exploratory-data-analysis
Category: data-science-and-ml · License: MIT · Version: 1.2 · Includes scripts
Tags: exploratory data analysis, data profiling, data quality, scientific data
When to use it
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.Example requests
Ask your agent in plain language, for example:- “Can you do a quick EDA on assay_results.csv before I start modeling?”
- “I have plasma_cytokines_v3.tsv from a 3-site cohort study, with repeated visits per participant and columns subject_id, site, visit, IL6, TNFa, split. I’m worried the train/test split leaks and that missing IL6 values aren’t random. Can you audit this before I fit a random forest? Some IL6 values are below the LOQ and coded as 0.”
- “My measurements are heavily right-skewed and a few points look extreme. Before I decide whether to log-transform or drop them, I’d like to see how much those points drive the mean and spread in my exported table.”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole data-science-and-ml category with /plugin install data-science-and-ml@research-agent-skills.