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Data Engineering

10 articles tagged #Data Engineering

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Fixing Pandas merge Duplicate Rows When Join Keys Are Not Unique

Your pandas.merge() operation suddenly doubles or triples the number of rows, even though the merge completes successfully. The cause is usually non-unique join keys that produce many-to-many relationships. Learn why duplicate rows appear after merges and how to validate, diagnose, and fix them

Jul 23, 2026 4m read πŸ‘ 15

Diagnosing Silent Data Loss in Pandas groupby Aggregations

Pandas groupby() is one of the most powerful tools for data aggregation, but subtle issues such as missing values, duplicate keys, incorrect aggregation functions, or dropped categories can silently produce incomplete results. Learn how to identify and prevent silent data loss in your groupby

Jul 19, 2026 4m read πŸ‘ 20

Pandas read_sql Returning Stale or Mismatched Data: Connection and Query Pitfalls

If pandas.read_sql() is returning outdated, incomplete, or unexpected results, the problem often isn't Pandas itself. Database transactions, connection pooling, replicas, query caching, and isolation levels can all affect what your application reads. Learn how to identify and resolve the most common

Jul 16, 2026 4m read πŸ‘ 14
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