Web Reference: May 30, 2024 · In this post, we will review the concepts you need to know to use Python effectively for data engineering. Each concept has an associated workbook for practicing these concepts. Core Python libraries for data engineering include Pandas for data manipulation, NumPy for numerical work, PySpark and Dask for large-scale processing, and SQLAlchemy for database access. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.
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