Clean up your CSVs.
Understand your Python errors.

Focused help for repetitive data tasks and reproducible script problems.

Explore the examples, then discuss a clearly defined scope.

Spreadsheet & CSV cleanup

  • Combine exports using explicit field and date rules
  • Review duplicates, missing values, and conflicting records
  • Keep exceptions separate and reconcile every input row
  • Define the output format and checks before work starts

18 automated checks

Synthetic CSV example

Explore the example

Python troubleshooting

  • Reproduce one clearly described script problem
  • Explain the cause with a minimal, reviewable fix
  • Compare the same tests before and after the change
  • Agree on environment, permissions, and acceptance criteria

6 regression tests

Synthetic UTF-8 BOM example

See the one-line fix

A practical guide

Keep leading zeros and long CSV IDs safe in Python

A complete, runnable synthetic example, with checks for every identifier and a separate Excel import boundary.

Start with a general question

Describe the file type, approximate size, or error message in a public comment on a relevant channel video, where comments are available. Keep it general: never post private files, personal data, customer records, passwords, API keys, or confidential code.

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