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:

1. Data Loading & Inspection — Read CSV files, detect column types, and display basic structure (shape, columns, sample rows)
2. Data Cleaning — Identify and handle missing values, duplicates, and type inconsistencies
3. Statistical Summary — Compute descriptive statistics (mean, median, mode, standard deviation, percentiles) for numeric columns
4. Filtering & Grouping — Slice data by conditions and aggregate by categories
5. Correlation Analysis — Find relationships between numeric variables
6. 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