small project.
A web-based dashboard that visualizes spending data, providing users with insights into their financial habits.
The dashboards consists offive sections
- Profit & Loss
- In- vs. Outflows
- Fix vs. Var (for In- and Outflows)
- Categories (for In- and Outflows)
- Biggest Transactions
- Notes(see above)
- Interactive charts and graphs for visualizing spending patterns.
- Filter and categorize spending data for detailed analysis.
- User-friendly interface with intuitive navigation.
- Responsive design for seamless usage on various devices.
Follow these steps to set up and run the Spending Dashboard locally.
- Clone the repository:
git clone https://github.com/your-username/spending-dashboard.git
- Navigate to the project directory:
cd spending-dashboard
- Install dependencies:
python -m pip install -r requirements.txt
- Configure the user input (seeConfiguration)
- Navigate into
reporting
directory:cd reporting
- Run
streamlit
:streamlit run streamlit.py
- Open web browser (might be done automatically by
streamlit
) athttp://localhost:8501/
(can differ, look at console output)
- Edit the
config.json
file to customize dashboard settings.{"year": "2023","quarter" : "Q1","path_to_data": "../data/sample_data.csv","notes": "This is a test note."}
- Make sure your data adheres to the minimal requirements defined in
QuarterlyInputData
here (this will also be checked by the application)
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Visualization of Spending Data realized with Streamlit, Pandera and Plotly
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