data-analysis

Q: How do I install data-analysis?

Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill data-analysis in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/data-analysis/ (personal) or .claude/skills/data-analysis/ (project).

by lingzhi227Testing & QA

Generate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.

Installs: 2K
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/lingzhi227/agent-research-skills --skill data-analysis

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads data-analysis automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Data Analysis

Generate rigorous statistical analysis code with multi-round review.

Input

$0 — Data source (CSV, JSON, pickle, or experiment logs)
$1 — Research goal or hypothesis to test

References

4-round code review prompts: ~/.claude/skills/data-analysis/references/review-prompts.md

Scripts

Statistical summary and comparison

python ~/.claude/skills/data-analysis/scripts/stat_summary.py --input results.csv --compare method --metric accuracy --output summary.json
python ~/.claude/skills/data-analysis/scripts/stat_summary.py --input results.csv --describe

Detects data types, recommends tests, runs comparisons, outputs effect sizes and significance stars. Requires numpy, scipy.

Format p-values

python ~/.claude/skills/data-analysis/scripts/format_pvalue.py --values "0.001 0.05 0.23" --format stars
python ~/.claude/skills/data-analysis/scripts/format_pvalue.py --csv results.csv --column pvalue --format latex

Formats p-values with stars, LaTeX notation, or plain text. Stdlib-only.

Workflow

Step 1: Generate Analysis Code

Structure the code with these sections:

# IMPORT — pandas, numpy, scipy, statsmodels, sklearn
# LOAD DATA — Load from original data files
# DATASET PREPARATIONS — Missing values, units, exclusion criteria
# DESCRIPTIVE STATISTICS — Summary tables if needed
# PREPROCESSING — Dummy variables, normalization
# ANALYSIS — Statistical tests per hypothesis
# SAVE ADDITIONAL RESULTS — Extra results to pickle

Step 2: 4-Round Code Review

Round 1 — Code Flaws: Mathematical/statistical errors, wrong calculations, trivial tests
Round 2 — Data Handling: Missing values, units, preprocessing, test choice
Round 3 — Per-Table: Sensible values, measures of uncertainty, missing data
Round 4 — Cross-Table: Completeness, consistency, missing variables

Step 3: Produce Results

Every nominal value must have uncertainty (CI, STD, or p-value)
Statistical tests must be appropriate for the data type
Results must match actual data — never hallucinate

Allowed Packages

pandas, numpy, scipy, statsmodels, sklearn, pickle

Statistical Test Selection

Data Type	Test
Two groups, normal	Independent t-test
Two groups, non-normal	Mann-Whitney U
Paired samples	Paired t-test / Wilcoxon
Multiple groups	ANOVA / Kruskal-Wallis
Categorical	Chi-square / Fisher's exact
Correlation	Pearson / Spearman
Regression	OLS / Logistic / Mixed effects

Rules

Always report p-values for statistical tests
Account for relevant confounding variables
Use inherent package functionality (e.g., formula = "y ~ a * b" for interactions)
Do not manually implement available statistical functions
Access dataframes using string-based column names, not integer indices

Related Skills

Upstream: experiment-code, experiment-design
Downstream: table-generation, figure-generation, backward-traceability
See also: math-reasoning

FAQ

What does the data-analysis skill do?

How do I install data-analysis?

Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill data-analysis in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/data-analysis/ (personal) or .claude/skills/data-analysis/ (project).

Which AI agents can use data-analysis?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is data-analysis safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains data-analysis?

It is published by lingzhi227 in lingzhi227/agent-research-skills. It has 1,988 recorded installs.