The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 345, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Federal Judges Biographical Database (FJC)
Every Article III federal judge since 1789 from the Federal Judicial Center's Biographical
Directory: demographics, every appointment with its nomination -> confirmation -> commission
timeline, chief-judge and senior-status dates, education, career, and other federal judicial
service. Six normalised tables joined on nid, plus v_current_judges.
Source snapshot: November 8, 2026. Latest commission: October 22, 2026.
Chief-judge year columns and raw birth/degree-year text
preserve source precision; no first-of-year dates are invented.
Appointment counts are not distinct-judge counts. v_current_judges is current only as of this snapshot.
Within this database join on nid; CourtListener judges.fjc_id joins this directory's judges.jid.
37,797 rows across 6 tables.
| Table | Description | Row Count | Column Count |
|---|---|---|---|
professional_career |
One row per professional-career entry as written by the FJC (clerkships, practice, prior judgeships), in sequence | 19,330 | 4 |
education |
One row per degree: school, degree, year | 8,159 | 7 |
federal_judicial_service |
One row per Article III appointment: court, appointing president and party, ABA rating, seat, nomination, committee, Senate vote and confirmation dates, commission date, chief-judge service, senior status, termination and reason | 4,777 | 34 |
judges |
One row per Article III judge, 1789-present: name, birth and death date/place, gender, race or ethnicity (FJC Biographical Directory) | 4,077 | 19 |
other_nominations_recess |
One row per unsuccessful nomination or recess appointment, as written by the FJC | 836 | 4 |
other_federal_judicial_service |
One row per non-Article III federal judicial post (magistrate judge, bankruptcy judge, territorial court ...) | 618 | 5 |
Query it remotely
INSTALL httpfs; LOAD httpfs;
ATTACH 'https://huggingface.co/datasets/Nason/fjc-judges-database/resolve/main/fjc-judges.duckdb' AS fjc_judges (READ_ONLY);
SELECT appointing_president, COUNT(*) AS appointments, ROUND(AVG(confirmation_date - nomination_date)) AS avg_days_to_confirm
FROM fjc_judges.federal_judicial_service WHERE nomination_date >= '1981-01-01'
GROUP BY 1 ORDER BY MIN(nomination_date);
Or with the datapond packages: pip install datapond / install.packages("datapond").
Build pipeline and caveats: https://github.com/ian-nason/fjc-judges-database Source: https://www.fjc.gov/history/judges (public domain).
Installation and query limits
Install or upgrade Python datapond (tested 0.1.5), or use CRAN R datapond 0.1.0. R 0.1.1 is a separate development version. Remote queries run on your machine. File size is disk storage, not required RAM; selected columns reduce transfer, but filters and a final LIMIT do not guarantee a small scan. A 128 MiB setting limits DuckDB's buffer pool, not the whole Python/R process. Larger queries can fail with spill disabled. Download only when you have room for the file, temporary download bytes and any existing copy.
Count appointment rows separately from distinct judges. Join within this directory on nid; for CourtListener use CourtListener fjc_id = judges.jid.
R with DBI and duckdb
Install the dependencies once with install.packages(c("DBI", "duckdb")).
library(DBI)
con <- dbConnect(duckdb::duckdb())
dbExecute(con, "INSTALL httpfs")
dbExecute(con, "LOAD httpfs")
dbExecute(con, "ATTACH 'https://huggingface.co/datasets/Nason/fjc-judges-database/resolve/main/fjc-judges.duckdb' AS fjc_judges (READ_ONLY)")
dbGetQuery(con, "SELECT appointing_president, nomination_date FROM fjc_judges.federal_judicial_service LIMIT 5")
dbDisconnect(con, shutdown = TRUE)
Queries run on your machine. A LIMIT does not guarantee a small scan.
Reproduce this snapshot
The November 8 source bundle contains the exact build code, pinned public source CSVs, and reproduction instructions. Check the per-file manifest before rebuilding. The GitHub revision in the provenance is a base revision; the bundle includes the release-specific working changes. Rebuilding should reproduce the logical tables, not necessarily byte-identical DuckDB files.
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