README.md

metadata

license: mit
task_categories:
  - time-series-forecasting
  - tabular-classification
tags:
  - prediction-markets
  - finance
  - politics
  - time-series
  - ohlc
size_categories:
  - 100K<n<1M

Politics1M Dataset

OHLC price data for political prediction markets, aggregated into 5-minute candles.

Dataset Structure

• Format: Parquet
• Time Resolution: 5-minute intervals
• Source: Polymarket prediction markets
• Scope: Political markets with resolved outcomes

Data Schema

• condition_id: Market condition identifier
• market_id: Market identifier
• token_id: Outcome token identifier
• bucket_start_ts: Unix timestamp (5-minute bucket start)
• open, high, low, close: Price values (0-1 range)
• volume: Total trading volume
• trade_count: Number of trades in bucket
• question: Market question text
• theme: Market category
• target_resolution: Ground truth outcome (0 or 1)
• yes_won: Binary label indicating if "Yes" outcome won

Usage

import pandas as pd

df = pd.read_parquet("v0.1.0/02_process/ohlc.parquet")