avani1998 / interrilato

This project involves the analysis of various socioeconomic factors across different states and union territories of India. The analysis focuses on relationships between literacy rates, poverty rates, unemployment rates, and crime contributions in these regions.

Interrilato: Exploring Data Relationships

Project Overview

This project involves the analysis of various socioeconomic factors across different states and union territories of India. The analysis focuses on relationships between literacy rates, poverty rates, unemployment rates, and crime contributions in these regions. The purpose is to uncover patterns and insights that could aid in understanding the socioeconomic dynamics at play.

Key Insights

Correlation Analysis: Identification of how different socioeconomic factors correlate with crime rates. Regression Analysis: Linear regression models to quantify the relationships between variables. Visualizations: Interactive visualizations to represent the data and the analysis, facilitating an intuitive understanding of the dataset and findings.

Setup and Execution

• Ensure Python 3.x is installed on your system.
• Install necessary Python packages using

  pip install pandas matplotlib seaborn plotly scikit-learn statsmodels numpy geopandas    
  

• Run the scripts in a sequential manner, starting with EDA.ipynb followed by StaticMap.ipynb.

Contributing

Contributions to the project are welcome! Please fork the repository, make your changes, and submit a pull request