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Faxinalzinho
City in Rio Grande do Sul, Brazil
Overview
Faxinalzinho is a small, rural town in the north of Rio Grande do Sul, Brazil, known for its welcoming community and relaxed pace of life. Agriculture drives the local economy, and visitors can enjoy scenic countryside views and simple, authentic Brazilian hospitality.
Geographic Context
Jurisdiction
Brazil
State
Rio Grande do Sul
Population
2,572
Time Zone
America/Sao_Paulo
Coordinates
-27.37°, -52.67°
Key Metrics
Safety Score · estimate
55
Female Safety
50
LGBTQ+ Safety
40
Traffic Safety
60
Food Safety
65
Monthly Cost · estimate
$630
Local Cost
$270
Local Income
$350
Cashless
32
English
18
Temperature
18.6°C
Summer Avg
22.8°C
Winter Avg
13.9°C
Record High
38.1°C
Record Low
-4.6°C
Humidity
81%
Precipitation
1777 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
XAP
Distance
26 km
Explore
Data sources
Source-backed data
World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-07.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-06.
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: 66/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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