Data-science runtime optimized for iterative coding and streamed analysis in the co-scientist loop.
This page explains what DS-Star is, who should use it, and why it may be the right agent for your workflow.
DS-Star is a data-science agent designed for real-world analysis tasks that involve messy, multi-file datasets and open-ended questions. It can work across different file formats, combine information from multiple sources, and produce full research-style reports instead of only short answers. In evaluations, DS-Star performs especially well on harder tasks that require multi-file reasoning and code-based analysis.
QUESTION
🚢 Using the /app/custom_data/titanic.csv dataset, write a short report for a general audience with: 1) overall survival rate, 2) survival rate by sex, 3) survival rate by passenger class (Pclass)
EXPECTED ANSWER
Overall survival: 38.38% (342/891). By sex: female 74.20% (233/314), male 18.89% (109/577). By class: 1st 62.96% (136/216), 2nd 47.28% (87/184), 3rd 24.24% (119/491).