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data-profiling

Official

Instantly summarize datasets without modeling.

Data & Analytics#data quality#report generation#data profiling#schema inference#dataset exploration#missing value#CSV Parquet
Authoraliyun
Version1.0.0
Installs0

System Documentation

What problem does it solve?

When you upload a dataset and need to quickly understand its shape and data quality, this Skill generates a clear data profiling report (rows, columns, field types, missing rates, distributions) without running any modeling metrics.

Core Features & Use Cases

  • Dataset structure overview: Produces a fast report including file info, row/column counts, and inferred field-type distribution.
  • Field-level description: Lists each column’s inferred type, missing rate, unique value count, and a few example values.
  • Quality & preview insights: Highlights issues such as duplicate rows, empty/constant columns, and high-missing-rate fields, plus a small sample preview.
  • Use case: After you receive a financial dataset file (CSV/Parquet), run this Skill to decide what to do next (e.g., whether you need deeper feature analysis or modeling).

Quick Start

Ask the agent to run data-profiling on your dataset file path to generate a profiling markdown report and a structured result manifest for downstream steps.

Dependency Matrix

Required Modules

pandasnumpy

Components

scripts

đź’» Claude Code Installation

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Please help me install this Skill:
Name: data-profiling
Download link: https://github.com/aliyun/qwen-dianjin/archive/main.zip#data-profiling

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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