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Get Started Free →matlab/matlab-analyze-data
Analyze data using MATLAB.
Passed 23 of 23 test cases with the skill, and 13 of 23 without it.
and 9 more in the full report
10 fixed13 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a MATLAB statement to calculate the maximum value of a numeric vector sensorReadings that contains NaN entries, ignoring the missing values.
| Checked | Without skill | With skill |
|---|---|---|
| Passes empty array [] as the second argument to max | Passed | Passed |
| Passes 'omitmissing' as the third argument to max | Missed | Passed |
The instructions your model reads when the skill loads.
Generate idiomatic MATLAB code for tabular data analysis tasks using tables and timetables.
This skill covers core MATLAB functions for tabular and time-series workflows. These functions work natively with table and timetable, handle missing data correctly, and are performance-optimized. Prefer the modern functions recommended here (e.g., groupsummary, datetime, fillmissing) over legacy alternatives (e.g., accumarray, nanmean, datenum). Override only if the user explicitly requests otherwise.
Before writing code, read the reference file linked at the end of the relevant section below. Reference files contain correct syntax, common pitfalls, and "Avoid" patterns that prevent silent bugs. Skipping the reference risks using a deprecated approach or hitting a known pitfall.
Most functions in this skill are available in R2023a or earlier. The following require a newer release:
| Function | Available From | Purpose |
|---|---|---|
paddata, trimdata, resize | R2023b | Pad, trim, or resize arrays to target length |
clip | R2024a | Clamp values to a range |
summary (enhanced) | R2024b | Supports arrays (numeric, datetime, duration, logical); adds Statistics, DataVariables, Detail name-value args |
isapprox | R2024b | Tolerance-aware floating-point comparison (use instead of == for computed values) |
isbetween (numeric) | R2024b | Check elements within a numeric range |
numunique | R2025a | Count distinct values in a variable |
allbetween | R2025a | Validate all values are within a range |
allunique | R2025a | Validate all values are unique |
When data is already in a workspace variable, start by understanding its structure and contents. Use JSON output for reliable parsing — table display is designed for human-readable grids, but as text it is easy to misinterpret which values belong to which variables:
test cases passed, vs 13 / 23 without
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