hugging-face-dataset-creator

slug	hf_dataset_creator
name	Hugging Face Dataset Creator
summary	Create and manage datasets on Hugging Face Hub with support for agricultural data, sensor readings, and farm-related datasets
description	Adapted from Hugging Face's dataset creator skill for FF-Terminal, this skill provides comprehensive tools for creating, managing, and publishing datasets on the Hugging Face Hub. Specialized for agricultural and farm-related data including sensor readings, crop yields, weather data, soil measurements, and farming operations data. Supports multiple dataset formats and provides quality assurance features for data integrity.
version	0.1.0
tags	["huggingface","datasets","agriculture","farming","data-management","iot","sensors","research"]
triggers	["dataset","huggingface","agricultural data","farm data","sensor data","crop data","upload data","publish dataset","create dataset"]
priority	default
assets	[]
recommended_tools	["analyze_data","write_file","run_command","tavily_search","generate_image_gemini"]

Hugging Face Dataset Creator for FF-Terminal

Overview

This skill enables you to create, manage, and publish datasets on the Hugging Face Hub with a focus on agricultural and farm-related data. It provides tools for dataset initialization, configuration management, and efficient data uploads.

When to Use This Skill

Use this skill when you need to:

• Create new datasets for agricultural research or farm management
• Upload sensor data, crop yield data, weather measurements, or soil analysis results
• Structure farm operational data for machine learning projects
• Publish datasets for collaboration with the agricultural research community
• Manage existing datasets on the Hugging Face Hub

Key Capabilities

1. Dataset Types Supported

• Sensor Data: IoT sensor readings, soil moisture, temperature, humidity
• Crop Data: Yield measurements, growth stages, harvest records
• Weather Data: Historical weather patterns, forecasts, climate data
• Soil Analysis: pH levels, nutrient content, compaction measurements
• Farm Operations: Equipment usage, labor records, input applications
• Economic Data: Cost analysis, market prices, profitability metrics

2. Dataset Formats

• Tabular/CSV: Structured data with proper column headers
• JSON: Nested data structures for complex farm records
• Time Series: Temporal data with timestamps for trend analysis
• Geospatial: Location-based data with GPS coordinates
• Image/Multimedia: Field photos, drone imagery, sensor visualizations

3. Quality Assurance

• Data validation and format checking
• Duplicate detection and removal
• Missing data handling strategies
• Data type consistency verification
• Metadata completeness checks

Prerequisites

• Hugging Face account with write permissions
• HF_TOKEN environment variable set
• Python packages: huggingface_hub, pandas, pyarrow

Usage Workflow

Step 1: Initialize Dataset

from huggingface_hub  HfApi

api = HfApi()
api.create_repo(
    repo_id=,
    repo_type=,
    private=,
    token=your_hf_token
)