5 Useful Python Scripts for Automated Data Quality Checks
Image by Author # Introduction Data quality problems are everywhere. Missing values where there shouldn’t be any. Dates in the wrong format. Duplicate records that slip through. Outliers that skew your analysis. Text fields with inconsistent capitalization and spelling variations. These issues can break your analysis, pipelines, and often lead to incorrect business decisions. Manual …
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