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Phase 8 · Data Cleaning & Wrangling

Topics

Standardizing & Normalizing Data

Part of the Data Analyst Roadmap.

Summary

Making values comparable — consistent units, consistent categorical labels ('NY' vs 'New York' vs 'ny'), and, for some statistical methods, rescaling numeric ranges.

How to Learn This

  • 1Standardize a messy categorical column (inconsistent casing/spelling) into clean values.
  • 2Learn the difference between normalization (0-1 scale) and standardization (z-scores).
  • 3Practice building a mapping table for messy categorical values to canonical ones.

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Outlier Handling

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Data Validation Rules

More topics in Data Cleaning & Wrangling

Identifying Data Quality IssuesHandling Missing DataHandling DuplicatesData Type ConversionOutlier HandlingData Validation RulesETL Basics (Extract, Transform, Load)Documenting Data Cleaning Decisions
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