5 repositorios
Transformation of comma-separated values files into JSON structures.
Distinct from JSON to CSV Conversion: Performs the inverse operation of JSON-to-CSV conversion.
Explore 5 awesome GitHub repositories matching data & databases · CSV to JSON Conversion. Refine with filters or upvote what's useful.
jc is a tool that transforms plain-text results from command-line utilities, system tools, log formats, and text tables into structured JSON data. It functions as a structured data transformer capable of converting various file formats, including CSV, INI, XML, and YAML, into JSON representations for programmatic use. The project includes a collection of specific parsers for Unix commands and system tools such as df, blkid, and various package managers. It also features specialized converters for web server logs, Common Log Format, and Common Event Format strings. The tool covers broad capab
Transforms comma-separated values files into JSON by detecting delimiters and using the first row as headers.
This project is an administrative GIS toolset that provides a comprehensive dataset of China's administrative divisions, including provinces, cities, districts, and townships. It functions as a coordinate system transformer and a boundary converter for transforming geographic data into standard formats. The toolset distinguishes itself through the ability to convert administrative boundary data between CSV, GeoJSON, Shapefiles, and SQL. It includes specialized utilities for coordinate system transformation between GCJ-02, BD-09, WGS-84, and CGCS2000 standards to ensure accuracy across differe
Transforms tabular CSV data into JSON structures to populate frontend multi-level dropdown menus.
csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly from the terminal. It provides a suite of focused single-purpose commands that can be combined via pipes to build complex data processing workflows, with a modular architecture that includes a column-type inference engine for automatically detecting data types and a streaming-pipeline design for efficient handling of tabular data. The toolkit distinguishes itself through its SQL-engine abstraction layer, which allows users to run SQL queries directly against CSV files without req
Outputs CSV data as JSON, enabling interchange with web and application formats.
Mapshaper es una herramienta para procesar, simplificar y convertir datos vectoriales geográficos, disponible como interfaz de línea de comandos, herramienta de navegador web y librería de Node.js. Funciona como un proyector de coordenadas, convertidor de datos vectoriales y optimizador de activos de mapas web diseñado para transformar conjuntos de datos espaciales entre diferentes sistemas de referencia de coordenadas y formatos de archivo. El proyecto se distingue por su simplificación de geometría que preserva la topología, lo que reduce el número de vértices mientras mantiene los límites compartidos para evitar huecos y superposiciones. Además, optimiza los activos para la web mediante la cuantización de coordenadas y el filtrado de atributos para reducir el tamaño de los archivos. El sistema cubre una amplia gama de capacidades, incluyendo reproyección de coordenadas utilizando cadenas PROJ y códigos EPSG, y conversión de datos entre formatos como Shapefile, GeoJSON, TopoJSON, GeoPackage y KML. Proporciona amplias herramientas de procesamiento de geometría para buffering, recorte, disolución y reparación de topologías, así como utilidades de gestión de datos para unión, filtrado y transformación de atributos. Además, incluye funciones de visualización para generar exportaciones SVG estilizadas, retículas y mapas de símbolos proporcionales. Las capacidades de procesamiento espacial pueden integrarse directamente en aplicaciones JavaScript y tuberías de construcción (build pipelines) a través de su librería de Node.js.
Reads and writes plain JSON arrays of objects as records with support for nested paths.
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
Implements conversion of comma-separated values files into structured JSON formats.