Skill UI

This advanced helper assists users in writing, debugging, and validating complex formulas, pivot tables, and array functions for platforms like Excel and Google Sheets. It ensures formulas are robust by handling common edge cases (e.g., blank rows, mixed data types, time zone quirks) and provides detailed, worked examples. It also manages cross-platform dialect translation.

This comprehensive guide provides advanced skills and references for writing, debugging, and systematically optimizing DAX in semantic models. It covers deep architectural topics, including engine internals, multi-tiered optimization workflows, and best practices for performance profiling. Use it to troubleshoot slow queries and ensure robust data model performance across Power BI Desktop and Fabric Service.

This skill enables the creation of advanced, highly customized visualizations directly within Power BI reports (PBIR). By utilizing powerful Python libraries like Matplotlib and Seaborn, users can process data via pandas DataFrames and render complex statistical charts (e.g., bar charts, line graphs) into static PNG images. It provides a structured workflow, covering script injection, validation, and best practices, significantly enhancing the depth and professionalism of business reports.

This skill guides the creation of advanced, publication-quality statistical visualizations within Power BI using the R programming language, primarily leveraging the ggplot2 package. It details the entire workflow, from structuring the visual JSON (using `pbir-format`) to writing the mandatory `ggplot2` script and correctly injecting it into the report. Ideal for data scientists needing to render complex, customized charts that surpass standard Power BI visuals. Static PNG output is generated, ensuring high fidelity for reports.

Calculates statistical power and required sample sizes for study planning. It supports both closed-form methods (for standard tests like t-tests, ANOVA) and simulation-based methods (for complex models like mixed models or survival analysis). Use this skill to determine the minimum detectable effect (MDE) or justify sample sizes for grants and IRB protocols before data collection.