Data Cleanup Day

Profile CSV, Parquet and JSON at speed with DuckDB/Polars and surface missingness, outliers and leakage first. Then run the right statistical test, plot it honestly, and ship an Excel report with the findings.

7 skills

Data Scientist (DuckDB/Polars)

Analyzes CSV, Parquet and JSON data at maximum speed by intelligently routing between DuckDB and Polars — never pandas.

Data & Analytics★ 67,531AI score 9/10

Statistical Analysis

A guided statistics workflow that picks the right test, verifies assumptions, reports effect sizes, and writes APA-formatted results.

Data & Analytics★ 33,030AI score 9/10

Scientific Visualization

Design, audit, and export truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly.

Data & Analytics★ 33,030AI score 9/10

Exploratory Data Analysis

Runs bounded, network-free exploratory profiling of authorized local scientific files with missingness, leakage, and outlier diagnostics.

Data & Analytics★ 33,030AI score 9/10

XLSX Spreadsheet Toolkit

Official

Official skill for reading, editing, and building Excel/CSV files with real formulas, professional formatting, and verified zero formula errors.

Docs & Office★ 167,132AI score 9/10

Seaborn Statistical Visualization

A reference skill that makes Claude write modern, correct seaborn 0.13 code for distributions, relationships and categorical comparisons from pandas DataFrames.

Data & Analytics★ 33,030AI score 8/10

Polars DataFrame Assistant

Teaches Claude idiomatic Polars — expressions, lazy queries, and pandas-to-Polars migration.

Data & Analytics★ 33,030AI score 8/10