Datasets:

lexusdev7
/

regbase-jp-registry-diff-sample

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 30 new columns ({'0.1', 'Unnamed: 16', '5010001048652', '1', '13', '301', '1010001091202', '東京都', '令和８年１０月１日東京都千代田区丸の内一丁目５番１号フランクリン・テンプルトン・ジャパン株式会社（5010001048652）に合併し解散', '2026-10-07', 'Unnamed: 27', '丸の内１丁目５番１号', '101', '21', '11', 'Unnamed: 25', 'Unnamed: 7', 'Unnamed: 26', '千代田区', '2026-11-06', 'ウエスタン・アセット・マネジメント株式会社', 'Unnamed: 12', 'Unnamed: 24', 'Unnamed: 17', '2026-10-07.1', 'ウエスタンアセットマネジメント', '0', '1.1', '2015-10-05', '1000005'}) and 2 missing columns ({'count', 'change_class'}).

This happened while the csv dataset builder was generating data using

hf://datasets/lexusdev7/regbase-jp-registry-diff-sample/data/sample_diff_20261106.csv (at revision 5c5407c7f9bf1cae9e272d3ff2b22e708569522a), ['hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/change_class_split.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/sample_diff_20261106.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/top_municipalities_new.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/top_prefectures_new.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/python3.14/site-packages/datasets/builder.py", line 1856, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 811, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              1: int64
              1010001091202: int64
              21: int64
              0: int64
              2026-11-06: string
              2026-10-07: string
              ウエスタン・アセット・マネジメント株式会社: string
              Unnamed: 7: double
              301: int64
              東京都: string
              千代田区: string
              丸の内１丁目５番１号: string
              Unnamed: 12: double
              13: int64
              101: int64
              1000005: int64
              Unnamed: 16: double
              Unnamed: 17: double
              2026-10-07.1: string
              11: double
              5010001048652: double
              令和８年１０月１日東京都千代田区丸の内一丁目５番１号フランクリン・� (... 81 chars omitted): double
              2015-10-05: string
              1.1: int64
              Unnamed: 24: double
              Unnamed: 25: double
              Unnamed: 26: double
              Unnamed: 27: double
              ウエスタンアセットマネジメント: string
              0.1: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 4957
              to
              {'change_class': Value('string'), '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 1379, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 30 new columns ({'0.1', 'Unnamed: 16', '5010001048652', '1', '13', '301', '1010001091202', '東京都', '令和８年１０月１日東京都千代田区丸の内一丁目５番１号フランクリン・テンプルトン・ジャパン株式会社（5010001048652）に合併し解散', '2026-10-07', 'Unnamed: 27', '丸の内１丁目５番１号', '101', '21', '11', 'Unnamed: 25', 'Unnamed: 7', 'Unnamed: 26', '千代田区', '2026-11-06', 'ウエスタン・アセット・マネジメント株式会社', 'Unnamed: 12', 'Unnamed: 24', 'Unnamed: 17', '2026-10-07.1', 'ウエスタンアセットマネジメント', '0', '1.1', '2015-10-05', '1000005'}) and 2 missing columns ({'count', 'change_class'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/lexusdev7/regbase-jp-registry-diff-sample/data/sample_diff_20261106.csv (at revision 5c5407c7f9bf1cae9e272d3ff2b22e708569522a), ['hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/change_class_split.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/sample_diff_20261106.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/top_municipalities_new.csv', 'hf://datasets/lexusdev7/regbase-jp-registry-diff-sample@5c5407c7f9bf1cae9e272d3ff2b22e708569522a/data/top_prefectures_new.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.

change_class string	count int64
new	1,404
changed	895
closed	298
revival	20
other	0
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End of preview.

YAML Metadata Warning:The task_categories "tabular-question-answering" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

RegBase — Japan Corporate Registry Daily Diff · Free Sample (2026-11-06)

Japan's National Tax Agency (国税庁) publishes the national corporate registry as open data: every registered company's corporate number (法人番号), name, entity type and address. What it does not publish in a usable shape is what changed today. RegBase cuts the registry's daily diff — the registrations that were created, changed, or removed on a single day — into a clean, documented, verifiable package.

This dataset is the free sample of that work: the first 100 records of the 2026-11-06 registry diff, plus the full day's census summary.

What happened on 2026-11-06

The complete diff for the 2026-11-06 update contained 2,617 records:

Change class	Count
New registrations	1,404
Changed registrations	895
Closed registrations	298
Revived registrations	20
Total	2,617

New registrations by prefecture (top 3): Tokyo 370, Osaka 128, Kanagawa 95. By municipality (top 3): Minato City, Tokyo 65; Chuo City, Tokyo 40; Chiyoda City, Tokyo 32. Cross-checked against a 3,808-company listed-company master, 6 of the day's records belonged to listed companies — all of them "changed". Full top-10 tables and the complete census are in data/.

Files

File	Contents
`data/sample_diff_20261106.csv`	First 100 records of the 2026-11-06 diff. UTF-8, no header row, 30 columns (schema below). Byte-identical to the first 100 records of the full product file.
`data/census_summary.json`	Full census of the day's 2,617 records: counts by change class, process code, prefecture, entity type, and top municipalities for new registrations.
`data/change_class_split.csv`	Record counts by change class (new / changed / closed / revival / other).
`data/top_prefectures_new.csv`	Top 10 prefectures by new registrations.
`data/top_municipalities_new.csv`	Top 10 municipalities by new registrations.

Schema (30 columns, in order)

sequence_number — row sequence within the source publication
corporate_number — 13-digit corporate number (法人番号); import as text to keep leading zeros
process_code — registry process code
correction_code — correction flag
update_date — date the change was published
change_date — date of the underlying change
name — registered name (Japanese)
name_image_id — name image reference
entity_type — entity type code (e.g. 301 = stock company)
prefecture — prefecture (Japanese)
city — city / ward / town / village (Japanese)
street_address — street address (Japanese)
address_image_id — address image reference
prefecture_code — 2-digit prefecture code
city_code — municipality code
postal_code — postal code
address_outside_japan — address outside Japan, if any
reserved_empty — reserved (empty)
closing_date — registry closing date, if closed
closing_reason — closing reason code, if closed
succeeded_corporate_number — successor corporate number, if any
change_cause — cause of change
assignment_date — date the corporate number was assigned
latest_history_flag — latest-history flag
name_en — registered name (English), where published
prefecture_en — prefecture (English)
city_en — city (English)
address_outside_japan_en — address outside Japan (English)
name_kana — registered name (kana)
non_display_flag — non-display flag

What this data is good for

Building or refreshing a Japan B2B sales list
Catching newly incorporated companies on the day they register
Market and competitor research on Japanese companies
A first-pass check of a counterparty's registered details

Limitations — please read

One day only. This sample covers the 2026-11-06 update. A single day shows what happened that day; it cannot show trends.
The counts are the records that changed that day, not the total number of companies in Japan.
"Closed" means the registry record was closed that day. It is not a count of all business closures in Japan.
The registry has no industry/sector column. Records cannot be filtered by industry.
Record accuracy follows the source publication (National Tax Agency).

The full products

This sample is the top of the RegBase funnel. The complete, verifiable packages — each shipped with a signed file list (a manifest carrying a digital stamp, Ed25519; if any file changes, the stamp stops matching) so you can confirm the files are byte-for-byte what RegBase produced:

Registry Diff Snapshot — one full day of registry changes (CSV + summary + signed manifest). ¥2,980. → Product page: BOOTH (¥2,980) — https://regbase.booth.pm/items/9113399 · Coconala (¥3,000) — https://coconala.com/services/4493403
Diff Feed — the same diff, delivered on a continuing basis. → Details: https://apify.com/regbase/jp-diff-feed
Signed verification (regbase-record/1) — per-record signed verification built on the same manifest format. → Details: https://regbase.local-connect-design.trade/verify

A free sample of the snapshot's summary (counts and the column reference) is also available before purchase — see the product page above.

License

The underlying registry data is public data published by Japan's National Tax Agency (法人番号公表サイト) as open data; its use follows the source's published terms. RegBase's own work in this dataset — the record selection, the census summaries, and this documentation — is the compilation layer described above; please credit RegBase and the National Tax Agency when reusing the summary files. The sample records themselves remain source data: consult the National Tax Agency's terms for redistribution of registry records.

Source

National Tax Agency, Corporate Number Publication Site (法人番号公表サイト), daily diff for the 2026-11-06 update.
Listed-company cross-check: the code list from EDINET, Japan's official online disclosure system for listed companies (3,808 listed filers), as of 2026-11-07.
Zenodo deposit of this sample (archival copy with DOI): https://doi.org/10.5281/zenodo.24046548

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