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README.md

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----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+pretty_name: Jaipur - Online Card Game Replays
+task_categories:
+  - reinforcement-learning
+tags:
+  - board-games
+  - card-games
+  - jaipur
+  - game-ai
+  - imperfect-information
+  - two-player
+language:
+  - en
+size_categories:
+  - 10K<n<100K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/games.parquet
+  - config_name: players
+    data_files:
+      - split: train
+        path: data/players.parquet
+dataset_info:
+  - config_name: default
+    features:
+      - name: game_id
+        dtype: string
+      - name: variant
+        dtype: string
+      - name: player_0
+        dtype: string
+      - name: player_1
+        dtype: string
+      - name: winner
+        dtype: int8
+      - name: num_rounds
+        dtype: int8
+      - name: num_turns
+        dtype: int16
+      - name: round_scores
+        sequence:
+          sequence: int16
+      - name: turns
+        list:
+          - name: round
+            dtype: int8
+          - name: actor
+            dtype: int8
+          - name: action_type
+            dtype: string
+          - name: action_goods
+            sequence: int8
+          - name: market
+            sequence: int8
+          - name: deck_size
+            dtype: int8
+          - name: actor_hand
+            sequence: int8
+          - name: opponent_hand
+            sequence: int8
+          - name: coin_stacks
+            sequence:
+              sequence: int8
+          - name: bonus_stacks
+            sequence:
+              sequence: int8
+          - name: actor_coins
+            sequence:
+              sequence: int8
+          - name: actor_bonuses
+            sequence: int8
+          - name: actor_score
+            dtype: int16
+          - name: opponent_score
+            dtype: int16
+    splits:
+      - name: train
+        num_examples: 38077
+  - config_name: players
+    features:
+      - name: player_id
+        dtype: string
+      - name: num_games
+        dtype: int32
+      - name: num_wins
+        dtype: int32
+      - name: win_rate
+        dtype: float32
+      - name: num_games_as_p0
+        dtype: int32
+      - name: num_games_open_info
+        dtype: int32
+      - name: num_games_original
+        dtype: int32
+    splits:
+      - name: train
+        num_examples: 4264
+---
+
+# Jaipur: Online Card Game Replays
+
+A dataset of **38,000+ complete Jaipur card game replays** from human players on
+[Yucata.de](https://www.yucata.de).
+
+[Jaipur](https://boardgamegeek.com/boardgame/54043/jaipur) is a two-player trading card game where players compete as merchants, buying and selling goods to earn the
+most money. It features imperfect information (hidden deck and opponent hand), delayed rewards,
+and strategic tension between short-term gains and long-term planning.
+
+## Why This Dataset?
+
+Jaipur is an excellent benchmark for game AI research:
+
+- **Imperfect information**: Players cannot see the deck or (in the original variant) the
+  opponent's hand, requiring belief tracking and risk assessment
+- **Mixed strategy space**: Actions include taking goods, selling sets, and multi-card trades
+- **Compact but deep**: Games are short (~20-40 turns) but strategically rich
+- **Two variants included**: Open information (both hands visible) and original rules (hidden
+  hands), enabling research on how information availability affects strategy
+
+## Dataset Structure
+
+### Games (`data/games.parquet`)
+
+Each row is one complete game. The `turns` column contains the full sequence of game states
+and actions.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `game_id` | `string` | Unique anonymized game identifier |
+| `variant` | `string` | `"open_info"` or `"original"` (whether hands are visible) |
+| `player_0` | `string` | Anonymized player ID (consistent across games) |
+| `player_1` | `string` | Anonymized player ID |
+| `winner` | `int8` | `0` = player\_0 won, `1` = player\_1 won, `-1` = unknown |
+| `num_rounds` | `int8` | Number of rounds played (1-3, best of 3) |
+| `num_turns` | `int16` | Total turns across all rounds |
+| `round_scores` | `list[list[int16]]` | Per-round scores `[[p0_r1, p1_r1], [p0_r2, p1_r2], ...]` |
+| `turns` | `list[struct]` | Ordered list of turn records (see below) |
+
+#### Turn Schema
+
+Each element in the `turns` list is a struct with the state **before** the action and the
+action taken:
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `round` | `int8` | Round index (0-based) |
+| `actor` | `int8` | Which player acted (`0` or `1`) |
+| `action_type` | `string` | `"take"`, `"sell"`, or `"trade"` |
+| `action_goods` | `list[int8]` | Signed goods delta for actor: `[D, G, S, Cl, Sp, L, Ca]`. Positive = gained, negative = given away |
+| `market` | `list[int8]` | Market goods count: `[D, G, S, Cl, Sp, L, Ca]` |
+| `deck_size` | `int8` | Cards remaining in draw pile |
+| `actor_hand` | `list[int8]` | Actor's hand: `[D, G, S, Cl, Sp, L, Ca]` |
+| `opponent_hand` | `list[int8]` | Opponent's hand (always present in data, even for original variant) |
+| `coin_stacks` | `list[list[int8]]` | Remaining coin values per good `[[D coins], [G], [S], [Cl], [Sp], [L]]`, ordered highest-first |
+| `bonus_stacks` | `list[list[int8]]` | Remaining bonus token values `[[3-set], [4-set], [5-set]]` |
+| `actor_coins` | `list[list[int8]]` | Coins actor has earned per good `[[D coins], ..., [L coins]]` |
+| `actor_bonuses` | `list[int8]` | Bonus token values actor has earned |
+| `actor_score` | `int16` | Actor's current score (goods + bonus coins) |
+| `opponent_score` | `int16` | Opponent's current score |
+
+**Goods order**: Diamond (D), Gold (G), Silver (S), Cloth (Cl), Spice (Sp), Leather (L), Camel (Ca) — 7 types. Coin stacks cover the 6 tradeable types (no camel coins).
+
+### Players (`data/players.parquet`)
+
+Aggregated statistics for each unique player across all games.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `player_id` | `string` | Anonymized player ID (matches `player_0`/`player_1` in games) |
+| `num_games` | `int32` | Total games played |
+| `num_wins` | `int32` | Total wins |
+| `win_rate` | `float32` | Win rate (wins / games with known outcome) |
+| `num_games_as_p0` | `int32` | Games played as player 0 (first mover) |
+| `num_games_open_info` | `int32` | Games played in open info variant |
+| `num_games_original` | `int32` | Games played in original variant |
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+# Load all games
+ds = load_dataset("noidvan/jaipur")
+game = ds["train"][0]
+
+print(f"Variant: {game['variant']}")
+print(f"Winner: player_{game['winner']}")
+print(f"Turns: {game['num_turns']}")
+
+# Iterate through turns
+for turn in game["turns"]:
+    print(f"  Round {turn['round']}, Player {turn['actor']}: {turn['action_type']}")
+    print(f"    Market: {turn['market']}, Deck: {turn['deck_size']}")
+
+# Load player stats
+players = load_dataset("noidvan/jaipur", "players")
+```
+
+## Game Rules Summary
+
+- **Setup**: 5 cards in market (3 camels + 2 goods initially), each player gets 5 cards
+- **Turn actions**:
+  - **Take**: Pick one good from market (deck refills) or take all camels
+  - **Sell**: Sell 1+ cards of same type for coins (premium goods require selling 2+)
+  - **Trade**: Swap 2+ cards with market (can offer camels)
+- **Coins**: Each good type has a coin stack with decreasing values (sell early = more coins)
+- **Bonuses**: Selling 3/4/5+ cards earns a random bonus token
+- **Round end**: 3 coin stacks empty OR deck exhausted. Most coins wins the round.
+- **Game end**: Best of 3 rounds (first to 2 "seals")
+
+## Variants
+
+| Variant | Games | Description |
+|---------|-------|-------------|
+| `open_info` | ~33,000 | Both players can see each other's hands |
+| `original` | ~5,500 | Standard rules — opponent's hand is hidden |
+
+The `opponent_hand` field is populated for all games regardless of variant (the server
+records full state). The `variant` field indicates what information was available to players
+during play, which affects their strategy.
+
+## Source & License
+
+- **Source**: Game replays from [Yucata.de](https://www.yucata.de), an online board game platform
+- **License**: [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/)
+- **Privacy**: All player identities are anonymized with irreversible hashing. Original
+  usernames are not recoverable from the dataset. The player ID `"unknown"` represents
+  unknown users (~1,400 games); They are excluded from the players table.
+
+## Citation
+
+```bibtex
+@dataset{jaipur_replays_2026,
+  title={Jaipur: Online Card Game Replays},
+  author={Yifan Lin},
+  year={2026},
+  url={https://huggingface.co/datasets/noidvan/jaipur},
+  license={CC-BY-NC-4.0}
+}
+```

data/games.parquet

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+size 75896870

data/players.parquet

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