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Premium Geo-Datafor Modern Applications
High-precision postal codes, cities, and geographic datasets — ready to integrate into your product in minutes.
CSV · JSON · Parquet · GeoJSON·Commercial license·12 months of updates
Numbers that matter
Built for production workloads — every record is verified and enriched.
28,650
German PLZ records
99.7%
Coordinate accuracy
250k+
Cities worldwide
Weekly
Data updates
Developer Experience
Easy to integrate
Standard formats that drop into your existing stack. No proprietary tools required.
import pandas as pd
# Load the PLZ Premium dataset
df = pd.read_csv('plz_premium.csv')
# Find all postal codes in Bavaria
bavaria = df[df['bundesland'] == 'Bayern']
print(f"PLZ in Bavaria: {len(bavaria)}")
# Closest PLZ to a given coordinate
from geopy.distance import geodesic
munich = (48.1351, 11.5820)
df['distance_km'] = df.apply(
lambda r: geodesic(munich, (r['lat'], r['lng'])).km,
axis=1
)
closest = df.loc[df['distance_km'].idxmin()]
print(f"Closest to Munich: PLZ {closest['plz']} ({closest['distance_km']:.1f} km)")Open Source
10% of our data is open
Sample datasets, schema definitions, and helper tools live on GitHub — for everyone, forever.
- praevisode/plz-sample★ 124
1,000 sample German postal codes (CC-BY-4.0)
- praevisode/cities-toolkit★ 58
CLI to validate and enrich your own geo datasets
- praevisode/schema-definitions★ 37
JSON Schemas for all our data packages
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