“Data analysis”

High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data.

Profile and aggregate a bundled sales dataset - group revenue by region, category, channel or month, apply filters, and compute sums, means, medians and ranges.

Scientific data analysis including data cleaning, exploratory data analysis (EDA), statistical testing, regression, and reporting.

Data analysis from external services.

Handle statistical data analysis tasks: t-tests, regression, correlation analysis, data visualization, CSV processing, hypothesis testing, effect size…

对 CSV、Excel、ZIP 或其他附件数据执行可复现的数据清洗、统计、建模、图表和报告工作；用户要求 data science 报告、探索性分析、预测或从数据生成交付文件时使用。

Use for exploratory analysis, statistical analysis, trends, cohorts, segmentation, variance drivers, forecasting inputs, analytical visualisation or decision…

Answer a business question from a database, warehouse or spreadsheet: SQL, EDA, a decision memo.

Analyses a dataset correctly and reports what it shows.

用于数据分析任务，提供统计方法和可视化建议

Analyse a dataset like a data scientist — profile it, find the signal, explain it.

Use when analysing tabular data — CSV, Excel or JSON — computing aggregates, finding anomalies, cleaning messy data, or answering questions about a dataset…

数据分析与可视化 (Use when: 需要处理 CSV/Excel 数据、生成图表、统计分析).

Explore, clean, and summarize tabular data.

Compute over a .csv or .xlsx in a script the sandbox keeps, cite every figure to its cell, and draw the result as a plain SVG chart

对上传的数据文件进行分析，生成统计摘要和可视化建议

数据分析专家 — 数据探索、统计分析、可视化建议和洞察输出

Análisis estadístico de datasets con Pandas y NumPy — explora, correlaciona, testea hipótesis y extrae conocimiento no obvio.

数据解读与分析 — 统计方法、趋势分析、透视汇总、结论输出规范

数据分析技能，激活计算器与沙盒文件工具，支持数值计算与结果导出

Economic data-analysis discipline.

Analyze user behavior patterns through quantitative data to validate hypotheses and discover product growth drivers.

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.

This skill should be used when users need to analyze CSV or Excel files, understand data patterns, generate statistical summaries, or create data…