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README.md
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@@ -27,7 +27,7 @@ A free, monthly dataset of the **routed IPv4 address space** at **`/24` granular
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| Group | Fields |
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| --- | --- |
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| **Geolocation** | `CountryCode`, `ContinentCode`, `IsInEU`, `RegionName` (ISO 3166-2), `CityName`, `Latitude`, `Longitude`, `TimeZone` |
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| **Network / ASN** | `ASNID`, `ASNName`, `ASNOrg`, `ASNDomain`, `ASNType` (ISP / hosting / business / education / government) |
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| **Ownership (WHOIS)** | `Company`, `CompanyCountry`, `WhoisNetName`, `AbuseContact` |
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| **Registry (RIR)** | `RIR` (ARIN/RIPE/APNIC/LACNIC/AFRINIC), `RIRAllocationDate`, `RIRStatus` |
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@@ -47,14 +47,14 @@ Key column: `IP24Prefix` (e.g. `8.8.8.0/24`).
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# pandas — read straight from the Hub
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import pandas as pd
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df = pd.read_parquet(
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"hf://datasets/ProdIPData/geoip-locations/prefix_attributes_2026-
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)
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# duckdb (query without loading it all into memory)
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import duckdb
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duckdb.sql("""
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SELECT CountryCode, COUNT(*) AS prefixes
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FROM 'prefix_attributes_2026-
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GROUP BY 1 ORDER BY 2 DESC LIMIT 10
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""").show()
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## Limitations
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- Geolocation is **derived** from MaxMind, the RIRs and other upstream sources merged monthly — it is a **snapshot, not real-time**, and only as accurate as those sources.
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- **Low-confidence blocks fall back to country-level centroids.** For example `8.8.8.8` resolves to the US geographic centre, not Mountain View.
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- `/24` granularity: attributes describe the block, not individual hosts.
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## Attribution
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@@ -79,4 +79,4 @@ Please credit **ProdIPData / GeoIP Locations (geoiplocations.com)** under **CC B
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- Website: https://geoiplocations.com
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- Downloads: https://geoiplocations.com/downloads.html
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- Methodology: https://geoiplocations.com/methodology.html
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| Group | Fields |
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| --- | --- |
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+
| **Geolocation** | `CountryCode`, `ContinentCode`, `IsInEU`, `RegionName` (ISO 3166-2), `CityName`, `Latitude`, `Longitude`, `AccuracyRadius`, `TimeZone` |
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| **Network / ASN** | `ASNID`, `ASNName`, `ASNOrg`, `ASNDomain`, `ASNType` (ISP / hosting / business / education / government) |
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| **Ownership (WHOIS)** | `Company`, `CompanyCountry`, `WhoisNetName`, `AbuseContact` |
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| **Registry (RIR)** | `RIR` (ARIN/RIPE/APNIC/LACNIC/AFRINIC), `RIRAllocationDate`, `RIRStatus` |
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# pandas — read straight from the Hub
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import pandas as pd
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df = pd.read_parquet(
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"hf://datasets/ProdIPData/geoip-locations/prefix_attributes_2026-07_iso-ALL.parquet"
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)
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# duckdb (query without loading it all into memory)
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import duckdb
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duckdb.sql("""
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SELECT CountryCode, COUNT(*) AS prefixes
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FROM 'prefix_attributes_2026-07_iso-ALL.parquet'
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GROUP BY 1 ORDER BY 2 DESC LIMIT 10
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""").show()
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## Limitations
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- Geolocation is **derived** from MaxMind, the RIRs and other upstream sources merged monthly — it is a **snapshot, not real-time**, and only as accurate as those sources.
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- **Low-confidence blocks fall back to country-level centroids.** For example `8.8.8.8` resolves to the US geographic centre, not Mountain View. The `AccuracyRadius` field (in km) now makes this precision **explicit**, so country-level fallbacks are visible rather than implied.
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- `/24` granularity: attributes describe the block, not individual hosts.
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## Attribution
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- Website: https://geoiplocations.com
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- Downloads: https://geoiplocations.com/downloads.html
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- Methodology: https://geoiplocations.com/methodology.html
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