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Ivaiporã

City in Paraná, Brazil

Overview

Ivaiporã is a small but lively city in Paraná, Brazil, known for its welcoming community and lush surrounding countryside. Its relaxed pace, local festivals, and mix of traditional charm with modern conveniences make it an appealing spot for travelers looking to experience authentic interior Brazil.

Geographic Context

Jurisdiction
Brazil
State
Paraná
Population
33,566
Time Zone
America/Sao_Paulo
Coordinates
-24.28°, -51.63°

Key Metrics

Safety Score
60
Female Safety
50
LGBTQ+ Safety
45
Traffic Safety
65
Food Safety
70
Monthly Cost
$743
Local Cost
$444
Local Income
$410
Cashless
35
English
20
Temperature
19.8°C
Summer Avg
23.0°C
Winter Avg
15.7°C
Record High
37.4°C
Record Low
-3.4°C
Humidity
80%
Precipitation
1585 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0

Explore

Cost of Living
Prices & expenses
Weather & Climate
Temperature & conditions
Alternatives
Similar cities worldwide
Compare
Side-by-side comparison
Neighborhoods
4 areas mapped
City Guide
Tips & insights

Neighborhoods

Partial

Coverage is incomplete — additional neighborhoods are being added as more source data is processed.

Alto Porã Jacutinga Praça França

Coverage is incomplete — more neighborhoods are being added.

View all 4 neighborhoods

Frequently Asked Questions

Data sources

Source-backed data

NASA POWER - Climate normals and monthly weather measurements rendered as city weather metrics. Updated 2026-03-22.
World Air Quality Index - Latest available city-level air quality station measurement. Updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Updated 2025-12-06.
Oyster List city price model - City price estimates calibrated from local price surveys and jurisdiction-level cost signals. Updated 2026-01-14.
Overture Maps and OpenStreetMap - 4 source-backed neighborhood entities are available for this city. Updated 2026-03-22.

Estimated data

Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores are model-assisted estimates derived from source-backed country and city signals. Confidence 70/100.

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