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Departamento de Nueve de Julio
City in Chaco, Argentina
Overview
Departamento de Nueve de Julio, centered on the city of Villa Ángela, is a welcoming locality in southern Chaco province. Known for its agricultural roots and tranquil lifestyle, the area offers a blend of small-town charm and everyday conveniences.
Geographic Context
Jurisdiction
Argentina
Province
Chaco
Population
12,514
Time Zone
America/Argentina/Buenos_Aires
Coordinates
-26.95°, -61.28°
Key Metrics
Safety Score · estimate
55
Female Safety
48
LGBTQ+ Safety
35
Traffic Safety
40
Food Safety
65
Monthly Cost · estimate
$606
Local Cost
$425
Local Income
$220
Cashless
22
English
10
Temperature
22.4°C
Summer Avg
27.9°C
Winter Avg
16.1°C
Record High
45.5°C
Record Low
-1.9°C
Humidity
64%
Precipitation
1060 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
CNT
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: 54/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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