Awesome-Agent-Skills-for-Empirical-Research wrangling-skills
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.
install
source · Clone the upstream repo
git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/43-wentorai-research-plugins/skills/analysis/wrangling" ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-wrangling-skills && rm -rf "$T"
manifest:
skills/43-wentorai-research-plugins/skills/analysis/wrangling/SKILL.mdsource content
Data Wrangling — 10 Skills
Select the skill matching the user's need, then
read| Skill | Description |
|---|---|
| csv-data-analyzer | Load, explore, clean, and analyze CSV data with statistical summaries |
| data-cleaning-pipeline | Systematic data cleaning workflows for research datasets |
| data-cog-guide | Upload messy CSVs with minimal prompting for deep automated analysis |
| missing-data-handling | Diagnose missing data patterns and apply appropriate imputation strategies |
| pandas-data-wrangling | Data cleaning, transformation, and exploratory analysis with pandas |
| questionnaire-design-guide | Questionnaire and survey design with Likert scales and coding |
| stata-data-cleaning | Clean, transform, and validate messy research data using Stata |
| streamline-analyst-guide | End-to-end data analysis AI agent with Streamlit UI |
| survey-data-processing | Clean, recode, and prepare survey response data for analysis |
| text-mining-guide | Apply NLP and text mining techniques to research text data |