Rio de Janeiro Real Estate Data Analysis

This Jupyter Notebook provides a step-by-step guide for analyzing real estate data in Rio de Janeiro using geospatial tools, including GeoPandas and Folium. The primary goal is to visualize and analyze real estate data in the context of Rio de Janeiro's geographic boundaries.

Getting Started

Prerequisites

Before running this notebook, ensure you have the following installed:

• Python
• GeoPandas
• Folium

Data Sources

The data for this analysis can be found here.

Notebook Sections

• Loading Geospatial Data

In this section, we load shapefiles for Rio de Janeiro and real estate data from CSV files.

• Visualizing Geospatial Data

We visualize the geographical boundaries of Rio de Janeiro and filter the data to focus on the city itself.

• Creating a Heatmap

We generate a heatmap to visualize real estate data spatially. The heatmap displays the concentration of properties in the city.

• Adding Layer Controls

This section adds layer controls to the map, allowing you to toggle between different map styles, such as dark mode and positron.

• Adding Neighborhood Names

To enhance the map, we add neighborhood names as tooltips, making it easier to identify different areas.

• Saving the Map

The final map is saved as an HTML file for sharing and further analysis.