awesome-repositories.com

AI-संचालित खोज के साथ बेहतरीन ओपन-सोर्स रिपॉजिटरी खोजें।

एक्सप्लोर करेंक्यूरेटेड खोजेंOpen-source alternativesSelf-hosted softwareब्लॉगसाइटमैप
प्रोजेक्टहमारे बारे मेंHow we rankप्रेसMCP सर्वर
कानूनीगोपनीयताशर्तें
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
awesome-repositories.comब्लॉग
श्रेणियाँ

4 रिपॉजिटरी

Awesome GitHub RepositoriesData Normalization

Standardizes raw input formats into a consistent internal representation.

Distinct from Input Validation: Distinct from Input Validation: focuses on the process of cleaning and standardizing data rather than simply verifying correctness.

Explore 4 awesome GitHub repositories matching part of an awesome list · Data Normalization. Refine with filters or upvote what's useful.

Awesome Data Normalization GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • modood/administrative-divisions-of-chinamodood का अवतार

    modood/Administrative-divisions-of-China

    20,829GitHub पर देखें↗

    This project provides a structured dataset of the administrative divisions of China, covering five levels from provinces down to villages. It delivers this geographical information in a standardized JSON format designed for data exchange and integration. The dataset is organized as a hierarchical source specifically for building cascading address selectors and region pickers. It uses linked data to enable sequential filtering from higher-level provinces down to village-level boundaries. The project covers geographic data management and regional data normalization. It provides the necessary m

    Standardizes regional inputs using a consistent hierarchy of provinces, cities, districts, towns, and villages.

    JavaScriptaddressadministrative-divisionsarea
    GitHub पर देखें↗20,829
  • open-circle/valibotopen-circle का अवतार

    open-circle/valibot

    8,769GitHub पर देखें↗

    Valibot is a modular, type-safe schema library for validating and parsing structural data in TypeScript environments.

    Transforms raw input into a standardized format during the validation process.

    TypeScriptbundle-sizemodularparsing
    GitHub पर देखें↗8,769
  • openvenues/libpostalopenvenues का अवतार

    openvenues/libpostal

    4,819GitHub पर देखें↗

    Libpostal is a C library designed for international address parsing and normalization. It utilizes statistical NLP and a language classifier to decompose unstructured global address strings into structured components and standardize street addresses by expanding abbreviations and resolving regional naming variations across multiple languages. The project provides tools for text transliteration, converting various scripts into standardized Latin-ASCII or NFD forms. It also includes capabilities for address deduplication, using symmetric fuzzy matching to identify whether different address reco

    Provides multi-language expansion of shorthand address terms into their full-form equivalents.

    C
    GitHub पर देखें↗4,819
  • dathere/qsvdathere का अवतार

    dathere/qsv

    3,687GitHub पर देखें↗

    qsv is a high-performance command line toolkit for querying, transforming, and analyzing comma-separated value files. It functions as a data wrangling interface and a tabular data profiler, featuring a query engine capable of executing SQL statements and joins directly on flat files without requiring a database. The project is distinguished by its ability to process massive datasets that exceed available system memory. This is achieved through disk-based external memory processing, including multithreaded merge sorting, on-disk hash tables for deduplication, and lightweight file indexing for

    Reads data with specific quoting or transcoding rules to standardize input for processing.

    Rustaickancsv
    GitHub पर देखें↗3,687
  1. Home
  2. Part of an Awesome List
  3. Developer Tools
  4. Input Validation
  5. Data Normalization

सब-टैग एक्सप्लोर करें

  • Address Normalizations1 सब-टैगStandardizing varying address inputs into a consistent administrative hierarchy. **Distinct from Data Normalization:** Focuses on geographic hierarchy normalization rather than general raw data cleaning or email formats.