Clean messy CSV files with pandas — handle missing data, duplicates, dates
KDnuggets walks through a practical pandas workflow for CSV data cleanup: missing values, duplicate rows, text noise, type mismatches, date inconsistencies, invalid emails, and currency formatting.
• Detect and fill or drop missing values
• Remove duplicate rows
• Standardize text (whitespace, case)
• Convert columns to correct data types
• Parse and unify date formats
• Validate email addresses
• Parse and normalize currency