Analyzing crime trends in Mexico using population and poverty data. Includes Plotly maps, EDA, and correlation with social factors.
-
Updated
Jun 29, 2025 - Jupyter Notebook
Analyzing crime trends in Mexico using population and poverty data. Includes Plotly maps, EDA, and correlation with social factors.
Exploratory data analysis and visualization of the Gapminder dataset, focusing on life expectancy, GDP per capita, and population trends across countries and continents from 1952 to 2007 using Python and Seaborn.
Hierarchical agglomerative clustering (HAC) based on socioeconomic indicators of countries.
Interactive map exploring affordability across counties based on income and cost of living.
Add a description, image, and links to the socioeconomic-data topic page so that developers can more easily learn about it.
To associate your repository with the socioeconomic-data topic, visit your repo's landing page and select "manage topics."