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SELECT column::DOUBLE, TRY_CAST(date_str AS DATE) FROM raw;
-- Drop nulls SELECT * FROM raw WHERE column IS NOT NULL; -- Fill nulls SELECT COALESCE(column, 0) FROM raw;
If you’re looking for a on using DuckDB for data preparation (cleaning, reshaping, transforming), here’s a concise practical guide: DuckDB Data Prep Guide 1. Installation pip install duckdb Or use the standalone CLI / embedded in Python, R, Node.js. 2. Load Data -- From CSV CREATE TABLE raw AS SELECT * FROM 'data.csv'; -- From Parquet/JSON CREATE TABLE raw AS SELECT * FROM 'data.parquet'; 3. Inspect Data DESCRIBE raw; SELECT * FROM raw LIMIT 10; SELECT COUNT(*), COUNT(DISTINCT column) FROM raw; 4. Common Prep Operations Handle missing values
-- Remove duplicates SELECT DISTINCT * FROM raw; -- String cleaning SELECT UPPER(name), TRIM(address) FROM raw;
It looks like you’re referencing — possibly a typo or a shorthand for a resource related to DuckDB and data preparation (e.g., “qwack” → “quack” as in duck sound, “prep” as in preparation).
