4 个仓库
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.
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Awesome Data Normalization GitHub Repositories
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- modood/administrative-divisions-of-china
modood/Administrative-divisions-of-China
20,829在 GitHub 上查看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 - open-circle/valibot
open-circle/valibot
8,769在 GitHub 上查看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 - openvenues/libpostal
openvenues/libpostal
4,819在 GitHub 上查看Libpostal 是一个专为国际地址解析和标准化设计的 C 库。它利用统计自然语言处理（NLP）和语言分类器，将非结构化的全球地址字符串分解为结构化组件，并通过扩展缩写和解决跨语言的区域命名差异来标准化街道地址。 该项目提供文本转写工具，将各种脚本转换为标准化的拉丁-ASCII 或 NFD 形式。它还包括地址去重功能，使用对称模糊匹配来识别不同的地址记录是否指向同一个物理位置。 该库涵盖了更广泛的文本处理需求，例如 UTF-8 标准化，以及将书写数字和罗马数字转换为标准数字表示。它允许通过外部配置文件扩展地址识别功能，以添加新的语言和同义词。
Provides multi-language expansion of shorthand address terms into their full-form equivalents.
C - dathere/qsv
dathere/qsv
3,687在 GitHub 上查看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
