Datasets:

biglam
/

hansard_speech

	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""
	A dataset containing every speech in the House of Commons from May 1979-July 2020.
	"""

	import json
	import os
	import time
	import pandas as pd
	from datetime import datetime
	import datasets

	_CITATION = """@misc{odell, evan_2021,
	title={Hansard Speeches 1979-2021: Version 3.1.0},
	DOI={10.5281/zenodo.4843485},
	abstractNote={<p>Full details are available at <a href="https://evanodell.com/projects/datasets/hansard-data">https://evanodell.com/projects/datasets/hansard-data</a></p> <p><strong>Version 3.1.0 contains the following changes:</strong></p> <p>- Coverage up to the end of April 2021</p>},
	note={This release is an update of previously released datasets. See full documentation for details.},
	publisher={Zenodo},
	author={Odell, Evan},
	year={2021},
	month={May} }
	"""

	_DESCRIPTION = """
	A dataset containing every speech in the House of Commons from May 1979-July 2020.
	"""

	_HOMEPAGE = "https://evanodell.com/projects/datasets/hansard-data/"

	_LICENSE = "Creative Commons Attribution 4.0 International License"

	_URLS = {
	"csv": "https://zenodo.org/record/4843485/files/hansard-speeches-v310.csv.zip?download=1",
	"json": "https://zenodo.org/record/4843485/files/parliamentary_posts.json?download=1",
	}

	fields = [
	"id",
	"speech",
	"display_as",
	"party",
	"constituency",
	"mnis_id",
	"date",
	"time",
	"colnum",
	"speech_class",
	"major_heading",
	"minor_heading",
	"oral_heading",
	"year",
	"hansard_membership_id",
	"speakerid",
	"person_id",
	"speakername",
	"url",
	"parliamentary_posts",
	"opposition_posts",
	"government_posts",
	]

	logger = datasets.utils.logging.get_logger(__name__)


	class HansardSpeech(datasets.GeneratorBasedBuilder):
	"""A dataset containing every speech in the House of Commons from May 1979-July 2020."""

	VERSION = datasets.Version("3.1.0")

	def _info(self):
	features = datasets.Features(
	{
	"id": datasets.Value("string"),
	"speech": datasets.Value("string"),
	"display_as": datasets.Value("string"),
	"party": datasets.Value("string"),
	"constituency": datasets.Value("string"),
	"mnis_id": datasets.Value("string"),
	"date": datasets.Value("string"),
	"time": datasets.Value("string"),
	"colnum": datasets.Value("string"),
	"speech_class": datasets.Value("string"),
	"major_heading": datasets.Value("string"),
	"minor_heading": datasets.Value("string"),
	"oral_heading": datasets.Value("string"),
	"year": datasets.Value("string"),
	"hansard_membership_id": datasets.Value("string"),
	"speakerid": datasets.Value("string"),
	"person_id": datasets.Value("string"),
	"speakername": datasets.Value("string"),
	"url": datasets.Value("string"),
	"government_posts": datasets.Sequence(datasets.Value("string")),
	"opposition_posts": datasets.Sequence(datasets.Value("string")),
	"parliamentary_posts": datasets.Sequence(datasets.Value("string")),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	temp_dir = dl_manager.download_and_extract(_URLS["csv"])
	csv_file = os.path.join(temp_dir, "hansard-speeches-v310.csv")
	json_file = dl_manager.download(_URLS["json"])
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepaths": [csv_file, json_file], "split": "train",},
	),
	]

	def _generate_examples(self, filepaths, split):
	logger.warn("\nThis is a large dataset. Please be patient")
	json_data = pd.read_json(filepaths[1])
	csv_data_chunks = pd.read_csv(filepaths[0], chunksize=50000, dtype="object")
	for data_chunk in csv_data_chunks:
	data_chunk.fillna("", inplace=True)
	for _, row in data_chunk.iterrows():
	data_point = {}
	for field in fields[:-3]:
	data_point[field] = str(row[field]) if row[field] else ""
	parl_post_list = []
	if data_point["mnis_id"] and data_point["date"]:
	speech_dt = data_point["date"] + " 00:00:00"
	try:
	parl_posts = json_data[
	(json_data["mnis_id"] == int(data_point["mnis_id"]))
	& (json_data["date"] == speech_dt)
	]["parliamentary_posts"]
	if len(parl_posts) > 0:
	parl_posts = parl_posts.iloc[0]
	for item in parl_posts:
	parl_post_list.append(item["parl_post_name"])
	except Exception as e:
	logger.warn(
	f"Data could not be fetched for mnis_id: {data_point['mnis_id']}, date: {data_point['date']}\nError: {repr(e)}"
	)
	opp_post = []
	gov_post = []
	data_point["government_posts"] = gov_post
	data_point["opposition_posts"] = opp_post
	data_point["parliamentary_posts"] = parl_post_list
	yield data_point["id"], data_point