| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: top |
| path: |
| - top/*.parquet |
| - days_0721_0731/top/*.parquet |
| - split: medium_high |
| path: |
| - medium_high/*.parquet |
| - days_0721_0731/medium_high/*.parquet |
| size_categories: |
| - 100K<n<1M |
| tags: |
| - game-logs |
| - pokemon-tcg |
| - agents |
| --- |
| |
| # Pokémon TCG Tournament Game Logs |
|
|
| Full game logs from an agent Pokémon TCG tournament ("Limited Card Battle"), |
| 122,542 recorded games collected across 26 daily archives — an initial batch |
| of 15 undated archives (`top/`, `medium_high/`) plus dated days |
| 2026-07-21 → 2026-07-31 (`days_0721_0731/`). Both batches use the same |
| per-day split rule and load together via the split config above. |
|
|
| ## Splits |
|
|
| Games in each daily archive were ranked by `avg_score` (per-agent average |
| rating, ELO-like, ~1000–1230, higher = better): |
|
|
| | Split | Games | Contents | |
| |---|---|---| |
| | `top` | 18,200 | the 700 highest-rated games from each archive (high-quality / eval set) | |
| | `medium_high` | 104,342 | every other game (pretraining set) | |
|
|
| Episode IDs are globally unique across archives; the two splits are disjoint. |
|
|
| ## Columns |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | `episode_id` | int64 | unique game/episode id (original JSON filename) | |
| | `agents` | list\<string\> | the two agent names (`info.TeamNames`) | |
| | `rewards` | list\<double\> | final rewards per agent, e.g. `[1, -1]` (win/loss), `[0, 0]` (draw); may be null | |
| | `json` | string | the complete original game record, verbatim JSON | |
|
|
| Each `json` value is one full game dump (~2–9 MB raw) with top-level keys: |
| `configuration, description, id, info, module_version, name, rewards, |
| schema_version, specification, statuses, steps, title, version` — including |
| the complete step-by-step game trajectory under `steps`. |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| import json |
| |
| ds = load_dataset("shantezhou/pokemon_data", split="top", streaming=True) |
| for row in ds: |
| game = json.loads(row["json"]) |
| print(row["episode_id"], row["agents"], row["rewards"]) |
| break |
| ``` |
|
|
| Parquet shards are zstd-compressed (~80x vs raw JSON); the full dataset is |
| ~300 GB of raw JSON stored in a few GB of parquet. |
|
|
