cintia-shinoda/sp-transit-network-centrality

---
language:
- pt
license: cc-by-4.0
tags:
- urban-mobility
- public-transport
- graph-theory
- network-analysis
- centrality-metrics
- sao-paulo
- brazil
- gtfs
size_categories:
- 10K<n<100K
task_categories:
- tabular-classification
- graph-ml
---

# São Paulo Transit Network — Centrality Metrics

## Description

Dataset containing graph centrality metrics for 21,892 bus stops in the São Paulo
public transit network, built from official SPTrans GTFS data.

The graph was modeled with stops as **nodes** and consecutive connections
within each trip as **edges**.

## Structure

| Column | Type | Description |
|--------|------|-------------|
| stop_id | str | Unique stop identifier (SPTrans) |
| stop_name | str | Stop name/address |
| lat | float | Latitude |
| lon | float | Longitude |
| degree | int | Node degree (number of direct connections) |
| degree_centrality | float | Normalized degree centrality |
| betweenness_centrality | float | Betweenness centrality |
| closeness_centrality | float | Closeness centrality |

## Graph Statistics

- **Nodes:** 21,892 stops
- **Edges:** ~29,797 unique connections
- **Source:** SPTrans GTFS (2025)

## Usage
```python
from datasets import load_dataset

ds = load_dataset("cintia-shinoda/sp-transit-network-centrality")
print(ds["train"][0])
```

## Citation
```bibtex
@misc{shinoda2026sp-transit,
author = {Cintia Shinoda},
title = {São Paulo Transit Network — Centrality Metrics},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/cintia-shinoda/sp-transit-network-centrality}
}
```

---

## Descrição (PT-BR)

Dataset com métricas de centralidade de grafo para 21.892 paradas de ônibus da rede de transporte público de São Paulo, construído a partir de dados
GTFS oficiais da SPTrans.

O grafo foi modelado com paradas como **nós** e conexões consecutivas dentro de cada trip como **arestas**.

## Contexto Acadêmico

Preparado como parte do Trabalho de Conclusão de Curso (TCC) em Ciência de Dados na UNIVESP (2026), com foco em análise de redes de transporte urbano
usando Teoria dos Grafos.