🔗 https://population-growth-analysis-sejal.streamlit.app
The Smart Population Growth and Migration Analysis System is a Python-based Data Science project that simulates population growth, migration trends, forecasting, and statistical analysis over time.
The project combines mathematical modeling, data analytics, visualization, and simulation techniques to study how population changes under different growth and migration conditions.
- Simulate population growth over multiple years.
- Analyze the impact of migration on population changes.
- Detect important population milestones.
- Forecast future population trends.
- Compare growth patterns across multiple cities.
- Perform Monte Carlo simulations for random growth scenarios.
- Generate statistical insights and reports.
- Visualize population trends using charts and dashboards.
- Python
- Pandas
- NumPy
- Matplotlib
- OpenPyXL
- Streamlit
- 50-year population simulation
- Growth and migration calculations
- Year-by-year reporting
Detects when population exceeds:
- 5,000
- 10,000
- 50,000
- 100,000
- 1,000,000
Forecasts population for:
- 50 Years
- 100 Years
- 200 Years
- 500 Years
Calculates:
- Population doubling time
- Exact year of doubling
Compares growth of:
- City A
- City B
- City C
Studies scenarios where migration exceeds growth.
- 100 Random Simulations
- Best Outcome
- Worst Outcome
- Average Outcome
Calculates:
- Maximum Population
- Minimum Population
- Average Population
- Median Population
- Standard Deviation
- Variance
Generates:
- Line Chart
- Bar Chart
- Pie Chart
- City Comparison Chart
Exports:
- CSV Files
- Excel Workbook
Built using Streamlit for data visualization and analysis.
Population Growth Formula:
Population = Population × (1 + Growth Rate − Migration Rate)
Given:
- Growth Rate = 8%
- Migration Loss = 2%
Net Growth:
Net Growth = 6%
Population Formula:
Population = Population × 1.06
Population_Growth_Analysis_System/
├── population_analysis.py ├── app.py ├── requirements.txt ├── README.md
├── population_data.csv ├── growth_analysis.csv ├── milestone_report.csv ├── population_report.xlsx
├── charts/ │ ├── line_chart.png │ ├── bar_chart.png │ ├── pie_chart.png │ └── city_comparison.png
pip install -r requirements.txt
python population_analysis.py
streamlit run app.py
- Population Reports
- Excel Reports
- CSV Exports
- Population Growth Charts
- Statistical Analysis
- Streamlit Dashboard
- AI-Based Population Prediction
- Machine Learning Forecasting Models
- Interactive Plotly Dashboards
- Public Cloud Deployment
- Real-World Population Datasets Integration
Sejal Choudhari B.Tech (CSE - Artificial Intelligence)
This project is developed for academic and learning purposes.