Since when I moved to Bangalore I've been monitoring my expenses. Every night I used to fill the data in an Excel sheet. And this is my personal finance dashboard where I have plotted various charts representing my spendings...

• So Initially I have used an .ipynb file to do the preprocessing and do some visualization

• Then I have made another file finance.py to implement all the functions related to preprocessing and plotting

• I have imported the same file in app.py and used it along with streamlit to build the app.

• Shows multiple analytical charts to help me better understand my spendings.
• Can be connected to the database and automated.
• Answers few predefined quick QNA type questions.
• Responsive layout, can be opened in any device.

To run the app you need to download this repository along with the required libraries and it the command line you have to write streamlit run app.py to run.

it might ask for your email once...

Personal Finance 
│
|---- __pycache__
|
|---- .streamlit
|   |---- config.toml
|
|---- data 
|   |---- bangalore - item.csv
|   |---- bangalore - Total_spending.csv
|
|---- demo 
|   |---- __pycache__
|   |---- data
|   |   |---- bangalore - item.csv
|   |   |---- bangalore - Total_spending.csv
|   |
|   |---- demoapp.py
|   |---- democalss.py
|   |---- README.md
|   
|---- results
|   |---- Personal Finance.mp4
|   |---- Screenshot.png
|
|---- static
|   |---- compressed_heroimage.gif
|   |---- hero_image.gif
|
|---- app.py
|---- exploratory_data_analysis.ipynb
|---- finance.py
|---- markdown.py
|---- Procfile 
|---- README.md
|---- requirements.txt
|---- setup.sh

• python library - numpy, pandas, seaborn, matplotlib, streamlit
• version control - git
• backend - streamlit
• concept - OOP

• IDE - Vs code
• Application Deployment - Heroku
• Code Repository - GitHub

• LinkedIn

• You can find my other projects and EDAs on Kaggle