SAGE › Countries › United Kingdom

United Kingdom: election results by parliamentary constituency

2001–2024 · 7 elections · GBR

SAGE has legislative election results for the United Kingdom from 7 elections between 2001 and 2024: 2001, 2005, 2010, 2015, 2017, 2019 and 2024. The smallest unit is the parliamentary constituency. The 2024 election has 650 parliamentary constituencies, and 100% of them have a location. Unit boundaries are available for every election.

Elections

Units are the smallest units in the data, and located units are those with coordinates. A year with several rows has several contests or votes; filter on them before you add up votes.

YearElection typeVote typeRound Units% locatedVotes Polygons
2001Legislative (lower house)65997%26,363,122yes[map]
2005Legislative (lower house)646100%27,148,480yes[map]
2010Legislative (lower house)650100%29,687,737yes[map]
2015Legislative (lower house)650100%30,697,854yes[map]
2017Legislative (lower house)650100%32,202,871yes[map]
2019Legislative (lower house)650100%32,014,110yes[map]
2024Legislative (lower house)650100%28,810,084yes[map]

Download

csv opens in Excel, Stata, R, or Python. gpkg has the unit boundaries for QGIS, ArcGIS, R, or Python. parquet has the vote rows as Parquet. rds is the native R sf object. Each ZIP has a README with the columns.

All years: [csv 551 KB] [gpkg 489 MB] [parquet 581 MB] [rds 3.5 GB] [codebook 239 KB]

YearDownloads
2024[csv 86 KB] [gpkg 138 MB] [parquet 86 KB]
2019[csv 83 KB] [gpkg 62 MB] [parquet 83 KB]
2017[csv 83 KB] [gpkg 60 MB] [parquet 82 KB]
2015[csv 84 KB] [gpkg 60 MB] [parquet 84 KB]
2010[csv 84 KB] [gpkg 60 MB] [parquet 84 KB]
2005[csv 68 KB] [gpkg 58 MB] [parquet 75 KB]
2001[csv 69 KB] [gpkg 52 MB] [parquet 75 KB]

In R or Python:

R:      install.packages("sage")
        sage::sage_load("United Kingdom", years = 2024)

Python: import sage
        sage.sage_load("United Kingdom", years=[2024])

Sources

Citation

Dasanaike, Noah. “The Small-Area Global Elections (SAGE) Dataset.” Scientific Data (2026). Paper · Harvard Dataverse

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