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