CSV Data Analyzer

A skill that enables Claw to load, explore, analyze, and visualize CSV datasets, providing statistical insights and answering questions about the data.

What This Skill Does

This skill equips Claw with a structured approach to CSV data analysis:

Data Loading & Inspection — Read CSV files, detect column types, and display basic structure (shape, columns, sample rows)
Data Cleaning — Identify and handle missing values, duplicates, and type inconsistencies
Statistical Summary — Compute descriptive statistics (mean, median, mode, standard deviation, percentiles) for numeric columns
Filtering & Grouping — Slice data by conditions and aggregate by categories
Correlation Analysis — Find relationships between numeric variables
Visualization — Generate charts (bar, line, scatter, histogram) to illustrate patterns

How to Use

Provide a CSV file and ask Claw to analyze it:

"Analyze this sales data and tell me which product category has the highest revenue"
"Find outliers in the temperature column of this dataset"
"Create a chart showing monthly trends from this CSV"
"Compare group A vs group B performance in this experiment data"

Requirements

Input must be a valid CSV file (comma-separated by default; other delimiters can be specified)
Python with pandas and matplotlib should be available in the environment

Output

Summary statistics table
Key insights in plain language
Charts saved as PNG files when visualization is requested
Cleaned dataset exported as a new CSV if data cleaning was performed