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Manfrinópolis
City in Paraná, Brazil
Overview
Manfrinópolis is a tranquil small town in southwestern Paraná, Brazil, with a welcoming rural charm. Known for its scenic landscapes, friendly locals, and traditional Southern Brazilian culture, it's ideal for visitors seeking peaceful retreats.
Geographic Context
Jurisdiction
Brazil
State
Paraná
Population
2,790
Time Zone
America/Sao_Paulo
Coordinates
-26.10°, -53.36°
Key Metrics
Safety Score · estimate
65
Female Safety
62
LGBTQ+ Safety
36
Traffic Safety
60
Food Safety
60
Monthly Cost · estimate
$583
Local Cost
$380
Local Income
$290
Cashless
25
English
20
Temperature
19.3°C
Summer Avg
23.4°C
Winter Avg
14.6°C
Record High
37.9°C
Record Low
-3.9°C
Humidity
81%
Precipitation
1698 mm
Internet Speed
16 Mbps
Upload
27 Mbps
Latency
27 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
FBE
Distance
30 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: 53/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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