CSV Data Normalizer
Mixed date formats, inconsistent phone number styles, 'Yes/yes/YES/1/true' in the same column — our normalizer applies consistent formatting rules across your data so every value speaks the same language.
CSV Data Normalizer
Normalize data values including date formats, phone numbers, currencies, casing, country codes, and boolean representations
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Normalization types:
- Dates: Standardize various date formats to a consistent format
- Phones: Format phone numbers with consistent separators and country codes
- Currencies: Format monetary values with symbols, decimals, and separators
- Casing: Normalize text to uppercase, lowercase, title case, or sentence case
- Countries: Convert country names/codes to standard formats (alpha-2, alpha-3, numeric, full)
- Booleans: Standardize boolean representations (true/false, yes/no, 1/0, Y/N)
What This Tool Does
This tool normalizes data values in your CSV file to consistent formats. Select columns and choose normalization rules for dates, phone numbers, currencies, text casing, country codes, and boolean values. Transform messy, inconsistent data into clean, standardized formats.
Normalization Types
Dates: Convert various date formats to a standard format (YYYY-MM-DD, MM/DD/YYYY, DD-MM-YYYY, etc.).
Phone numbers: Format to international (+1-555-123-4567), national ((555) 123-4567), or digits-only (15551234567).
Currencies: Standardize currency symbols, decimal places, and thousand separators.
Casing: Convert text to uppercase, lowercase, title case, or sentence case.
Country codes: Convert between alpha-2 (US), alpha-3 (USA), numeric (840), or full names (United States).
Booleans: Normalize true/false, yes/no, 1/0, Y/N to a consistent format.
Example: Date Normalization
Input (mixed formats):
name,birth_date Alice,01/15/1990 Bob,1985-03-22 Charlie,22.07.1988 Diana,July 4, 1992
Normalize to YYYY-MM-DD:
name,birth_date Alice,1990-01-15 Bob,1985-03-22 Charlie,1988-07-22 Diana,1992-07-04
Example: Phone Normalization
Input (mixed formats):
name,phone Alice,5551234567 Bob,(555) 123-4567 Charlie,555.123.4567 Diana,+1 555 123 4567
Normalize to international format:
name,phone Alice,+1-555-123-4567 Bob,+1-555-123-4567 Charlie,+1-555-123-4567 Diana,+1-555-123-4567
Example: Casing Normalization
Input (inconsistent casing):
name,city alice smith,NEW YORK BOB JONES,los angeles Charlie Brown,CHICAGO
Normalize names to Title Case, cities to uppercase:
name,city Alice Smith,NEW YORK Bob Jones,LOS ANGELES Charlie Brown,CHICAGO
When to Use This
Data consolidation: Merge data from multiple sources with different formatting conventions.
Database preparation: Standardize data before import to ensure consistent storage.
API integration: Format data to match API expectations for dates, phones, etc.
Report generation: Create consistently formatted reports for stakeholders.
Data quality improvement: Fix inconsistencies that cause grouping, sorting, and matching issues.
Date Format Options
YYYY-MM-DD: ISO 8601 standard. Best for sorting and international use.
MM/DD/YYYY: US format.
DD-MM-YYYY: European format.
DD/MM/YYYY: UK/international format.
YYYY/MM/DD: Alternative ISO format, common in Asia.
Phone Format Options
International: +1-555-123-4567. Best for global datasets.
National: (555) 123-4567. Best for single-country datasets.
Digits only: 15551234567. Best for storage and comparison.
Dashed: 555-123-4567. Common US format.
Dotted: 555.123.4567. Alternative format.
Limitations
Date parsing: Ambiguous dates (01/02/2024 could be Jan 2 or Feb 1) may parse incorrectly.
Phone validation: This tool formats phones but doesn't validate if they're real numbers.
Large files: Works best with files under 50MB. Very large files may cause slow performance.
Complex patterns: Custom data patterns require scripting for normalization.
Frequently Asked Questions
What if my dates are ambiguous?
Dates like 01/02/2024 are ambiguous (US: Jan 2, EU: Feb 1). The tool tries to infer from context, but manual review may be needed.
Can I normalize multiple columns at once?
Yes. Select multiple columns and apply the same or different normalization rules to each.
Does this validate data?
This tool formats data but doesn't validate correctness. Invalid dates or phone numbers may produce unexpected output.
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