usc-billstatus / README.md
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metadata
configs:
  - config_name: default
    data_files:
      - split: '108'
        path: data/usc-108-billstatus.parquet
      - split: '109'
        path: data/usc-109-billstatus.parquet
      - split: '110'
        path: data/usc-110-billstatus.parquet
      - split: '111'
        path: data/usc-111-billstatus.parquet
      - split: '112'
        path: data/usc-112-billstatus.parquet
      - split: '113'
        path: data/usc-113-billstatus.parquet
      - split: '114'
        path: data/usc-114-billstatus.parquet
      - split: '115'
        path: data/usc-115-billstatus.parquet
      - split: '116'
        path: data/usc-116-billstatus.parquet
      - split: '117'
        path: data/usc-117-billstatus.parquet
      - split: '118'
        path: data/usc-118-billstatus.parquet
license: mit
language:
  - en

Dataset Description

This dataset is part of a family of datasets that provide convenient access to congressional data from the US Government Publishing Office via the GovInfo Bulk Data Repository. GovInfo provides bulk data in xml format. The raw xml files were downloaded using the congress repo. Further processing was done using the legisplain legisplain repo.

Hyperdemocracy Datasets

BILLSTATUS (metadata for congresses 108-118)

These xml files contain metadata about each bill and pointers to different xml files that contain various text versions of each bill.

Column Descriptions

Hyperdemocracy column descriptions.

Column Description
legis_id a unique ID for each bill ({congress_num}-{legis_type}-{legis_num})
congress_num the congress number for the bill
legis_type one of [hr, hres, hconres, hjres, s, sres, sconres, sjres] (see govinfo - types of legislation)
legis_num bills in each congress and of each type get an incrementing number as part of their ID
bulk_path XML file path during bulk download
lastmod lastmod date during bulk download
bs_xml contents of billstatus XML file
bs_json billstatus XML parsed into JSON

See the BILLSTATUS XML User Guide for descriptions of the other columns.

Examples

The dataset is broken into splits (one split per congress number).

from datasets import load_dataset

# load each split into a `DatasetDict` keyed on congress number
dsd = load_dataset(path="hyperdemocracy/usc-billstatus")

# load a single congress number into a `Dataset`
ds = load_dataset(path="hyperdemocracy/usc-billstatus", split=117)

# load all congress numbers into a single `Dataset`
ds = load_dataset(path="hyperdemocracy/usc-billstatus", split="all")

Congress Number to Date Mapping

Congress Number Years Metadata Text
118 2023-2024 True True
117 2021-2022 True True
116 2019-2020 True True
115 2017-2018 True True
114 2015-2016 True True
113 2013-2014 True True
112 2011-2012 True False
111 2009-2010 True False
110 2007-2008 True False
109 2005-2006 True False
108 2003-2004 True False