clquestions is an R package for downloading data from the UK Parliament's Written Questions API. This package has been developed principally to support work on Parliamentary data in the House of Commons Library but it may be useful to other researchers working with this data. This package is still in active development and the API may evolve over time.
The package provides sets of functions for retrieving data from different endpoints of the written questions and statements API and returning the data as a tibble. The package does not aim to exhaustively expose every possible parameter of the API, but is focussed on downloading key datasets than can be further explored, transformed and combined with other data in R. To help with using parts of the API that are not explicitly covered, the package also provides a lower level function that allow you to retrieve data from the API with different parameters as native R data structures.
Install from Github with using remotes.
install.packages("remotes")
remotes::install_github("houseofcommonslibrary/clquestions")All functions have four optional arguments: from_date, to_date, on_date and house which can be used to filter the data returned from the API based on the date of a question or answer and the house it was tabled.
The on_date argument is a convenience that sets the from_date and to_date to the same given date. The on_date has priority: if the on_date is set, the from_date and to_date are ignored. The values for these arguments can be either a Date or a string specifying a date in ISO 8601 format ("YYYY-MM-DD"). By default the date arguments are set to NULL meaning that data form the API is not filtered by question or answer date.
The date arguments filter data retrieved by the API based on whether the function is aimed at _questions or _answers. For example, in fetch_written_questions the date filtering will be against the date of when the question was tabled, whereas fetch_written_answers will be against the date of when a question was answered.
Functions ending in _questions are more inclusive and will return questions regardless if they have been answered or not.
The house argument accepts "c", "C", "Commons", "l", "L", "Lords" to indicate which house the written question was tabled in. By default it is set to NULL and returns data from both houses.
There are two additional arguments which must be supplied for each function: take and summary.
take is an integer used to tell the API how many records should be retrieved. Records are taken newest to oldest, e.g. if take = 1000 (the default) then up to 1,000 of the most recent records are retrieved from the API. If there are fewer records available than the value of take all records will be retrieved. A warning appears if there are more records available than the value of take.
summary is a boolean indicating whether to exclude nested and empty columns in the results. The default is TRUE.
clquestions::fetch_written_questions(
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)
clquestions::fetch_written_answers(
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written question and answer, with one row per question and answer.
This dataframe contains summary details for each written question and answer, such as the question/answer date, question/answer text and details on the member who asked/answered the question.
clquestions::fetch_written_questions_body(
body_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)
clquestions::fetch_written_answers_body(
body_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written question and answer by the body responsible for responding, with one row per question and answer.
body_id is an integer representing the ID of the body responsible for answering the written question. Only one integer can be supplied.
This dataframe contains summary details for each written question and answer, such as the question/answer date, question/answer text and details on the member who asked/answered the question.
Use get_answer_bodies() for a list of all available answer bodies and their corresponding ID numbers.
clquestions::fetch_written_questions_member(
member_mnis_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)
clquestions::fetch_written_answers_member(
member_mnis_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written question and answer by the member asking or answering the question, with one row per question and answer.
member_mnis_id is an integer representing the MNIS ID for Commons and Lords members.
This dataframe contains summary details for each written question and answer, such as the question/answer date, question/answer text and details on the member who asked/answered the question.
All functions have four optional arguments: from_date, to_date, on_date and house which can be used to filter the data returned from the API based on the date of a statement and the house it was made.
The on_date argument is a convenience that sets the from_date and to_date to the same given date. The on_date has priority: if the on_date is set, the from_date and to_date are ignored. The values for these arguments can be either a Date or a string specifying a date in ISO 8601 format ("YYYY-MM-DD"). By default the date arguments are set to NULL meaning that data form the API is not filtered by statement date.
The house argument accepts "c", "C", "Commons", "l", "L", "Lords" to indicate which house the written statement was made in. By default it is set to NULL and returns data from both houses.
There are two additional arguments which must be supplied for each function: take and summary.
take is an integer used to tell the API how many records should be retrieved. Records are taken newest to oldest, e.g. if take = 1000 (the default) then up to 1,000 of the most recent records are retrieved from the API. If there are fewer records available than the value of take all records will be retrieved. A warning appears if there are more records available than the value of take.
summary is a boolean indicating whether to exclude nested and empty columns in the results. The default is TRUE.
clquestions::fetch_written_statements(
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written statement, with one row per statement.
This dataframe contains summary details for each written statement, such as the statement date, statement text and details on the member who made the statement.
clquestions::fetch_written_statements_body(
body_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written statement by the body responsible for the statement, with one row per statement.
body_id is an integer representing the ID of the body responsible for the written statement. Only one integer can be supplied.
This dataframe contains summary details for each written statement, such as the statement date, statement text and details on the member who made the statement.
Use get_answer_bodies() for a list of all available answer bodies and their corresponding ID numbers.
clquestions::fetch_written_statements_member(
member_mnis_id = NULL,
from_date = NULL,
to_date = NULL,
on_date = NULL,
house = NULL,
take = 1000,
summary = TRUE)Fetch a dataframe of key details about each written statement by the member who made the statement, with one row per statement.
member_mnis_id is an integer representing the MNIS ID for Commons and Lords members.
This dataframe contains summary details for each written statement, such as the statement date, statement text and details on the member who made the statement.
clquestions::fetch_raw_query(url)Takes a URL for the written question or written statement endpoints, retrieves and converts data into a tibble, and standardises variable names. No further cleaning or alteration of the data occurs.