A simple CSV to JSON convertor
A JSON to CSV and CSV to JSON converter that natively supports sub-documents and auto-generates the CSV heading.
Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware encoding of JSON for LLM prompts
Streaming CSV parser that aims for maximum speed as well as compatibility with the csv-spectrum test suite
Convenient parsing for Fetch.
Fast and powerful CSV parser for the browser that supports web workers and streaming large files. Converts CSV to JSON and JSON to CSV.
CSV parser and writer
A tool concentrating on converting csv data to JSON with customised parser supporting
fast-csv formatting module
CSV parsing implementing the Node.js `stream.Transform` API
fast-csv parsing package
Object transformations implementing the Node.js `stream.Transform` API
CSV stringifier implementing the Node.js `stream.Transform` API
Convert CSV to JSON
stream-csv-as-json is a micro-library of stream components for building custom CSV processing pipelines with a minimal memory footprint, on Node.js or Web Streams. It can parse CSV files far exceeding available memory streaming individual primitives using
List of world countries in JSON, CSV, XML and YAML
Easily generate csv downloads of your json data.
A mature CSV toolset with simple api, full of options and tested against large datasets.
Pure Javascript JSON to CSV converter.
csv test data for writing robust csv parsers
convert csv to json and json to csv
CSV and object generation implementing the Node.js `stream.Readable` API
Table format APIs for JSON, CSV, etc...
TypeScript version of the gluestick ETL library for hotglue IPaaS platform
apiify is a little gem that takes any .csv file and turns it into an API. It's aimed at large organisations, e.g. government departments, that publish a lot of data as .csv and who want a quick way to access this data as JSON in their digital services.
# MakeData A CLI for generating fake json, csv, or yaml data. Uses Faker to produce fake data in whatever category you choose. ## Quick Start Requires `peco`, so `brew install peco` (or however you get packages) ``` mkdata ``` Follow the prompts to select the category, keys, count, and format. ## Options `-h --help` Shows the help menu `-c --category [CATEGORY]` choose a category from Faker. (I can never remember these, so I use the interactive mode. Mostly here so that this could be used without interaction, like in a script) `-f --format [FORMAT]` json, csv, or yaml. What format to generate the data in. `-a --all` use all the keys from that Faker category.
Ruby Scientist and Graphics is a practical data science toolkit for Ruby. It includes a lightweight built-in DataFrame for loading, cleaning, and transforming data; quick descriptive statistics and correlations; charting via Gruff (bar and line); and simple ML utilities (linear regression and k-means)—all behind a small, unified, pandas-inspired API. Key features: - Load data from CSV and JSON. - Clean and transform (remove/add columns, handle missing values, limit rows). - Describe datasets and compute correlations quickly. - Create bar and line charts with customization options. - Train/predict with linear regression; cluster with k-means. - Save/load project state (data + trained model) and run simple pipelines. - Optional backend adapters (e.g., Rover) while keeping the same API. Ideal for analysts and developers who want to explore data in Ruby without relying on Python or R. Note: plotting via Gruff uses rmagick, which requires ImageMagick installed on the system.
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