A curated library of ready-to-use SQL, Python, and R patterns for common data cleaning, transformation, analysis, and reporting tasks.
A curated, practical library of vetted SQL, Python, and R snippets for common data tasks (cleaning, validation, transformation, aggregation, sampling, and reporting). Each snippet includes usage notes, inputs/outputs, performance cautions, and adaptation guidance so analysts produce reliable, reproducible results faster.
A practical, curated index of ready-to-adapt SQL, Python (pandas), and R (dplyr) patterns for common data cleaning, validation, transformation, time-series/windowing, cohort joins, and feature extraction tasks. Includes contribution guidance, naming conventions, security and performance notes, and short vetted examples to get started.
A curated, practical collection of ready-to-use SQL, Python (pandas) and R (dplyr/data.table) patterns for common data cleaning, transformation, sampling, aggregation, cohorting, and reporting tasks. Each snippet includes a short description, required inputs, expected outputs, and a minimal example to adapt to your schema and dialect.
A practical, opinionated starter library of vetted SQL, Python, and R snippets for common analytics tasks (ETL patterns, dedupe, windowing, metric templates, feature engineering, model evaluation) with usage notes, simple tests, and packaging/versioning guidance so teams can adapt, review, and safely reuse code.