Mini Project
Data Science
Personal Finance Analytics
Statement parsing, auto-categorisation and spend forecasting
- Python
- Pandas
- Prophet
- Streamlit
- +2
₹2,299₹3,999
4.5/198 reviews
Data Science · Mini Project
Billionaires Wealth Analysis
Explores the Forbes list by country, industry, age and source
1-2 weeks build
Overview
Works with a public Forbes billionaires dataset from Kaggle to ask where extreme wealth sits and how it was made. The notebook breaks the list down by country, industry, age and self-made versus inherited status, measures how concentrated wealth is at the very top, and gives Indian billionaires a section of their own.
What makes it stand up
- 01Country and industry rankings by count and total wealth
- 02Self-made versus inherited comparison
- 03Age and gender distributions with box plots
- 04Wealth concentration shown with a Lorenz curve
- 05Dedicated section on Indian billionaires
Module breakdown
- 01
Cleaning
Parses net worth strings and fills missing fields.
- 02
Geography
Counts and wealth totals per country.
- 03
Industries
Which sectors produce the most billionaires.
- 04
Demographics
Age, gender and self-made breakdowns.
- 05
Concentration
Lorenz curve and share held by the top ten.
After this, you will be able to
- Explain what a Lorenz curve shows about inequality
- Defend how you parsed and cleaned net worth values
- Present the three most surprising findings with charts
Technology stack
- Python
- Pandas
- Seaborn
- Plotly
- Jupyter
- Level
- Mini Project
- Domain
- Data Science
- Build time
- 1-2 weeks
- Difficulty
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support