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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
candidate: string
poll_pct: double
market_pct: double
divergence_pp: double
snapshot_date: string
vs
date: string
Lee_Jae-myung: double
Kim_Moon-soo: double
Lee_Jun-seok: double
Other: double
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 580, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              candidate: string
              poll_pct: double
              market_pct: double
              divergence_pp: double
              snapshot_date: string
              vs
              date: string
              Lee_Jae-myung: double
              Kim_Moon-soo: double
              Lee_Jun-seok: double
              Other: double

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AFOS · South Korea 2025 Electoral Divergence

South Korea 2025 — Electoral Divergence Dataset

Open, auditable cross-reference of prediction market (Polymarket) × opinion polls × press for the 3 June 2025 South Korean snap presidential election, validated against the official result. Part of the AFOS Analytics validated-cases collection.

The case

Lee Jae-myung (Democratic Party) won with 49.42% of the vote, defeating Kim Moon-soo (People Power Party, 41.15%) and Lee Jun-seok (Reform Party, ~8.3%). The snap election followed Yoon Suk-yeol's martial-law crisis and his removal by the Constitutional Court.

The signal was strong and early: from early April the market already gave Lee ~80% probability of winning, rising to ~95% at the close, while polls measured his vote share around 46-49%. The market treated the race as decided, and it even nailed the victory margin (the "8-11pp" band; the actual margin was 8.27pp). With about US$290M in total volume, it was one of the largest election markets AFOS has tracked outside the US.

The market measures probability of winning; the poll measures vote share. That gap, candidate by candidate, is the AFOS signal, not a polling error.

Note: Korean law bars Koreans from betting on Polymarket, so the market volume is mostly international.

Files

  • data/south-korea-2025-market-odds-timeseries.csv — daily Polymarket win-probability per candidate (59 days, 2025-04-06 to 2025-06-03).
  • data/south-korea-2025-divergence.csv — market % vs poll % per candidate at the closing snapshot (2025-06-02).
  • data/south-korea-2025-structural-context.csv — World Bank governance (WGI) + macro/education (WDI).
  • data/south-korea-2025-poly-raw.json — raw Polymarket source (events + price history), fetched via the AFOS server-side proxy.
  • polls/south-korea-2025-polls.csv — full vote-intention series for the finalized race (82 polls, 36 pollsters, 12 May–3 June 2025), long format (one row per poll/candidate), parsed deterministically from the Wikipedia aggregation.
  • polls/south-korea-2025-polls.json — the same polls as structured JSON (per-poll, per-candidate).
  • news/south-korea-2025-press-coverage.csv — dated headlines from 5 Korean national outlets (Yonhap, Korea Herald, Korea Times, Korea JoongAng Daily, The Hankyoreh).

Sources

Polymarket (live odds via AFOS proxy), Korea opinion polls (36 pollsters, incl. Gallup Korea, KOPRA, Hangil, Jowon C&I, Media Tomato, Embrain, Metavoice) via the public Wikipedia aggregation, National Election Commission (official result), Korean national press. Market snapshot total volume: US$290.7M.

Provenance & method: poll figures compiled deterministically (rowspan/colspan-aware HTML parser) from the public Wikipedia aggregation "Opinion polling for the 2025 South Korean presidential election" (CC BY-SA), covering the finalized three-way race (Lee Jae-myung × Kim Moon-soo × Lee Jun-seok, plus minor candidates) from 12 May to 3 June 2025; hypothetical pre-nomination matchups and the official vote count are excluded. Nothing is imputed or smoothed; missing values left blank. The divergence snapshot compares the closing market (2025-06-02) against the final-wave vote-intention consensus (mean of the 25-27 May polls: Lee 47.1, Kim 38.2, Lee Jun-seok 9.8). Market odds come from the public Polymarket market. Underlying numbers are facts released by the named pollsters; please attribute AFOS Analytics and the original pollsters.

License: data CC BY 4.0; code Apache 2.0. afos-analytics.com

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