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Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'n_ixps', 'has_ixp', 'total_peers'}) and 5 missing columns ({'n_peers', 'ixp_name', 'net_count', 'ix_id', 'city'}).
This happened while the csv dataset builder was generating data using
hf://datasets/electricsheepafrica/africa-ixp-routing-exposure/ds3_ixp_country_coverage.csv (at revision 38da0ab20ede606bc8c3024ef491738f9e87e90e), [/tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
country_code: string
country: string
n_ixps: int64
total_peers: int64
has_ixp: bool
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 835
to
{'ix_id': Value('int64'), 'ixp_name': Value('string'), 'country_code': Value('string'), 'country': Value('string'), 'city': Value('string'), 'n_peers': Value('int64'), 'net_count': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1348, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'n_ixps', 'has_ixp', 'total_peers'}) and 5 missing columns ({'n_peers', 'ixp_name', 'net_count', 'ix_id', 'city'}).
This happened while the csv dataset builder was generating data using
hf://datasets/electricsheepafrica/africa-ixp-routing-exposure/ds3_ixp_country_coverage.csv (at revision 38da0ab20ede606bc8c3024ef491738f9e87e90e), [/tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ix_id int64 | ixp_name string | country_code string | country string | city string | n_peers int64 | net_count int64 |
|---|---|---|---|---|---|---|
592 | NAPAfrica IX Johannesburg | ZA | South Africa | Johannesburg | 768 | 548 |
597 | NAPAfrica IX Cape Town | ZA | South Africa | Cape Town | 368 | 281 |
129 | JINX | ZA | South Africa | Johannesburg | 252 | 197 |
969 | NAPAfrica IX Durban | ZA | South Africa | Durban | 161 | 137 |
236 | KIXP - Nairobi | KE | Kenya | Nairobi | 148 | 133 |
488 | IXPN Lagos | NG | Nigeria | Lagos | 142 | 117 |
344 | CINX | ZA | South Africa | Cape Town | 136 | 117 |
610 | DINX | ZA | South Africa | Durban | 115 | 100 |
2,381 | AMS-IX Lagos | NG | Nigeria | Lagos | 60 | 50 |
4,231 | LINX Nairobi | KE | Kenya | Nairobi | 58 | 54 |
4,653 | LINX Mombasa | KE | Kenya | Mombasa | 49 | 47 |
3,403 | NAPAfrica MAPS Johannesburg | ZA | South Africa | Johannesburg | 43 | 26 |
4,000 | AF-CIX | NG | Nigeria | Lagos | 41 | 39 |
2,362 | KIXP-Mombasa | KE | Kenya | Mombasa | 38 | 36 |
361 | TIX Tanzania - Dar es Salaam | TZ | Tanzania | Dar es Salaam | 33 | 32 |
3,812 | EG-IX | EG | Egypt | Cairo | 31 | 19 |
422 | UIXP | UG | Uganda | Kampala | 28 | 25 |
1,007 | angonix | AO | Angola | Luanda | 27 | 24 |
694 | GIXA | GH | Ghana | Accra | 27 | 24 |
1,508 | MIXP | MU | Mauritius | Ebene | 25 | 21 |
628 | KINIX | CD | Congo (Kinshasa) | Kinshasa | 25 | 23 |
967 | AMS-IX Djibouti | DJ | Djibouti | Djibouti | 21 | 20 |
4,259 | Accra Internet Exchange LBG | GH | Ghana | Accra | 21 | 21 |
421 | Angola IXP | AO | Angola | Luanda | 19 | 14 |
528 | MOZIX | MZ | Mozambique | Maputo | 18 | 18 |
1,201 | TIX Tanzania - Arusha (AIXP) | TZ | Tanzania | Arusha | 17 | 16 |
3,302 | PyramIX | EG | Egypt | Cairo | 17 | 18 |
1,870 | IXPN Abuja | NG | Nigeria | Abuja | 17 | 17 |
1,032 | RINEX | RW | Rwanda | Kigali | 17 | 15 |
2,729 | BFIX Ouagadougou | BF | Burkina Faso | Ouagadougou | 16 | 16 |
810 | CIVIX | CI | Côte d'Ivoire | Abidjan | 15 | 14 |
3,843 | BGP.Exchange - Johannesburg | ZA | South Africa | Johannesburg | 14 | 14 |
2,722 | LUBIX | CD | Congo (Kinshasa) | Lubumbashi | 14 | 12 |
4,148 | NMBINX | ZA | South Africa | Gqeberha | 14 | 12 |
3,633 | GOMIX | CD | Congo (Kinshasa) | Goma | 13 | 11 |
615 | Lusaka Internet Exchange Point | ZM | Zambia | Lusaka | 12 | 12 |
727 | MIX-BT | MW | Malawi | Blantyre | 10 | 10 |
2,541 | CAMIX Douala | CM | Cameroon | Douala | 10 | 10 |
4,081 | N'Djamena IX | TD | Chad | N'Djamena | 10 | 9 |
1,046 | CGIX-BZV | CG | Congo (Brazzaville) | Brazzaville | 9 | 9 |
2,552 | BDIXP | BI | Burundi | Bujumbura | 9 | 9 |
2,624 | TIX Tanzania - Dodoma | TZ | Tanzania | Dodoma | 9 | 8 |
3,561 | Douala-IX | CM | Cameroon | Douala | 8 | 8 |
2,388 | TGIX | TG | Togo | Lomé | 8 | 8 |
1,776 | GABIX | GA | Gabon | Libreville | 8 | 8 |
4,122 | ACIX | CD | Congo (Kinshasa) | Kinshasa | 7 | 6 |
4,769 | LINX Accra | GH | Ghana | Accra | 7 | 6 |
4,920 | HubSIX | SN | Senegal | Dakar | 6 | 5 |
4,037 | CV-IXP | CV | Cabo Verde | Praia | 6 | 5 |
2,414 | IXPN Kano | NG | Nigeria | Kano | 6 | 6 |
922 | IXP Namibia | null | Namibia | Windhoek | 6 | 6 |
3,401 | BFIX Bobo-Dioulasso | BF | Burkina Faso | Bobo-Dioulasso | 6 | 6 |
3,884 | NAPAfrica MAPS Cape Town | ZA | South Africa | Cape Town | 6 | 5 |
2,208 | TIX Tanzania - Zanzibar | TZ | Tanzania | Zanzibar | 6 | 6 |
274 | CAIX | EG | Egypt | Cairo | 5 | 5 |
1,335 | MGIX | MG | Madagascar | Antananarivo | 5 | 5 |
1,017 | BENIN-IX | BJ | Benin | Cotonou | 5 | 5 |
3,734 | Asteroid Nairobi | KE | Kenya | Nairobi | 5 | 5 |
4,446 | LIONEX1 | MW | Malawi | Lilongwe | 5 | 4 |
1,574 | TIX Tanzania - Mwanza | TZ | Tanzania | Mwanza | 5 | 5 |
2,665 | MLIX | ML | Mali | Bamako | 5 | 5 |
2,554 | CAMIX Yaounde | CM | Cameroon | Yaoundé | 4 | 4 |
4,892 | Michcom-IX | SL | Sierra Leone | Freetown | 4 | 3 |
2,320 | SIXP Sudan | SD | Sudan | Khartoum | 4 | 4 |
1,105 | TunIXP | TN | Tunisia | Tunis | 4 | 4 |
2,861 | JINX Voice | ZA | South Africa | Johannesburg | 4 | 4 |
2,520 | IXP-GUINEE | GN | Guinea | Conakry | 4 | 4 |
4,573 | DarIX | TZ | Tanzania | Dar es Salaam | 3 | 3 |
3,117 | FEZIX | MA | Morocco | Fez | 3 | 3 |
2,682 | SIXP Gambia | GM | Gambia | Serekunda | 3 | 2 |
2,713 | CAS-IX | MA | Morocco | Casablanca | 3 | 3 |
5,015 | Lesotho Internet Exchange Point | LS | Lesotho | Maseru | 3 | 3 |
4,357 | Addix | ET | Ethiopia | Addis Ababa | 3 | 3 |
2,415 | IXPN Port Harcourt | NG | Nigeria | Port Harcourt | 2 | 2 |
3,097 | TIX Tanzania - Mbeya | TZ | Tanzania | Mbeya | 2 | 2 |
2,815 | Asteroid Mombasa | KE | Kenya | Mombasa | 2 | 2 |
2,617 | Harare IX | ZW | Zimbabwe | Harare | 2 | 2 |
262 | SISPA | SZ | Eswatini | Swaziland | 0 | 0 |
1,409 | BINX | BW | Botswana | Gaborone | 0 | 0 |
2,899 | CINX Voice | ZA | South Africa | Cape Town | 0 | 0 |
2,410 | SoIXP | SO | Somalia | Mogadishu | 0 | 0 |
4,293 | CGIX-PNR | CG | Congo (Brazzaville) | Pointe-Noire | 0 | 0 |
4,413 | Asteroid Nairobi-IX | KE | Kenya | Nairobi | 0 | 0 |
4,450 | Tripoli IXP | LY | Libya | Tripoli | 0 | 0 |
4,724 | BGP.Exchange - Nairobi | KE | Kenya | Nairobi | 0 | 0 |
4,898 | PLUGINS IX | KE | Kenya | NAIROBI | 0 | 0 |
5,002 | Digital Delta IX | BW | Botswana | Gaborone | 0 | 0 |
null | null | DZ | Algeria | null | null | null |
null | null | CF | Central African Republic | null | null | null |
null | null | KM | Comoros | null | null | null |
null | null | GQ | Equatorial Guinea | null | null | null |
null | null | ER | Eritrea | null | null | null |
null | null | GW | Guinea-Bissau | null | null | null |
null | null | LR | Liberia | null | null | null |
null | null | MR | Mauritania | null | null | null |
null | null | NE | Niger | null | null | null |
null | null | ST | São Tomé and Príncipe | null | null | null |
null | null | SC | Seychelles | null | null | null |
null | null | SS | South Sudan | null | null | null |
null | null | ZA | South Africa | null | null | null |
Africa IXP & Routing Exposure | Africa (Electric Sheep Africa metadata inventory)
Size category: n<1K - Formats: not declared - Sector: governance_security - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
Dataset context from the existing Hugging Face card: Africa IXP & Routing Exposure Electric Sheep Africa · Post-Quantum Cryptographic Exposure cluster · dataset DS-3 · v0.1 African digital infrastructure is being recorded by state actors today under the assumption it will be decryptable once quantum computers arrive (2030–2035 per NIST/NCSC/ENISA). This dataset is one dimension of the Africa-specific evidence for that claim. What this dataset answers Which African countries lack local internet exchange points and… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-ixp-routing-exposure |
| Sector | governance_security |
| Topic tags | cryptography, post-quantum, pqc, security, harvest-now-decrypt-later, tls, cybersecurity, ixp, peering, bgp, routing, internet-exchange |
| Modalities | not declared |
| Formats | not declared |
| Size category | n<1K |
| Countries | Africa-wide or source-defined African coverage |
| ISO3 coverage | not declared |
| Last modified on HF | 2026-05-29 14:40:03+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-ixp-routing-exposure")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: country, upstream_publisher, modality, format.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: Electric Sheep Africa metadata inventory
- Publisher/source attribution: Public dataset metadata
- License: CC BY 4.0
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_ixp_routing_exposure_2026,
title = {Africa IXP & Routing Exposure | Africa (Electric Sheep Africa metadata inventory)},
author = {Public dataset metadata},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure}}
}
License
Released under CC BY 4.0.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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