tpot1515/pokemoncards

---
license: mit
task_categories:
- image-classification
- image-segmentation
- sentence-similarity
- image-to-text
- image-feature-extraction
language:
- en
pretty_name: Pokemon Cards TCG Dataset
size_categories:
- 10M<n<100M
---

# Dataset Card for Pokemon Cards TCG

## Dataset Description

- **Repository:** [tooniez/pokemoncards_tcg](https://github.com/tooniez/pokemoncards_tcg.git)
- **Point of Contact:** [@tooniez](https://github.com/tooniez)

### Dataset Summary

This dataset contains information about Pokemon Trading Card Game (TCG) cards, decks, and sets. It is designed to be used for training machine learning models to classify and analyze Pokemon cards.

### Supported Tasks and Leaderboards

- **Tasks:**
- Image Classification
- Text Classification
- Information Retrieval
- Image-to-Text
- Image Feature Extraction
- Image Segmentation
- Image Classification

### Languages

The dataset is primarily in English.

## Dataset Structure

### Data Instances

The dataset consists of three main components:

1. Cards: Detailed information about individual Pokemon cards.
2. Decks: Collections of cards forming playable decks.
3. Sets: Information about different Pokemon card sets.

### Data Fields

- Cards:
- id: Unique identifier for the card
- name: Name of the Pokemon or card
- supertype: Type of card (e.g., Pokemon, Trainer, Energy)
- subtypes: Subtypes of the card
- hp: Hit points (for Pokemon cards)
- types: Element types of the Pokemon
- evolves_from: Name of the Pokemon this card evolves from
- abilities: Special abilities of the Pokemon
- attacks: Attacks the Pokemon can use
- weaknesses: Elemental weaknesses
- resistances: Elemental resistances
- retreat_cost: Cost to retreat the Pokemon
- converted_retreat_cost: Numeric value of retreat cost
- set: Set the card belongs to
- number: Card number within the set
- artist: Name of the card artist
- rarity: Rarity of the card
- flavor_text: Descriptive text on the card
- national_pokedex_numbers: Pokedex numbers for the Pokemon
- legalities: Legal status in different game formats
- images: URLs to card images

- Decks:
- id: Unique identifier for the deck
- name: Name of the deck
- types: Types of cards in the deck
- card_id: Unique identifier for each card in the deck
- card_name: Name of each card in the deck
- card_rarity: Rarity of each card in the deck
- card_count: Number of copies of each card in the deck

- Sets:
- id: Unique identifier for the set
- name: Name of the set
- series: Series the set belongs to
- printedTotal: Total number of cards printed in the set
- total: Total number of cards in the set
- legalities: Legal status in different game formats
- ptcgoCode: Code used in the Pokemon Trading Card Game Online
- releaseDate: Date the set was released
- updatedAt: Date the set information was last updated
- symbol_image_source: URL to the set symbol image
- logo_image_source: URL to the set logo image

## Dataset Creation

### Curation Rationale

This dataset was created to provide a comprehensive resource for Pokemon TCG enthusiasts, collectors, and researchers. It aims to facilitate machine learning projects related to card classification, price prediction, and deck analysis.

### Source Data

#### Initial Data Collection and Normalization

[Describe the process of data collection and any normalization steps]

#### Who are the source language producers?

The data is sourced from official Pokemon TCG information and community-contributed data.

### Annotations

[If there are any annotations in the dataset, describe them here]

### Personal and Sensitive Information

This dataset does not contain personal or sensitive information.

## Considerations for Using the Data

### Social Impact of Dataset

This dataset can contribute to the Pokemon TCG community by enabling research and tool development for card analysis and deck building.

### Licensing Information

[Specify the license under which the dataset is released]

### Citation Information

[If there's a specific way to cite this dataset, include it here]

许可证：MIT许可证
任务类别：
- 图像分类
- 图像分割
- 句对相似度
- 图像转文本
- 图像特征提取
语言：
- 英语
数据集名称：Pokemon Cards TCG Dataset（宝可梦集换式卡牌游戏数据集）
规模类别：1000万<样本量<1亿

---

# 宝可梦集换式卡牌游戏数据集卡片

## 数据集说明
- **仓库地址**：[tooniez/pokemoncards_tcg](https://github.com/tooniez/pokemoncards_tcg.git)
- **联系方式**：[@tooniez](https://github.com/tooniez)

### 数据集概述
本数据集收录了宝可梦集换式卡牌游戏（Pokemon Trading Card Game, TCG）的卡牌、卡组与系列套装的相关信息，旨在为训练机器学习模型以分类、分析宝可梦卡牌提供支撑。

### 支持任务与基准排行榜
- **任务**：
- 图像分类
- 文本分类
- 信息检索
- 图像转文本
- 图像特征提取
- 图像分割
- 图像分类

### 语言说明
本数据集主要采用英语编写。

## 数据集结构
### 数据实例
本数据集包含三大核心组成部分：
1. **卡牌（Cards）**：单张宝可梦卡牌的详细信息
2. **卡组（Decks）**：构成可对战卡组的卡牌集合
3. **套装（Sets）**：不同宝可梦卡牌套装的相关信息

### 数据字段
- **卡牌（Cards）**：
- `id`：卡牌唯一标识符
- `name`：宝可梦或卡牌的名称
- `supertype`：卡牌类型（例如宝可梦、训练家、能量）
- `subtypes`：卡牌子类型
- `hp`：宝可梦卡牌的生命值（Hit Points, HP）
- `types`：宝可梦的属性类型
- `evolves_from`：该卡牌进化自的宝可梦名称
- `abilities`：宝可梦的特殊能力
- `attacks`：宝可梦可使用的招式
- `weaknesses`：宝可梦的属性弱点
- `resistances`：宝可梦的属性抗性
- `retreat_cost`：宝可梦撤退所需的费用
- `converted_retreat_cost`：撤退费用的数值表示
- `set`：该卡牌所属的套装
- `number`：该卡牌在所属套装中的编号
- `artist`：卡牌插画师姓名
- `rarity`：卡牌的稀有度
- `flavor_text`：卡牌上的风味描述文本
- `national_pokedex_numbers`：宝可梦的全国图鉴编号
- `legalities`：该卡牌在不同对战格式中的合法状态
- `images`：卡牌图片的下载链接

- **卡组（Decks）**：
- `id`：卡组唯一标识符
- `name`：卡组名称
- `types`：卡组内卡牌的类型
- `card_id`：卡组内每张卡牌的唯一标识符
- `card_name`：卡组内每张卡牌的名称
- `card_rarity`：卡组内每张卡牌的稀有度
- `card_count`：卡组内每张卡牌的复制品数量

- **套装（Sets）**：
- `id`：套装唯一标识符
- `name`：套装名称
- `series`：该套装所属的系列
- `printedTotal`：该套装印刷的卡牌总数量
- `total`：该套装包含的卡牌总数量
- `legalities`：该套装在不同对战格式中的合法状态
- `ptcgoCode`：宝可梦集换式卡牌游戏在线版（Pokemon Trading Card Game Online）使用的套装代码
- `releaseDate`：套装的发售日期
- `updatedAt`：套装信息的最后更新日期
- `symbol_image_source`：套装标志图片的下载链接
- `logo_image_source`：套装logo图片的下载链接

## 数据集构建
### 构建初衷
本数据集旨在为宝可梦集换式卡牌游戏爱好者、收藏者与研究人员提供一套全面的资源，助力开展与卡牌分类、价格预测以及卡组分析相关的机器学习项目。

### 源数据
#### 初始数据收集与归一化流程
[描述数据收集过程及相关归一化步骤]
#### 源语言生成者
本数据集的信息来源于官方宝可梦集换式卡牌游戏资料以及社区贡献的数据。

### 标注信息
[若数据集包含标注内容，请在此处描述相关信息]

### 个人与敏感信息说明
本数据集不包含任何个人或敏感信息。

## 数据集使用注意事项
### 数据集的社会影响
本数据集可助力宝可梦集换式卡牌游戏社区开展卡牌分析、卡组构建相关的研究与工具开发，从而推动社区发展。

### 许可证信息
[指定该数据集发布所遵循的许可证条款]

### 引用信息
[若该数据集有特定的引用方式，请在此处注明]