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 · Major Project
Crime Data Analysis & Visualisation
State and district crime trends from NCRB data with hotspot maps
2-3 weeks build
Overview
Brings the published National Crime Records Bureau tables into a single tidy dataset covering crime heads, states, districts and years. The analysis normalises counts by population to get crime rates, tracks trends in crimes against women and children, and maps district hotspots with GeoPandas. A Streamlit dashboard lets users filter by crime type, state and year.
What makes it stand up
- 01Tidy dataset assembled from year-wise NCRB tables
- 02Population-normalised crime rates, not raw counts
- 03Trend analysis for crimes against women and children
- 04District-level choropleth hotspot maps
- 05Filterable dashboard with year-on-year comparisons
Module breakdown
- 01
Assembly
Merges and reshapes yearly tables into long format.
- 02
Normalisation
Joins census population to compute crime rates.
- 03
Trend analysis
Year-on-year change by state and crime head.
- 04
Mapping
GeoPandas choropleths at state and district level.
- 05
Dashboard
Streamlit filters, maps and ranked tables.
After this, you will be able to
- Explain why rates per lakh beat raw counts for comparison
- Discuss reporting bias as a limit on the conclusions
- Demo a hotspot map for a state the examiner picks
Technology stack
- Python
- Pandas
- GeoPandas
- Plotly
- Streamlit
- Level
- Major Project
- Domain
- Data Science
- Build time
- 2-3 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