survey-analyzer
Analyze survey responses with Likert scale analysis, cross-tabulations, sentiment scoring, and frequency distributions with visualizations.
Profile →npx skills add majiayu000/claude-skill-registry --skill survey-analyzer-dkyazzentwatwa-chatgpt-skills-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Survey Analyzer Comprehensive survey data analysis with Likert scales, cross-tabs, and sentiment analysis. ## Features - **Likert Scale Analysis**: Agreement scale scoring and visualization - **Cross-Tabulation**: Relationship analysis between categorical variables - **Frequency Analysis**: Response distributions and percentages - **Sentiment Scoring**: Text response sentiment analysis - **Open-Ended Analysis**: Theme extraction from text responses - **Statistical Tests**: Chi-square, correlations, significance testing - **Visualizations**: Bar charts, heatmaps, word clouds, distribution plots - **Report Generation**: Comprehensive PDF/HTML reports ## Quick Start ```python from survey_analyzer import SurveyAnalyzer analyzer = SurveyAnalyzer() # Load survey data analyzer.load_csv('survey_responses.csv') # Analyze Likert scale question results = analyzer.likert_analysis('satisfaction', scale_type='agreement') print(f"Mean score: {results['mean_score']:.2f}") # Cross-tabulation crosstab = analyzer.crosstab('age_group', 'product_preference') print(crosstab) # Generate report analyzer.generate_report('survey_report.pdf') ``` ## CLI Usage ```bash # Analyze Likert scale python survey_an
- Features
- Quick Start
- CLI Usage
- API Reference
- SurveyAnalyzer Class
- Likert Scale Analysis
- Standard Scales
- Results
- Visualization
- Frequency Analysis
- Single Choice
- Multiple Choice
- Cross-Tabulation
- Basic Cross-Tab
Analyze Likert scale python survey_analyzer.py --data survey.csv --likert satisfaction --output results.pdf Cross-tabulation python survey_analyzer.py --data survey.csv --crosstab age_group product --output crosstab.png Sentiment analysis python survey_analyzer.py --data survey.csv --sentiment comments --output sentiment.html Full report python survey_analyzer.py --data survey.csv --report --output full_report.pdf
What does the survey-analyzer skill do?
Analyze survey responses with Likert scale analysis, cross-tabulations, sentiment scoring, and frequency distributions with visualizations.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill survey-analyzer-dkyazzentwatwa-chatgpt-skills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.