date-normalizer

Normalize date strings from various formats into ISO 8601 or custom formats.

86|18|Updated Dec 14, 2025

Search Tags:#etl #data cleaning #date parsing #data standardization #iso 8601 #csv processing

Ready to run

npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill date-normalizer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: date-normalizer
Source: https://github.com/dkyazzentwatwa/chatgpt-skills/tree/main/date-normalizer
Command: npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill date-normalizer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python-dateutil, pandas, and includes scripts (resource) components.

What problem does it solve?

This Skill solves the problem of inconsistent and varied date formats, ensuring all dates are standardized for reliable data processing and analysis.

Core Features & Use Cases

Smart Parsing: Handles over 100 date formats automatically.
Format Conversion: Converts dates to ISO 8601, US, EU, or custom formats.
Batch Processing: Normalizes entire columns in CSV files.
Use Case: You have a CSV file with a 'created_at' column containing dates like '03/14/2024', 'March 14, 2024', and '2024-03-15'. Use this Skill to convert all these entries into a consistent 'YYYY-MM-DD' format.

Quick Start

Use the date-normalizer skill to convert the date 'March 14, 2024' to the ISO 8601 format.

Frequently Asked Questions about date-normalizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I standardize inconsistent date strings in a CSV file for data analysis?▼

ISO 8601 date standardization converts varied inputs like '03/14/2024' and 'March 14, 2024' into a uniform YYYY-MM-DD format. It ensures reliable data processing by resolving format ambiguities across diverse datasets.

What is the best way to parse and normalize mixed date formats into ISO 8601?▼

The best way to parse mixed date formats into ISO 8601 is using smart parsing engines that handle over 100 variations automatically. This detects patterns and converts dates consistently without manual format mapping.

Can pandas handle timezone conversion and date ambiguity detection during date parsing?▼

Yes, using pandas with python-dateutil handles timezone conversion and ambiguity detection during date parsing. You can batch process CSV columns, converting mixed date formats directly into standardized ISO 8601 outputs.

How do I convert an entire CSV column of varied dates into a consistent format?▼

You convert a CSV column of varied dates into a consistent format by applying batch processing operations. This automatically parses multiple date string formats and normalizes them uniformly across the selected column.

Does relative date parsing work when standardizing dates from diverse CSV data sources?▼

Relative date parsing works when standardizing dates from CSV data sources by converting terms like 'yesterday' into absolute ISO 8601 formats. It manages ambiguity detection and timezone handling during batch processing.

Why does date standardization fail on ambiguous date formats in data cleaning workflows?▼

Date standardization often fails on ambiguous formats like '03/04/2024' because the system cannot determine if the month or day comes first. Ambiguity detection mechanisms are required to resolve these parsing conflicts.