Datasets:
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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
```python
import pandas as pd
df = pd.read_parquet("v0.1.0/02_process/ohlc.parquet")
```
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