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ericwang915
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csv_analyzer

Analyze CSV and Excel files with pandas and openpyxl for statistics and structure.

38|14|Updated Mar 1, 2026
Search Tags:#data#statistics#excel#csv#analyze#filter#groupby
One-click install
npx skills add https://github.com/ericwang915/PythonClaw --skill csv-analyzer-ericwang915
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: csv_analyzer
Source: https://github.com/ericwang915/PythonClaw/tree/main/pythonclaw/templates/skills/data/csv_analyzer
Command: npx skills add https://github.com/ericwang915/PythonClaw --skill csv-analyzer-ericwang915

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl.

What problem does it solve?

Automatically analyze and summarize tabular data stored in CSV, TSV, or Excel files, providing quick insights and actionable results.

Core Features & Use Cases

  • Descriptive statistics for numeric columns, including shape, column types, missing values.
  • Data previews and filtering via simple commands like head, query, and groupby.
  • Output-ready results for dashboards or reports in JSON or text formats.

Quick Start

Run the analyzer on a data file by executing python {skill_path}/analyze.py data.csv info.

Frequently Asked Questions about csv_analyzer

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

FAQPage Schema
How do I get summary statistics for a CSV file?▼

To get summary statistics for a CSV file, you can use an analyzer to expose descriptive stats, column types, and missing values. It parses tabular data to provide quick insights into numeric columns.

Can I filter and group Excel data without writing complex scripts?▼

Yes, you can filter and group Excel data using simple commands like query and groupby. This allows you to summarize and subset tabular data quickly without writing complex scripts.

Does pandas work with Excel files to analyze data quality and structure?▼

Pandas works with Excel files to analyze data quality and structure by relying on openpyxl to parse them. It exposes missing values, data types, and shape for quality assessment.

What is the best way to preview a large CSV dataset?▼

The best way to preview a large CSV dataset is by using the head command on an analyzer. It reads the file and outputs a structured preview of the initial rows.

Do I need openpyxl to analyze Excel files?▼

Yes, you need openpyxl to analyze Excel files because pandas relies on it to parse the format. This dependency enables reading and summarizing Excel data.

Can I output CSV analysis results in JSON format?▼

Yes, you can output CSV analysis results in JSON format. The analyzer produces output-ready results for dashboards or reports in either JSON or text formats.

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