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Use when computing descriptive statistics, generating ASCII histograms, calculating correlation matrices, d...\n\nTags: latest:1.0.1\n\nVersion history:\n\nv1.0.1 | 2026-04-17T06:27:03.687Z | user\n\nFix: align SKILL.md commands with script implementation\n\nv1.0.0 | 2026-04-17T06:13:19.549Z | user\n\nInitial release\n\nArchive index:\n\nArchive v1.0.1: 4 files, 5933 bytes\n\nFiles: scripts/script.sh (13203b), skill-card.md (1915b), SKILL.md (1457b), _meta.json (128b)\n\nFile v1.0.1:SKILL.md\n\n---\nname: \"r-analyst\"\ndescription: \"R-style statistical analysis powered by Python 3. Use when computing descriptive statistics, generating ASCII histograms, calculating correlation matrices, detecting missing values and outliers, or describing CSV dataset structure.\"\n---\n\n# r-analyst\n\n## Triggers on\nr statistics, csv analysis, data correlation, missing values, ascii histogram, describe dataset, r summary, outlier detection, pearson correlation\n\n## What This Skill Does\nPerform R-style data analysis on CSV files using Python 3. No R installation required.\n\n## Commands\n\n### stats\nCompute descriptive statistics (R-style summary: Min/1st Qu/Median/Mean/3rd Qu/Max/SD).\n```bash\nbash scripts/script.sh stats <file.csv> [column]\n```\n\n### plot\nGenerate an ASCII histogram for a numeric column.\n```bash\nbash scripts/script.sh plot <file.csv> [column] [bins]\n```\n\n### correlate\nCompute Pearson correlation matrix for all numeric columns.\n```bash\nbash scripts/script.sh correlate <file.csv>\n```\n\n### clean\nDetect missing values and statistical outliers (3σ rule).\n```bash\nbash scripts/script.sh clean <file.csv>\n```\n\n### describe\nShow dataset structure, column types, unique value counts, and sample values.\n```bash\nbash scripts/script.sh describe <file.csv>\n```\n\n### help\nShow all available commands.\n```bash\nbash scripts/script.sh help\n```\n\n## Requirements\n- bash 4+\n- python3 (standard library only — no R needed)\n\nPowered by BytesAgain | bytesagain.com\n\nFile v1.0.1:_meta.json\n\n{\n  \"ownerId\": \"kn73mq8fmvt64rz26m55z10wb982krr4\",\n  \"slug\": \"r-analyst\",\n  \"version\": \"1.0.1\",\n  \"publishedAt\": 1776407223687\n}\n\nFile v1.0.1:skill-card.md\n\n## Description:\n\nR-style statistical analysis powered by Python 3 for descriptive statistics, ASCII histograms, Pearson correlation matrices, missing value and outlier checks, and CSV structure summaries.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[loutai0307-prog](https://clawhub.ai/user/loutai0307-prog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers, analysts, and data practitioners use this skill to run local R-style summaries over CSV files without installing R. It helps inspect dataset shape, numeric distributions, correlations, missing values, and simple outlier signals.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Very large CSVs or excessive histogram bin counts can consume local compute or make terminal output unwieldy.\n\nMitigation: Run the skill on trusted, reasonably sized CSVs and choose practical histogram bin counts.\n\nRisk: The skill reads local CSV files selected by the user, so sensitive dataset contents may appear in analysis output.\n\nMitigation: Use only approved datasets and review generated summaries before sharing output.\n\n## Reference(s):\n\n- [ClawHub Skill Page](https://clawhub.ai/loutai0307-prog/skills/r-analyst)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, shell commands, guidance]\n\n**Output Format:** [Markdown or terminal text with tabular statistics, ASCII histograms, and inline shell commands]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Local CSV analysis output generated by bash and Python 3 standard-library code.]\n\n## Skill Version(s):\n\n1.0.1 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.0: 3 files, 4777 bytes\n\nFiles: scripts/script.sh (13203b), SKILL.md (1507b), _meta.json (128b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: \"r-analyst\"\ndescription: \"Statistical analysis and visualization in R. Use when running regression, plotting data, cleaning datasets, computing statistics, or generating ggplot2 charts.\"\n---\n\n# R Analyst\n\nStatistical analysis and visualization in R. Use when running regression, plotting data, cleaning datasets, computing statistics, or generating ggplot2 charts.\n\n## Triggers on\nr statistics, csv analysis, data correlation, missing values, ascii plot, describe dataset, r summary\n\n## When to Use\n\n- Working with r analyst and need quick reference\n- Looking up general standards or best practices for r analyst\n- Troubleshooting r analyst issues\n- Need a checklist or guide for r analyst tasks\n\n## Commands\n\n### `intro`\n\n```bash\nscripts/script.sh intro\n```\n\nOverview and background\n\n### `theory`\n\n```bash\nscripts/script.sh theory\n```\n\nCore theory and principles\n\n### `methods`\n\n```bash\nscripts/script.sh methods\n```\n\nMethods and techniques\n\n### `tools`\n\n```bash\nscripts/script.sh tools\n```\n\nTools and software\n\n### `standards`\n\n```bash\nscripts/script.sh standards\n```\n\nStandards and protocols\n\n### `experiments`\n\n```bash\nscripts/script.sh experiments\n```\n\nPractical experiments and labs\n\n### `glossary`\n\n```bash\nscripts/script.sh glossary\n```\n\nKey terminology\n\n### `references`\n\n```bash\nscripts/script.sh references\n```\n\nFurther reading and references\n\n### `help`\n\n```bash\nscripts/script.sh help\n```\n\n### `version`\n\n```bash\nscripts/script.sh version\n```\n\n\nPowered by BytesAgain | bytesagain.com\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn73mq8fmvt64rz26m55z10wb982krr4\",\n  \"slug\": \"r-analyst\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776406399549\n}","readmeExcerpt":"Skill: R Analyst Owner: loutai0307-prog Summary: R-style statistical analysis powered by Python 3. 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Use when computing descriptive statistics, generating ASCII histograms, calculating correlation matrices, detecting missing values and outliers, or describing CSV dataset structure.\"\n---\n\n# r-analyst\n\n## Triggers on\nr statistics, csv analysis, data correlation, missing values, ascii histogram, describe dataset, r summary, outlier detection, pearson correlation\n\n## What This Skill Does\nPerform R-style data analysis on CSV files using Python 3. 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