matlab-analyze-data

What problem does it solve?

This Skill helps you generate idiomatic MATLAB code to analyze tabular and time-series data efficiently and correctly, reducing the chance of wrong functions or error-prone handling of missing values.

Core Features & Use Cases

• Tabular and timetable analysis: explore, clean, transform, aggregate, and answer questions using table and timetable workflows.
• Missing/outlier/range-safe processing: use MATLAB-native missing detection and cleaning patterns (ismissing, standardizeMissing, fillmissing, isoutlier/rmoutliers, clip/isbetween) instead of brittle comparisons.
• Time-aware operations: convert to timetable to unlock spacing-aware resampling and time-based computation (table2timetable, retime, smoothdata, timerange, synchronize).
• Real-world examples: generating code for tasks like “summarize by region,” “find top-N rows,” “clean missing values then compute group stats,” and “analyze trends with smoothing and change points.”

Quick Start

Use the matlab-analyze-data skill to write MATLAB code that summarizes and cleans a table T with columns such as dates, categories, and numeric measurements, then computes grouped statistics and answers specific questions about the results.