data-analysis

name	data-analysis
description	Analyze datasets with spreadsheets, Python stats, plots, and reports.

Data Analysis

Use this skill when the user asks to analyze data, spreadsheets, CSV/XLSX files, experiment results, statistics, charts, dashboards, or model outputs.

Routing

1. For .xlsx, .xls, or spreadsheet work, prefer the Spreadsheets plugin and officecli-xlsx.
2. For experiment metrics and result folders, use analyze-results.
3. For statistical tests and reporting, use statistical-analysis.
4. For regression, time series, diagnostics, or inference tables, use statsmodels.
5. For scientific computing, optimization, interpolation, or numerical routines, use scipy.
6. For symbolic formulas or exact derivations, use sympy.
7. For graph/network datasets, use networkx.
8. For publication-quality figures, use plot-from-data.

Always preserve source data, produce reproducible code or notebooks/scripts when analysis is non-trivial, and verify generated tables/figures against the input data.