Analyze CSV, JSON, Excel, and Pandas DataFrames with profiling and hypothesis testing.
npx skills add https://github.com/inho-team/qe-framework --skill qdata-analysis
Please help me install this Agent Skill. Skill: Qdata-analysis Source: https://github.com/inho-team/qe-framework/tree/main/skills/Qdata-analysis Command: npx skills add https://github.com/inho-team/qe-framework --skill qdata-analysis
It enables structured, end-to-end data analysis workflows in a repeatable, auditable manner to turn raw data into actionable insights.
Run an end-to-end data analysis on a dataset to generate a summary report with visualizations.
High-intent search queries and answers about installing and using this skill.
Structured data analysis on a CSV file involves data profiling, missing value checks, and basic statistics to turn raw datasets into actionable insights. The workflow enforces sample data display and generates a summary report with visualizations.
Yes, you can run hypothesis testing on Pandas DataFrames with non-parametric tests when normality fails. The analysis enforces confidence intervals and robust reporting of findings to ensure valid statistical conclusions from your data.
The best way to analyze relationships and distributions in raw datasets is through distribution and relationship analyses, including correlations and cross-tabulations. This process identifies patterns and enforces data quality checks for reliable insights.
Yes, this data profiling approach supports JSON and Excel formats, alongside CSV and Pandas DataFrames. It performs missing value analysis and basic statistics across these formats to generate visualization recommendations and ready-to-use code templates.
To get visualization recommendations for your data analysis report, run an end-to-end analysis on your dataset. The process provides ready-to-use code templates for charts and reports, along with an insights summary and guidance for next steps.
If your raw dataset fails normality checks during distribution analysis, apply non-parametric tests. The analysis workflow automatically supports these tests when normality fails, ensuring robust reporting of findings and maintaining valid confidence intervals.
rar-fileAnalyze datasets to extract insights and present actionable findings.
hmzainjamilGenerate formatted reports with charts, tables, and metric summaries from structured data.
YuvalShafririReview dashboard code and suggest UX and data visualization improvements.
nferrer-devPerform statistical hypothesis testing with assumption checks and APA-formatted reporting.
