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Combining Data From Multiple Sources

src/data/question-groups/data-science/content/combining-data-from-multiple-sources.md

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When I combine data from different sources with inconsistent formats, the first thing I do is standardize everything: dates, column names, booleans, numbers, etc., so they all speak the same language. After doing that, I'll:

  • Align schemas: match columns across datasets. If one has extras, I drop or keep them depending on relevance.
  • Unify categories: I clean up inconsistencies like "Y" vs. "Yes" to avoid downstream issues.
  • Tag the source: I add a source column so I know where each row came from. This is super useful for tracking or debugging later.
  • Merge or stack: If the structure is the same, I concat(). If I'm matching on something like customer ID, I go with a merge or join.
  • Final clean-up: I look for duplicates, mismatched types, or broken values post-merge and fix them.

I avoid merging before checking data types or keys. That’s a fast track to lost or duplicated rows.