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wrangling-skills

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10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.

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Source SKILL.md: https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/blob/HEAD/skills/43-wentorai-research-plugins/skills/analysis/wrangling/SKILL.md

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Data Wrangling — 10 Skills

Select the skill matching the user's need, then read its SKILL.md.

SkillDescription
csv-data-analyzerLoad, explore, clean, and analyze CSV data with statistical summaries
data-cleaning-pipelineSystematic data cleaning workflows for research datasets
data-cog-guideUpload messy CSVs with minimal prompting for deep automated analysis
missing-data-handlingDiagnose missing data patterns and apply appropriate imputation strategies
pandas-data-wranglingData cleaning, transformation, and exploratory analysis with pandas
questionnaire-design-guideQuestionnaire and survey design with Likert scales and coding
stata-data-cleaningClean, transform, and validate messy research data using Stata
streamline-analyst-guideEnd-to-end data analysis AI agent with Streamlit UI
survey-data-processingClean, recode, and prepare survey response data for analysis
text-mining-guideApply NLP and text mining techniques to research text data