What problem does it solve?
AI-driven hybrid data analysis workflow across R (tidyverse and ggplot2) and Python (pandas and seaborn) that reduces repetitive tasks by providing templates for common steps and AI-generated code, speeding up cleaning, processing, visualization, and reporting, including Quarto qmd integration.
Core Features & Use Cases
- Hybrid templates for standard patterns (explore_variable, clean_data, process_data, plot_scatter, plot_bar, plot_box, statistical_test, plot_dag, tte_cloning) in R and their Python equivalents.
- AI-assisted code generation for custom data needs when templates do not fit.
- Built-in MCP Context7 guidance and QMD integration practices to streamline reproducible reporting.
- Renders ready-to-run scripts and supports lifecycle phases: Understand, Prepare, Analyze, Visualize, and Report.
Quick Start
Describe your data task and let the templates or AI generate runnable code you can execute to start analysis.