Cleaning messy CSVs without pandas: 3 tiny no-install scripts

📰 Dev.to · wave zhou

Learn to clean messy CSVs without pandas using 3 tiny no-install scripts, improving data quality and efficiency

intermediate Published 11 Jun 2026
Action Steps
  1. Run a script to remove stray whitespace from CSV cells using Python's built-in csv module
  2. Use a script to eliminate duplicate rows by leveraging Python's set data structure
  3. Apply a script to standardize inconsistent data formats, such as date or timestamp fields, using regular expressions
Who Needs to Know This

Data scientists, analysts, and engineers can benefit from these scripts to preprocess CSV data, making it easier to work with and analyze

Key Insight

💡 Small, specialized scripts can be more efficient and effective than relying on large libraries like pandas for simple data cleaning tasks

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📊 Clean messy CSVs without pandas! 🚀 3 tiny no-install scripts to improve data quality 📈

Key Takeaways

Learn to clean messy CSVs without pandas using 3 tiny no-install scripts, improving data quality and efficiency

Full Article

Messy CSV exports are a tax on every data task: stray whitespace, duplicate rows, inconsistent...
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