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São João da Talha

City in Lisbon, Portugal

Overview

São João da Talha is a lively suburban city just outside Lisbon, known for its friendly neighborhoods and easy access to the capital. Blending traditional Portuguese charm with modern conveniences, it's attractive to both families and professionals.

Geographic Context

Jurisdiction
Portugal
District
Lisbon
Population
18,925
Time Zone
Europe/Lisbon
Coordinates
38.82°, -9.10°

Key Metrics

Safety Score · estimate
78
Female Safety
75
LGBTQ+ Safety
76
Traffic Safety
73
Food Safety
90
Monthly Cost · estimate
$1,830
Local Cost
$1,085
Local Income
$1,050
Cashless
64
English
54
Temperature
16.0°C
Summer Avg
19.9°C
Winter Avg
11.8°C
Record High
36.3°C
Record Low
0.0°C
Humidity
80%
Precipitation
574 mm
Internet Speed
252 Mbps
Upload
112 Mbps
Latency
9 ms
City Vibrancy
29
Coworking
0
Cafes
14
Nightlife
0
Parks
15
Transport
0
Walk Score
0
Footways
—
Airport
LIS
Distance
6 km

Data sources

Source-backed data

Ookla Open Data - Internet speed aggregates for 2024Q3 from 37 tests. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-05.

Estimates and unverified origins

Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-22.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 70/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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