explore-data

Profile datasets by computing statistics, null rates, and distribution patterns.

Updated Apr 18, 2026
One-click install
npx skills add https://github.com/Srujan0798/NRG --skill explore-data-srujan0798
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: explore-data
Source: https://github.com/Srujan0798/NRG/tree/main/.agents/skills/explore-data
Command: npx skills add https://github.com/Srujan0798/NRG --skill explore-data-srujan0798

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Profiling and exploring a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.

Core Features & Use Cases

  • Generate a comprehensive data profile: rows, columns, types, nulls, and cardinality.
  • Detect data quality issues: duplicates, suspicious values, and outliers.
  • Suggest follow-up analyses and potential dimensions and metrics for exploration.

Quick Start

Inspect a dataset by running the explore-data command on a connected table or uploaded file to generate a full profile.

Frequently Asked Questions about explore-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I profile a dataset to check data quality and null rates?▼

To profile a dataset for data quality, run a profile command on your table or uploaded file. It computes row and column statistics, data types, null rates, cardinality, and distribution patterns, returning a structured summary that highlights anomalies and duplicates.

Can I explore data in CSV, Excel, Parquet, and JSON files?▼

Yes, you can explore data in CSV, Excel, Parquet, and JSON files. The profiling tool analyzes uploaded files or data warehouse tables to compute statistics, detect suspicious values, and suggest follow-up analyses for analysts.

What is data profiling and when do I need to do it?▼

Data profiling is the process of examining a dataset to understand its shape, types, and patterns. You need it when encountering a new table or file, checking null rates and column distributions, or deciding which dimensions and metrics to analyze.

Does data profiling detect duplicates and outliers automatically?▼

Yes, data profiling detects duplicates and outliers automatically. It scans your dataset to compute distribution patterns and returns a structured profile that highlights data quality issues and suspicious values for further investigation.

What's the best way to summarize column statistics for a new table?▼

The best way to summarize column statistics for a new table is to generate a comprehensive data profile. It calculates row and column statistics, cardinality, null rates, and data types, providing a concise summary with recommended follow-up analyses.