Geospatial Analysis: Hotels & Parks in Naples

GIS project using GeoPandas, Plotly Express, and Contextily for spatial buffer and intersection analysis.

View the Project on GitHub Forren70/geopandas-plotly-express-naples

Geopandas Plotly Express Naples

This repository contains a GIS project for Naples, Italy, showcasing geospatial analysis using Geopandas, Matplotlib, Contextily, and Plotly Express.

The spatial datasets used in this project were originally downloaded from Overpass Turbo (https://overpass-turbo.eu/). The area was zoomed to the metropolitan area of Naples and two queries were run using the keywords tourism=hotel and leisure=park to obtain Hotels.geojson and Parks.geojson.

These files were subsequently refined in ArcGIS Pro: For hotels, only those located within the administrative boundaries of the City of Naples and with a recorded name in the attribute table were retained (saved as the shapefile Naples_Hotels_32633 in the Naples_geopandas folder). For parks, only polygons with an area greater than or equal to 0.8 hectares were selected (saved as the shapefile Naples_Parks_32633 in the Naples_geopandas folder).

⚠️ Disclaimer: This analysis is intended solely as an example of the capabilities of Python geospatial libraries such as Geopandas, Matplotlib, Contextily, and Plotly Express. It does not represent a complete or official inventory of all hotels and green areas in Naples.

The project includes:

Contents

Map Examples

Map 1: Parks and Hotels in Naples

Map 1

Map 2: 150m Buffer Analysis

Map 2

Map 3: Suitable Hotels (within 150 m from Parks)

Map 3

Dependencies

This project uses the following Python libraries:

How to Run the Scripts

  1. Make sure all the shapefiles are in the Naples_geopandas folder.
  2. Place the screenshots folder in the same repository if you want to view the generated maps.
  3. Run the scripts in this order:

```bash python geopandas-plotly-express-naples.py python geopandas-plotly-express-naples-buffer.py python geopandas-plotly-express-naples-intersected-hotels.py