Dataset Viewer
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Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, 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: Column() changed from object to string in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
                  pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
                             ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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.

FEC Campaign Finance Database

356,327,912 rows, ten data tables, four views and 237 dictionary entries. Cycles 2004–2026; 111 loaded sources and nine expected pre-2010 absences. Frozen to the source manifest completed 2026-10-18T08:55:34.351341+00:00; sources have individual modification dates.

Table Rows Columns
candidate_committee_links 74,721 8
candidates 77,581 16
committee_contributions 5,314,838 23
committee_to_committee 48,182,632 22
committees 185,708 16
communication_costs 25,716 26
electioneering_communications 1,711 20
independent_expenditures 618,341 24
individual_contributions 282,086,037 22
operating_expenditures 19,760,627 26

Quick start

INSTALL httpfs; LOAD httpfs;
SET memory_limit='128MiB'; SET threads=1; SET max_temp_directory_size='0B';
ATTACH 'https://huggingface.co/datasets/Nason/fec-database/resolve/aee3ae8b28685104765fb1b1e3ebc2588cb907a3/fec.duckdb' AS fec (READ_ONLY);
SELECT CAND_ID,CAND_NAME FROM fec.candidates WHERE cycle=2026 AND CAND_OFFICE='H' ORDER BY CAND_ID LIMIT 5;

Install/upgrade Python with python -m pip install --upgrade datapond (the examples use 0.1.5), or install released R datapond from CRAN with install.packages("datapond"). R 0.1.1 remains a separate development version. The catalog ID is fec.

The file occupies 19.69 GiB on disk; that is not a RAM estimate. Remote execution can still transfer much of it. Contribution views aggregate large tables, so a final LIMIT does not guarantee a small scan. The SQL above sets limits before attachment; leave process and disk headroom, and expect larger queries to fail when spill is disabled.

Interpretation and source quality

Transaction rows are not unique donors or a complete census of donations. The FEC individual-contributions file includes a subset of reported itemized contributions under rules that changed over time. Entity IDs recur across cycles: join with cycle and aggregate child transactions before combining them.

v_candidate_totals and v_top_donors net specified refund types. v_daily_donations instead excludes refunds and reports positive non-refund transactions; v_pac_to_candidate selects direct 24K/24Z contributions. Their outputs are different measures.

All 37 historical changes have documented parsing/upstream explanations. A strict double-quote CSV interpretation removes balanced wrapper quotes from fourteen 2022 fields (twelve RETIRED occupations, one POLICY occupation, one NOT EMPLOYED CURRENTLY employer). Thirteen separate malformed literal-quote recoveries retain literal quotes. FEC's field description does not specify quote escaping; this is a disclosed interpretation choice, not an official rule. Eight malformed nonblank dates in 2016/2018 remain NULL, with raw tokens/identifiers retained in the provenance. No guessed date repair was applied.

A later source added committee C00962951, CARMELA CONROY VICTORY FUND, after the validated cutoff. It is outside this frozen snapshot. Source outlier dates, inconsistent amounts and prank filings remain; inspect unusual records against filings. Blank fields become NULL; DOUBLE amounts preserve the existing floating-point representation. For net contributions, account for memo rows, conduit transfers and refunds; avoid join fan-out.

The complete typed-row multiset audits, source hash/CRC checks, exact small-table comparisons and metadata verification are documented in provenance. Fingerprints preserve multiplicity but are not a claim of hash injectivity. Dictionary; source repository. The bounded-loader source patch is merged in source PR #1. That source merge does not replace this frozen data artifact.

Underlying records: U.S. Federal Election Commission. Build code: MIT. Published artifact: 21,140,877,312 bytes. SHA-256: 6227fb7c162c3d48a10bb677d2bfd74b21c1acba3aff68eafac2afc49d57a2d4.

The release dictionary retains its prepublication “candidate” heading and historical audit terminology; it describes the published hash above. Its ID join hints are shorthand: include cycle and check child-table multiplicity as described here.

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