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SKU/Artículo: AMZ-B0FPCD3MR6

Pandas and SQL for Data Science: Build Efficient Workflows with Python and Databases

Detalles del producto

Disponibilidad:
En stock

Peso con empaque:
0.63 kg

Devolución:
Sí

Condición
Nuevo

Producto de:
Amazon

Viaja desde
USA

Sobre este producto

Set up a reliable Python and SQL environment for data analysis.
Connect Pandas to relational databases using SQLAlchemy and read_sql().
Write efficient SQL queries with SELECT, WHERE, JOIN, and GROUP BY to filter, aggregate, and combine data.
Decide which tasks belong in SQL and which should be handled in Pandas.
Apply best practices like method chaining and vectorization for clean, efficient Pandas code.
Ingest data from multiple sources—databases, CSVs, Excel, JSON, and Parquet—and unify it in Pandas.
Merge SQL data with flat files or APIs to build complete, real-world datasets.
Work through practical case studies, such as analyzing customer transactions and identifying top spenders.

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U$S 46,22

49% OFF

U$S 23,70

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