Package {assemblykor}

assemblykor: Korean National Assembly Data for Political Science Education

Description

Provides ready-to-use datasets from the Korean National Assembly for teaching quantitative methods in political science. Includes seven built-in datasets covering legislator metadata, bills, asset declarations, policy seminars, committee speeches, plenary vote tallies, and member-level roll call votes.

Built-in datasets

• legislators: 963 MP records (20th-22nd assemblies)

• bills: 64,900 legislative bills

• wealth: 3,215 legislator-year asset declarations

• seminars: 5,962 legislator-year seminar records

• speeches: 15,795 speech records (22nd, Science & ICT Committee)

• votes: 8,611 plenary vote tallies (20th-22nd assemblies)

• roll_calls: 549,513 member-level roll call votes (22nd assembly)

Download functions

• get_bill_texts: 64,900 bill propose-reason texts

• get_proposers: 825,283 co-sponsorship records

• get_speech_tokens: 663,582 morpheme tokens for the speeches dataset (Kiwi morphological analyzer)

Data corrections and coverage

Version 0.1.4 corrects defects that releases 0.7.0 to 0.8.1 of the kna project (https://github.com/kyusik-yang/kna) found in the underlying Open Assembly records, among them the seniority and committees of legislators, the results of vetoed bills, the co-sponsorship records cut at 100 names per bill and the votes the API omits. It also extends the 22nd assembly to 2026-09-23 and the asset declarations to 2025, from kna 0.8.1. See the package NEWS for details.

Tutorials

Nine Korean-language tutorials covering tidyverse, visualization, regression, panel data, text analysis, network analysis, roll call analysis, bill success, and speech patterns. Use list_tutorials to see all tutorials, and open_tutorial to copy them to your working directory.

Author(s)

Maintainer: Kyusik Yang kyusik.yang@nyu.edu

See Also

Useful links:

• https://kyusik-yang.github.io/assemblykor/

• https://github.com/kyusik-yang/assemblykor

• Report bugs at https://github.com/kyusik-yang/assemblykor/issues

Bills Proposed in the Korean National Assembly (20th-22nd)

Description

Metadata for the 64,900 bills that members proposed during the 20th through 22nd Korean National Assembly (2016-2026), up to 2026-09-23.

Usage

bills

Format

A data frame with 64,900 rows and 11 variables:

bill_id

Unique bill identifier from the National Assembly system

bill_no

Numeric bill number

assembly

Assembly number (20, 21, or 22)

bill_name

Full bill title in Korean

committee

Standing committee to which the bill was referred

propose_date

Date the bill was formally proposed

result

Legislative outcome in Korean. Common values include passed as-is, expired at term end, and incorporated into alternative bill. NA for bills pending on 2026-09-23. For a vetoed bill, the outcome after the veto (rejected on the re-vote, passed again, or expired at the end of the term). See table(bills$result) for all values.

proposer

Name of the lead (primary) proposer

proposer_id

MONA_CD of the lead proposer (links to legislators$member_id). Comma-separated for the few bills with joint lead proposers.

vetoed

Logical: the President returned the bill to the Assembly for reconsideration (a presidential veto)

alt_vetoed

Logical: the bill was incorporated into a committee alternative (result "incorporated into alternative bill") that was vetoed and not passed again, so its content never became law

Details

The Korean National Assembly has seen a dramatic increase in bill proposals: the 21st Assembly produced 23,655 bills versus 21,594 in the 20th. Most bills expire at the end of the assembly term (term expiry). Only about 5\ with amendments.

Up to version 0.1.3, 11 of the 12 vetoed bills, which were rejected on the re-vote or expired at the end of the term, kept the result of their first floor vote. Their result now follows the re-vote, as in release 0.7.0 of the kna project. To count bills whose content became law, exclude alt_vetoed bills as well.

Use get_bill_texts() to download the full propose-reason texts for text analysis, and get_proposers() for the complete co-sponsorship records (825,283 rows).

Source

Open National Assembly Information API (Republic of Korea), as corrected in kna 0.7.0 (20th and 21st) and kna 0.8.1 (22nd) (https://github.com/kyusik-yang/kna).

Examples

data(bills)

# Bills per assembly
table(bills$assembly)

# Top 10 committees
sort(table(bills$committee), decreasing = TRUE)[1:10]

# Distribution of legislative outcomes
head(sort(table(bills$result), decreasing = TRUE))

Download bill propose-reason texts

Description

Downloads the full propose-reason texts (jean-iyu) for all 64,900 bills in bills. The file is approximately 26 MB and is cached locally after the first download. Requires the arrow package to read parquet files.

Usage

get_bill_texts(cache_dir = NULL, force_download = FALSE)

Arguments

Details

The texts are those of release 0.8.1 of the kna project (https://github.com/kyusik-yang/kna), for the bills in bills. Versions up to 0.1.3 downloaded the scraped texts of the korean-assembly-bills dataset, which cover the bills proposed by 2026-02-27 and are unchanged here. Record source in text analyses.

Value

A data frame with 64,900 rows and 4 variables, or NULL (invisibly) if the download fails (e.g., no internet connection):

bill_id

Bill identifier (links to bills$bill_id)

propose_reason

Full text of the propose-reason statement (Korean). NA for the 80 bills that have no text in the source.

scrape_status

Status of the web collection of the text: "ok", "empty", "no_csrf", or "error". NA for texts from the API.

source

"likms_scrape" for the texts collected from the Legislative Information System (bills proposed by 2026-02-27), or "BPMBILLSUMMARY" for the texts of the Open Assembly API, which begin with a heading that the scraped texts lack. NA for the eight bills without any text record.

Examples

if (requireNamespace("arrow", quietly = TRUE)) {
  texts <- get_bill_texts(cache_dir = tempdir())

  if (!is.null(texts)) {
    nchar_dist <- nchar(texts$propose_reason)
    hist(nchar_dist, breaks = 100, main = "Length of Propose-Reason Texts")
  }
}

Download bill co-sponsorship records

Description

Downloads the complete proposer records (825,283 rows) listing every legislator who proposed, co-proposed or supported each of the 64,900 bills in bills. Requires the arrow package.

Usage

get_proposers(cache_dir = NULL, force_download = FALSE)

Arguments

Details

The records come from the official proposer list of each bill (BILLINFOPPSR endpoint), as rebuilt in the kna project (https://github.com/kyusik-yang/kna), release 0.8.1. Releases up to 0.1.3 of this package served an earlier file that stopped at 100 names per bill, which left out 7,447 records of the 208 bills with more than 100 proposers and supporters, and whose is_lead was FALSE for the lead proposer of 36 single-proposer bills. Bills with joint lead proposers have more than one row with is_lead = TRUE.

Value

A data frame with 825,283 rows and 9 variables, or NULL (invisibly) if the download fails (e.g., no internet connection):

bill_id

Bill identifier (links to bills$bill_id)

bill_no

Numeric bill number

bill_name

Bill title in Korean

propose_date

Proposal date

proposer_name

Legislator name

proposer_party

Party affiliation at the time of proposal

member_id

Legislator identifier (links to legislators$member_id)

is_lead

Logical: TRUE if lead (primary) proposer, FALSE if co-proposer or supporter (see role)

role

Role on the bill in Korean, one of lead proposer (daepyo balui), co-proposer (gongdong balui) or supporter (chanseong). Supporters are the members counted in the "oe M in" part of the proposer text.

Examples

if (requireNamespace("arrow", quietly = TRUE) &&
    requireNamespace("dplyr", quietly = TRUE)) {
  props <- get_proposers(cache_dir = tempdir())

  if (!is.null(props)) {
    # Build co-sponsorship edgelist
    leads <- dplyr::select(
      dplyr::filter(props, is_lead), bill_id, lead = member_id
    )
    cosponsors <- dplyr::select(
      dplyr::filter(props, !is_lead), bill_id, cosponsor = member_id
    )
    edges <- dplyr::inner_join(
      leads, cosponsors,
      by = "bill_id", relationship = "many-to-many"
    )
  }
}

Download morpheme tokens for committee speeches

Description

Downloads a pre-tokenized version of the speeches dataset, produced with the Kiwi morphological analyzer (via kiwipiepy). Korean is an agglutinative language, so whitespace tokenization mixes particles and verb endings into the tokens; morphological analysis separates them and lemmatizes verbs and adjectives. This dataset lets students work with proper Korean tokens without installing a morphological analyzer. The file is approximately 1.3 MB and is cached locally after the first download. Requires the arrow package.

Usage

get_speech_tokens(cache_dir = NULL, force_download = FALSE)

Arguments

Details

Only content morphemes are included; particles (josa), verb endings (eomi), and punctuation are removed. Function words carry little topical meaning, so this is the usual starting point for keyword and topic analysis. For noun-based analysis, filter to pos %in% c("NNG", "NNP").

Join back to speeches with by = c("date", "speech_order") to attach speaker metadata. Every speech has at least one token. Two meetings were held on 2024-06-25, so eight speech_order values of that date belong to two speeches each, and their tokens are pooled under the shared key. Up to version 0.1.3 the file also held a second copy of the tokens of 48 speeches that appeared twice in speeches.

The tokenization script is in the package source repository under data-raw/tokenize_speeches.py.

Value

A data frame with 663,582 rows and 4 variables, or NULL (invisibly) if the download fails (e.g., no internet connection):

date

Date of the committee meeting (links to speeches$date)

speech_order

Speech turn within the meeting (links to speeches$speech_order); date + speech_order identifies one speech, except on 2024-06-25 (see Details)

token

Morpheme, in dictionary form. Verbs and adjectives are lemmatized (e.g., the stem plus -da)

pos

Part-of-speech tag from the Sejong tagset: "NNG" (common noun), "NNP" (proper noun), "VV" (verb), "VA" (adjective), "MAG" (adverb), or "SL" (foreign word, e.g., "AI")

See Also

speeches

Examples

if (requireNamespace("arrow", quietly = TRUE)) {
  tokens <- get_speech_tokens(cache_dir = tempdir())

  if (!is.null(tokens)) {
    # Most frequent nouns
    nouns <- tokens[tokens$pos %in% c("NNG", "NNP"), ]
    head(sort(table(nouns$token), decreasing = TRUE), 20)
  }
}

Members of the Korean National Assembly (20th-22nd)

Description

Biographical and political metadata for 963 records of legislators who served in the 20th (2016-2020), 21st (2020-2024), or 22nd (2024-2028) Korean National Assembly. Some legislators appear in multiple assemblies. The 22nd assembly covers the members seated by 2026-09-23, among them the winners of the by-elections of 2026-06-11.

Usage

legislators

Format

A data frame with 963 rows and 15 variables:

member_id

Unique legislator identifier (MONA_CD from the National Assembly API)

assembly

Assembly number (20, 21, or 22)

name

Name in Korean (hangul)

name_hanja

Name in Chinese characters (hanja)

name_eng

Name in English (romanized)

party

Party label that the official roster of that assembly records for the member. It reflects party mergers, renamings and switches during the term. For the 22nd assembly it is the party as of September 2026, or the last party recorded for a member who had left the Assembly by then.

party_elected

Party at election, that is, the party on whose ticket or list the member was elected. For a successor to a proportional seat, the party of the list the seat came from. The source records ten such successors under the party that the list party had merged into by the time they took the seat (for example, the Democratic Party of Korea for the Democratic Alliance of Korea), as does release 0.7.0 of the kna project.

district

Electoral district name, or party list position for proportional members

district_type

Election type: "constituency" or "proportional"

committees

Committees (standing and special) the member served on in that assembly, comma-separated in order of first assignment. Empty for a member with no assignment, such as the Speaker.

gender

"M" (male) or "F" (female)

birth_date

Date of birth

seniority

Seniority at that assembly, that is, the number of terms served up to and including this one, counting terms before the 20th (1 = first-term)

n_bills

Number of bills in bills the member proposed, co-proposed or supported (see get_proposers)

n_bills_lead

Bills proposed as lead (primary) proposer

Details

672 unique legislators served across the three assemblies. member_id is consistent across assemblies, so legislators can be tracked over time. Party names may differ between party (mid-term) and party_elected (election day) due to party mergers and name changes, which are common in Korean politics. Some legislators share a name with another member of the same assembly (for example, two members named Kim Seong-tae in the 20th), so join on member_id, never on name.

Up to version 0.1.3, seniority held each member's lifetime number of terms at the time of data collection, so it overstated the seniority of 286 member-terms of the 20th and 21st assemblies, and committees came from a present-day string that did not match the assembly. Both now follow release 0.7.0 of the kna project, as do six values of party_elected, one district, two district types and the bill counts. The 22nd assembly is rebuilt from release 0.8.1 of the kna project.

Source

Open National Assembly Information API (Republic of Korea), as corrected in kna 0.7.0 (20th and 21st) and kna 0.8.1 (22nd) (https://github.com/kyusik-yang/kna). License: public domain (Korean government open data).

Examples

data(legislators)

# Party composition by assembly
table(legislators$assembly, legislators$party)

# Gender gap in bill production
tapply(legislators$n_bills_lead, legislators$gender, median)

# First-term vs senior legislators
boxplot(n_bills_lead ~ seniority, data = legislators,
        xlab = "Terms served", ylab = "Bills proposed (lead)")

List available tutorials

Description

Lists the tutorial R Markdown files included with the package. Tutorials are designed for classroom use in Korean political science methods courses. Each tutorial is available in two formats:

1. Plain Rmd for editing in RStudio (open_tutorial)

2. Interactive learnr format (run_tutorial)

Usage

list_tutorials()

Value

A character vector of tutorial file names (invisibly).

Examples

list_tutorials()

Open a tutorial file

Description

Copies a tutorial R Markdown file to the specified directory (default: current working directory) so students can edit and run it in RStudio.

Usage

open_tutorial(name, dest_dir = getwd())

Arguments

Value

The path to the copied file (invisibly).

See Also

run_tutorial for the interactive browser version.

Examples

if (interactive()) {
  # Copy by name
  open_tutorial("01-tidyverse-basics")

  # Copy by number
  open_tutorial(1)
}

Path to assemblykor CSV files

Description

Returns the file path to CSV versions of the built-in datasets stored in inst/extdata. Useful for teaching file I/O with read.csv() or readr::read_csv().

Usage

path_to_file(file = NULL)

Arguments

Value

A character string with the full file path.

Examples

# Read data from CSV (alternative to data())
path <- path_to_file("legislators.csv")
legislators_csv <- read.csv(path, fileEncoding = "UTF-8")
head(legislators_csv)

Member-Level Roll Call Votes (22nd Assembly)

Description

Individual legislator voting records for all 1,847 bills that went to a recorded plenary vote in the 22nd Korean National Assembly from July 2024 to September 17, 2026. Each row represents one legislator's vote on one bill.

Usage

roll_calls

Format

A data frame with 549,513 rows and 9 variables:

bill_id

Bill identifier (links to votes$bill_id and bills$bill_id)

assembly

Assembly number (22)

member_name

Legislator name in Korean

member_id

Legislator identifier (MONA_CD, links to legislators$member_id)

party

Party label reported by the API at data collection (September 2026). The API writes the member's party at that time onto every past vote, so a member who changed party during the term appears under the later party on all votes. For the votes taken from the LIKMS vote pages (see Source) it is the member's party in September 2026.

party_elected

Party at election, as in legislators$party_elected. Members elected on the lists of the satellite parties (e.g., the People Future Party and the Democratic Alliance of Korea) carry the list party, although they sat with other parties. Three members who succeeded to proportional seats during the term carry the party into which the list party had merged, two the Democratic Party of Korea and one the People Power Party (see legislators).

district

Electoral district at the 2024 election, or the proportional list, as in legislators$district

vote

Vote cast in Korean: one of four values meaning yes, no, abstain, or absent

vote_date

Date of the vote

Details

This dataset covers the 22nd assembly. The same API endpoint also has member-level votes of the 20th and 21st assemblies, which are left out to keep the package small. The kna project (https://github.com/kyusik-yang/kna) provides them. For the 20th and 21st assemblies, use the bill-level votes dataset.

Neither party column records the party at the time of each vote. Up to version 0.1.3, party was documented as the party at the time of the vote. Version 0.1.4 corrects that description, adds party_elected, and rebuilds the dataset from release 0.8.1 of the kna project, which adds the votes of the 16 members seated in 2026 that the API omits. Every member seated at a vote has a row for it, absent if the member did not vote.

This dataset enables ideal point estimation (e.g., W-NOMINATE), party unity scores, and analysis of legislative coalitions. Use member_id to link with legislators for biographical metadata.

Source

Open National Assembly Information API (Republic of Korea), endpoint nojepdqqaweusdfbi, as collected by release 0.8.1 of the kna project (https://github.com/kyusik-yang/kna) in September 2026. The votes of the 16 members the API omits come from the vote pages of the Legislative Information System (LIKMS), as in kna 0.8.0.

See Also

votes

Examples

data(roll_calls)

# Vote distribution
table(roll_calls$vote)

# Votes per party
head(sort(table(roll_calls$party), decreasing = TRUE))

# Number of unique legislators
length(unique(roll_calls$member_id))

Run an interactive tutorial

Description

Launches a learnr interactive tutorial in the browser. Students can type and run code directly in the browser with hints and solutions. Requires the learnr package.

Usage

run_tutorial(name)

Arguments

Value

No return value, called for the side effect of launching a learnr tutorial in the browser.

See Also

open_tutorial for the plain Rmd version.

Examples

if (interactive()) {
  run_tutorial(1)
}

Policy Seminar Activity by Legislator-Year (2004-2025)

Description

Annual panel of policy seminar hosting activity for legislators in the 17th through 22nd Korean National Assembly. Policy seminars (jeongchaek semina) are informal legislative events where MPs invite experts, stakeholders, and colleagues from other parties to discuss policy issues.

Usage

seminars

Format

A data frame with 5,962 rows and 18 variables:

name

Legislator name in Korean

member_id

Legislator identifier (MONA_CD, links to legislators$member_id). Available for 5,696 rows (95.5\ and NA for unmatched or ambiguous (homonym) cases.

year

Calendar year

assembly

Assembly number (17-22), assigned from the calendar year (2004-2007 to the 17th, 2008-2011 to the 18th, and so on)

party

Party affiliation

camp

Political camp: "liberal", "conservative", "progressive", "centrist", or "other" (values are in Korean)

seniority

Seniority at that assembly, that is, the number of terms served up to and including this one, counting terms before the 17th (1 = first-term)

n_seminars

Number of policy seminars hosted that year

n_cross_party

Number of seminars co-hosted with other-party legislators

cross_party_ratio

Share of seminars that were cross-party (0-1)

avg_coalition_size

Average number of co-hosts per seminar

is_governing

Logical: belongs to the governing (presidential) party

is_female

Logical: female legislator

is_proportional

Logical: holds a proportional-representation seat in that assembly

is_seoul

Logical: represents a Seoul district in that assembly

province

Province or metropolitan city of the electoral district in that assembly, in Korean short form (e.g., Seoul, Gyeonggi). NA for proportional-representation members.

total_terms

Total assembly terms served across the career, as of September 2026

n_bills_led

Number of bills the legislator proposed as lead proposer in that assembly term (the same value in every year of the term)

Details

Policy seminars are a distinctive feature of the Korean National Assembly. Unlike floor speeches or committee hearings, seminars are voluntary and allow legislators to signal policy expertise and build cross-party ties. The cross_party_ratio variable captures how often a legislator cooperates across party lines in this informal arena.

The is_governing variable enables difference-in-differences designs: when a party transitions from opposition to governing (or vice versa), does its members' cross-party collaboration change?

The member attributes seniority, total_terms, is_female, is_proportional, is_seoul and province come from the member records of release 0.7.0 of the kna project, matched on member_id and assembly. Up to version 0.1.3 they were matched on the name alone and counted only the terms from the 17th assembly on. They are NA when a row has no member_id, and all but total_terms and is_female are NA when the legislator did not serve in that assembly.

The panel counts seminars by name and year. Because a new assembly begins on May 30 of an election year, the rows of an election year also hold the activity of members of the outgoing assembly, under the new assembly number. Legislators who share a name with another member of the same assembly have one row per year for both of them, with member_id NA.

Source

National Assembly Seminar Database, collected via API. Member attributes from kna 0.7.0 (https://github.com/kyusik-yang/kna).

Examples

data(seminars)

# Cross-party collaboration by governing status
tapply(seminars$cross_party_ratio, seminars$is_governing, mean, na.rm = TRUE)

# Seminar activity over time
agg <- aggregate(n_seminars ~ year, data = seminars, FUN = sum)
plot(agg, type = "b", main = "Total Policy Seminars by Year")

# Gender gap in seminar hosting
tapply(seminars$n_seminars, seminars$is_female, median, na.rm = TRUE)

Set Korean font for ggplot2

Description

Detects a Korean-compatible font on the current system and applies it to all ggplot2 plots via theme_set(). Call this once at the top of your script to avoid broken Korean text in plot titles and labels.

Usage

set_ko_font(font = NULL)

Arguments

Value

The font family name used (invisibly).

Examples

if (interactive()) {
  library(ggplot2)
  set_ko_font()

  # Now Korean text renders correctly
  ggplot(data.frame(x = 1), aes(x, x)) +
    geom_point() +
    labs(title = "Korean Title Test")
}

Committee Speeches from the Science and ICT Committee (22nd Assembly)

Description

Full corpus of 15,795 speech records from the Science, Technology, Information, Broadcasting and Communications Committee of the 22nd Korean National Assembly (2024). Standing committee meetings only.

Usage

speeches

Format

A data frame with 15,795 rows and 10 variables:

assembly

Assembly number (22)

date

Date of the committee meeting

committee

Committee name in Korean

speaker

Speaker label as it appears in the minutes (may include titles)

role

Speaker role: "legislator", "chair", "minister", "vice_minister", "senior_bureaucrat", "agency_head", "witness", "expert_witness", "nominee", "minister_nominee", "testifier", "public_corp_head", "broadcasting", "committee_staff"

speaker_name

Cleaned speaker name with titles removed

member_id

Legislator identifier (MONA_CD, links to legislators$member_id) for the 12,060 speeches by members of the Assembly. NA for other speakers (ministers, witnesses, and the heads of other bodies).

speaker_id

Numeric speaker identifier used in the committee minutes, which versions up to 0.1.3 stored in member_id. NA for speakers who are not members of the Assembly.

speech_order

Order of the speech turn within the meeting

speech

Full text of the speech in Korean

Details

This dataset contains the complete standing committee speech records (no sampling) for the Science and ICT Committee of the 22nd assembly (June-December 2024). Speeches shorter than 50 characters were excluded. date and speech_order identify a speech, except on 2024-06-25, when two meetings were held and eight speech_order values occur twice.

Up to version 0.1.3, member_id held the numeric speaker identifier of the minutes, so it did not link to legislators$member_id, and 48 speeches of 2024-08-14 appeared twice under two speaker identifiers. Version 0.1.4 attaches the MONA_CD through the member records of release 0.7.0 of the kna project and drops the duplicates.

The role variable distinguishes legislators from government officials, witnesses, and other participants. Filter to role == "legislator" for MP speeches only, or compare how legislators and ministers discuss the same agenda items.

This committee covers AI, telecommunications, broadcasting, space policy, and R&D governance, making it suitable for keyword analysis, topic modeling, and other text analysis exercises.

Source

National Assembly committee minutes via the Open National Assembly Information API.

Examples

data(speeches)

# Distribution of speech lengths
hist(nchar(speeches$speech), breaks = 100,
     main = "Speech Length Distribution", xlab = "Characters")

# Speaker roles
table(speeches$role)

# Most frequent legislator speakers
leg <- speeches[speeches$role == "legislator", ]
head(sort(table(leg$speaker_name), decreasing = TRUE), 10)

# Simple keyword search (example: AI-related speeches)
ai <- speeches[grepl("AI", speeches$speech), ]
nrow(ai)

Plenary Vote Results in the Korean National Assembly (20th-22nd)

Description

Bill-level vote tallies from plenary sessions of the 20th through 22nd Korean National Assembly (2016-2026). Each row represents one bill that went to a recorded floor vote.

Usage

votes

Format

A data frame with 8,611 rows and 13 variables:

bill_id

Bill identifier (links to bills$bill_id). Unique except for bill 2000491 of the 20th assembly, which has two tally rows in the source.

bill_no

Numeric bill number

bill_name

Full bill title in Korean

assembly

Assembly number (20, 21, or 22)

committee

Standing committee to which the bill was referred

vote_date

Date of the plenary vote

result

Vote outcome in Korean (e.g., passed as-is, passed with amendments, rejected)

bill_type

Type of bill (e.g., legislation, budget, resolution)

total_members

Total number of assembly members at the time

voted

Number of members who cast a vote

yes

Number of yes votes

no

Number of no votes

abstain

Number of abstentions

Details

Not all bills go to a floor vote. Most bills are disposed of in committee or expire at the end of the assembly term. The votes dataset captures only those that reached the plenary floor for a recorded vote.

About 40\ because bills only contains legislator-proposed bills while votes also includes committee alternatives, budget bills, and resolutions that have separate identifiers.

See roll_calls for member-level voting records (22nd assembly), useful for ideal point estimation or party discipline analysis.

Source

Open National Assembly Information API (Republic of Korea), endpoint ncocpgfiaoituanbr. The 22nd assembly is the collection of release 0.8.1 of the kna project (https://github.com/kyusik-yang/kna), with votes up to 2026-09-17.

Examples

data(votes)

# Votes per assembly
table(votes$assembly)

# Pass rate
table(votes$result)

# Average yes rate
votes$yes_rate <- votes$yes / votes$voted
summary(votes$yes_rate)

# Contentious votes (yes rate < 70%)
contentious <- votes[votes$yes / votes$voted < 0.7, ]
nrow(contentious)

Legislator Asset Declarations (2015-2025)

Description

Panel data of asset declarations for 776 Korean National Assembly members across 11 years (2015-2025). Derived from the mandatory annual public disclosures.

Usage

wealth

Format

A data frame with 3,215 rows and 14 variables:

member_id

Legislator identifier (links to legislators$member_id)

year

Year the declared wealth refers to (2015-2025). The declaration is published in March of the following year.

name

Legislator name in Korean

total_assets

Total declared assets, in thousands of KRW

total_debt

Total declared liabilities, in thousands of KRW

net_worth

Net worth (assets minus debt), in thousands of KRW

real_estate

Total real estate value, in thousands of KRW

building

Total building/structure value, in thousands of KRW

land

Total land value, in thousands of KRW

deposits

Total bank deposits, in thousands of KRW

stocks

Total stock holdings, in thousands of KRW

n_properties

Total number of properties disclosed

has_seoul_property

Logical: owns property in Seoul

has_gangnam_property

Logical: owns property in Gangnam (Seoul's wealthiest district)

Details

All monetary values are in thousands of KRW (1 unit = 1,000 won). To convert to billions of won, divide by 1,000,000. For example, a net_worth of 1,670,000 means 1.67 billion won (approximately USD 1.2 million).

Legislators are required by law to disclose their assets annually. Not all legislators appear in every year, as the panel is unbalanced (entries correspond to active service periods).

Source

2015-2024: OpenWatch (https://docs.openwatch.kr/data/national-assembly), CC BY-SA 4.0 license. 2025: the National Assembly Gazette (Gukhoe Gongbo) No. 2026-54 of 2026-03-26, the March 2026 regular disclosure. Both as compiled in release 0.8.1 of the kna project (https://github.com/kyusik-yang/kna).

Examples

data(wealth)

# Distribution of net worth (in billions of won)
hist(wealth$net_worth / 1e6, breaks = 50,
     main = "Legislator Net Worth", xlab = "Billion KRW")

# Real estate as share of total assets
wealth$re_share <- wealth$real_estate / wealth$total_assets
summary(wealth$re_share)

# Gangnam property owners vs others
tapply(wealth$net_worth / 1e6, wealth$has_gangnam_property, median, na.rm = TRUE)