In 2022, I decided to create a budget to track my expenditures and see how I was spending my money. The goal was to identify any trends or hidden patterns that could help improve my financial well-being.
The data was collected from my personal financial statements and stored in a google sheet. For this app, I connected to the Google API to access the data. A link has been cited below with a tutorial that you can follow if you want to try this for yourself.
The data was cleaned in python and google sheets. There is an 'clean_data.ipynb' file in the repo that outlines the data manipulation.
- Monthly and Yearly Financial Statistics
- Analyze 10 categories with the highest spend. This is the default but you can filter for specific categories with the sidebar
- View the selected month's ledger and view the historical ledger
- Analyze the Income and Debits and how they change over time
- See the cumulative Income and Debits for the selected years
- Open terminal and use command
pip -r requirements.txtto install required packages an version numbers. - Run with terminal command
streamlit run app.py - Optional: Use the
import data.ipynbfile to import your data from googlesheets - Optional: Run the
clean_data.ipynbto clean the data and concatenate multiple sheets into a single dataframe
I plan to add more data for years 2023 and 2024. I also hope to add a file uploader so that I can upload data directly into Streamlit when it is current. I would also like to add a 'Select All' check box to the sidebar to select all categories.
Medium Article - Reading Google Sheets into a Pandas Dataframe
Connecting to Google Sheets API -- Ensure you give access to google sheets api (not explictly stated in the tutorial)