Easily transform your CSV to a custom JSON with cool options
A JSON to CSV and CSV to JSON converter that natively supports sub-documents and auto-generates the CSV heading.
Pure Javascript JSON to CSV converter.
CSV stringifier implementing the Node.js `stream.Transform` API
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.
Node.js Transform and Async interface to convert JSON into CSV.
fast-csv parsing package
A tool concentrating on converting csv data to JSON with customised parser supporting
fast-csv formatting module
CSV parser and writer
CSV parsing implementing the Node.js `stream.Transform` API
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Security & License Compliance For Your App's Dependencies 🪱
Object transformations implementing the Node.js `stream.Transform` API
Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware encoding of JSON for LLM prompts
Convert CSV to JSON
PostgreSQL interface for Node.js
React CSV import widget with user-customizable mapping
Easily generate csv downloads of your json data.
convert csv to json and json to csv
List of world countries in JSON, CSV, XML and YAML
csv test data for writing robust csv parsers
Provides API for building response based on ActiveRecord::Relation objects (json, csv, even using custom view builder). It makes much easier to fetch information from database for displaying it for example using JavaScript MV* based frameworks (such as Knockout, Backbone, Angular, etc), in csv format or even with any custom format. Tags: json, csv, grid, api, grid builder, activerecord relation builder, relation
serialize_with_coder is an ActiveRecord 2.x extended serialize function which acts like Rails 3.1 one - you can use custom coder as storing engine. Including 2 sample coders - CSV and JSON.
Rack middleware that logs API request details (method, path, IP, duration, status, errors) into a CSV or JSON file. Supports daily rotation and format customization.
Twitter word clouds. Analyse the frequency of word occurrences for a user or list of users. Configurable - set the words to ignore, the range of dates to look at, and whether to include hashtags, @-mentions, and URLs. Customize your Twitter configuration, too. Sensible defaults are provided for all options. Look at the data in different ways. Easily convert and/or export to CSV and JSON. Change configuration options on the fly and re-audit with ease.
Geoptima is a suite of applications for measuring and locating mobile/cellular subscriber experience on GPS enabled smartphones. It is produced by AmanziTel AB in Helsingborg, Sweden, and supports many phone manufacturers, with free downloads from the various app stores, markets or marketplaces. This Ruby library is capable of reading the JSON format files produced by these phones and reformating them as CSV, GPX and PNG for further analysis in Excel. This is a simple and independent way of analysing the data, when compared to the full-featured analysis applications and servers available from AmanziTel. If you want to analyse a limited amount of data in excel, or with Ruby, then this GEM might be for you. If you want to analyse large amounts of data, from many subscribers, or over long periods of time then rather consider the NetView and Customer IQ applications from AmanziTel at www.amanzitel.com. Current features available in the library and the show_geoptima command: * Import one or many JSON files * Organize data by device id (IMEI) into datasets * Split by event type * Time ordering and time correlation (associate data from one event to another): ** Add GPS locations to other events (time window and interpolation algorithms) ** Add signal strenth, battery level, etc. to other events * Export event tables to CSV format for further processing in excel * Make and export GPS traces in GPX and PNG format for simple map reports The amount of data possible to process is limited by memory, since all data is imported in ruby data structures for procssing. If you need to process larger amounts of data, you will need a database-driven approach, like that provided by AmanziTel's NetView and Customer IQ solutions. This Ruby gem is actually used by parts of the data pre-processing chain of 'Customer IQ', but it not used by the main database and statistics engine that generates the reports.
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.