Run a full exploratory data analysis — distributions, correlations, outliers, and visualisation code — on any CSV or DataFrame, with hypotheses and next steps.
Automates the exploratory data analysis (EDA) workflow for tabular data: generates distribution summaries, correlation matrices, missing-value heatmaps, outlier detection, and skew analysis. Suggests appropriate transformations (log, normalise, encode), proposes hypothesis tests (t-test, chi-square, ANOVA) with code, and outputs publication-ready charts using matplotlib/seaborn or plotly. Handles CSV, Parquet, and Pandas DataFrames. Inspired by analytics-data-analysis (551 installs, mindrally/skills) and the broader data-scientist skill category on skills.sh.
No account needed · Instant delivery · Secure Stripe checkout
Hand-picked Claude skills + tips for getting more out of your AI tools. No spam, unsubscribe anytime.
Weekly tips on using Claude effectively. Unsubscribe anytime.