Data Visualization

Daru (Data Analysis in RUby) is a library for analysis, manipulation and visualization of data. Daru works seamlessly accross interpreters and leverages interpreter-specific optimizations whenever they are available. It is the default data storage gem for all the statsample gems (glm, timeseries, etc.) and can be used with many others like mixed_models, gnuplotrb, nyaplot and iruby.

Gem installation of javascript framework for data visualization, D3

Visualizing your data in a simple way.

Glimmer DSL for LibUI (Fukuoka Award Winning Prerequisite-Free Ruby Desktop Development Cross-Platform Native GUI Library) - Winner of Fukuoka Ruby Award Competition 2022 Special Award (http://www.digitalfukuoka.jp/topics/187?locale=ja) - No need to pre-install any prerequisites. Just install the gem and have cross-platform native GUI that just works on Mac, Windows, and Linux! Glimmer DSL for LibUI aims to provide declarative DSL syntax that visually maps to GUI control hierarchy, convention over configuration via smart defaults, automation of low-level details, requiring the least amount of syntax possible to build GUI, bidirectional data-binding, custom control/window support, and application/gem/window/control scaffolding. If you liked Shoes, You'll love Glimmer!

Seer is a lightweight, semantically rich wrapper for the Google Visualization API. It allows you to easily create a visualization of data in a variety of formats, including area charts, bar charts, column charts, gauges, line charts, and pie charts.

Daru (Data Analysis in RUby) is a library for analysis, manipulation and visualization of data. Daru-view is for easy and interactive plotting in web application & IRuby notebook. It can work in frameworks e.g. Rails, Sinatra, Nanoc and hopefully in others too.

Ferry is a data migration and visualization command line tool rubygem that seeks to simplify the increasingly prevalent big data problems for developers

Use this SDK to access the Looker API. The Looker API provides functions to perform administrative tasks such as provisioning users, configuring database connections, and so on. It also enables you to leverage the Looker data analytics engine to fetch data or render visualizations defined in your Looker data models. For more information, see https://looker.com.

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

Contact Center AI Insights helps users detect and visualize patterns in their contact center data. Understanding conversational data drives business value, improves operational efficiency, and provides a voice for customer feedback. Note that google-cloud-contact_center_insights-v1 is a version-specific client library. For most uses, we recommend installing the main client library google-cloud-contact_center_insights instead. See the readme for more details.

Epsagon provides tracing to Ruby applications for the collection of distributed tracing and performance metrics to simplify complex architectures, eliminate manual work, visualize and correlate data to identify and fix problems fast.

Google Chart Tools provide a perfect way to visualize data on your website: now on Ruby

Kaitai Struct is a declarative language used for describe various binary data structures, laid out in files or in memory: i.e. binary file formats, network stream packet formats, etc. The main idea is that a particular format is described in Kaitai Struct language (.ksy file) and then can be compiled with ksc into source files in one of the supported programming languages. These modules will include a generated code for a parser that can read described data structure from a file / stream and give access to it in a nice, easy-to-comprehend API. This package is a visualizer tool for .ksy files. Given a particular binary file and .ksy file(s) that describe its format, it can visualize internal data structures in a tree form and a multi-level highlight hex viewer.

Seer is a lightweight, semantically rich wrapper for the Google Visualization API. It allows you to easily create a visualization of data in a variety of formats, including area charts, bar charts, column charts, gauges, line charts, and pie charts.

Collect and visualize Product related data from Bugzilla and Github

Multidimensional scaling (MDS) is a set of related statistical techniques often used in information visualization for exploring similarities or dissimilarities in data.

Seer is a lightweight, semantically rich wrapper for the Google Visualization API. It allows you to easily create a visualization of data in a variety of formats, including area charts, bar charts, column charts, gauges, line charts, and pie charts.

Allows design of digital signals using the FFT, design of Digital Filters using the Windowing Method, creation of Digital Signals or Analog Signals sampled at a certain interval, convolution, cross-correlation, and visualization of the data. .

Ruby wrapper for MathGL - library for scientific data visualization

Parse and visualize data from AppStore and GooglePlay Store to display it in Octopress or Jekyll posts

Contact Center AI Insights helps users detect and visualize patterns in their contact center data. Understanding conversational data drives business value, improves operational efficiency, and provides a voice for customer feedback.

Jarmo Isotalo's application project for software factory

Visualization of data and associations represented by Active Record.

for visualization of music playlist data

Collection of visual helpers

This tool helps visualize which directories are occupying the most storage. Any directory that occupies more than 5% of used disk space is added to a visual hierarchichal storage report in the form of a Google Sankey diagram. The storage data is gathered using the linux `du` utility. It has been tested on Mac OSX and linux systems (Ubuntu & CentOS), will not work on Windows. Run as sudo if analyzing otherwise inaccessible directories. May take a while to run.

Data visualization toolkit for Rails App using D3.js

A Ruby data-visualization library

An enterprise-grade Database is provided as a Service (DBaaS) solution that can be managed through a browser-based "Data Center Designer" (DCD) tool or via an easy to use API. The API allows you to create additional PostgreSQL database clusters or modify existing ones. It is designed to allow users to leverage the same power and flexibility found within the DCD visual tool. Both tools are consistent with their concepts and lend well to making the experience smooth and intuitive.

Seer is a lightweight, semantically rich wrapper for the Google Visualization API. It allows you to easily create a visualization of data in a variety of formats, including area charts, bar charts, column charts, gauges, line charts, and pie charts.

This gem allows you to read and/or create a valid picture by working with an array of pixel data. This can be used to easily visualize the MSNT dataset, ecrypt/decrypt images, create graphs and charts, etc.

Gem that creates a google visualization data source from hashes passed to it.

Flex Data Visualization Libraries

Data scraping, cleansing, and visualization gem

Rails gem that creates a google visualization data source from ActiveRecord models passed to it.

Ruby library to serialize, format, and visualize Iraq data shared by Agence France-Presse.

This Ruby extension implements a DataMatrix encoder for Ruby. It is typically used to create semacodes, which are barcodes, that contain URLs. This encoder does not create image files or visual representations of the semacode. This is because it can be used for more than creating images, such as rendering semacodes to HTML, SVG, PDF or even stored in a database or file for later use.

Visually displays data structures to make solving coding challenges easier.

The Gem for Experimental Computer Science (GECS) is for managing the data resulting from experiments on software and IT systems. It realizes a data model that disambiguates the vocabulary of experimentation and measurement for a computer science audience. It also provides convenience functions to determine confidence intervals, analyze main effects and interactions, and export data in an R-compatible format for further analysis and visualization.

Charting toolset that integrates into ActiveRecord and ActionView for fast, easy business intelligence and data visualization on any Rails app. Uses inline SVG wherever possible for best performance on the web. Javascript is used only when absolutely necessary.

I introduced Ruby and Apache Arrow integration including the "super fast large data interchange and processing" Apache Arrow feature at RubyKaigi Takeout 2021. This talk introduces how we can use the "super fast large data interchange and processing" Apache Arrow feature in Ruby. Here are some use cases: * Fast data retrieval (fast (({pluck}))) from DB such as MySQL and PostgreSQL for batch processes in a Ruby on Rails application * Fast data interchange with JavaScript for dynamic visualization in a Ruby on Rails application * Fast OLAP with in-process DB such as DuckDB and Apache Arrow DataFusion in a Ruby on Rails application or irb session

east_asian_width_simple is a Ruby gem that calculates the visual width of strings by parsing and looking up East Asian Width Property Data File, aka EastAsianWidth.txt, which is defined in Unicode Standard Annex #11: East Asian Width. It aims to be time-performant and easy to use.

Visualize data distribution in your storage volumes.

This is a simple machine learning library written in Ruby. It provides implementations of linear regression and multiclass perceptron and visualization and validation methods to verify results. Also included are helper methods to work with training and testing data.

A lightweight and straightforward Ruby wrapper for Plotly.js, enabling developers to create interactive, high-quality data visualizations effortlessly.

Easily visualize data from your ruby code

Library for data visualization in the terminal.

A toolkit for making custom visualizations for exploratory data analysis (currently a work in progress)

This is an interface to quickly visualize data on the command line. It supports various kinds of plots (curves, bar diagram, histogram, 2D color, etc) that are presented as text output on the console.

Daru (Data Analysis in RUby) is a library for analysis, manipulation and visualization of data. Daru works seamlessly accross interpreters and leverages interpreter-specific optimizations whenever they are available. It is the default data storage gem for all the statsample gems (glm, timeseries, etc.) and can be used with many others like mixed_models, gnuplotrb and iruby. Daru Lite is a fork of Daru that aims to focus on data manipulation and stability.