dataset-finder

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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.

modbender By modbender schedule Updated 3/6/2026
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name: dataset-finder

description: "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."

license: Proprietary

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:

Install via CLI
npx skills add https://github.com/modbender/skill-library-mcp --skill dataset-finder
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