blanket.js

blanket.js

Blanket.js

About

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy).

About

WebDataRocks is a simple free JS library for creating functional and easy-to-use pivot tables. It can be used with Angular, Vue, React or any other framework. Free Flexible in customization JavaScript based client-side component Loads 1MB of JSON or CSV data files Full set of enterprise features Integration with 3rd party charting libraries Full set of enterprise features Features like filtering, sorting, grouping, conditional and number formatting, calculated values, totals are available for efficient work with your data. It supports printing or exporting web report to PDF, Excel or HTML with just one click. Ready-to-use modern UI The tool offers a classy spreadsheet-like interface optimized both for browsers and apps. All principles of reliability and excellent user experience are already implemented in this web reporting tool.

About

A seamless JavaScript code coverage library. Blanket.js is a code coverage tool for JavaScript that aims to be easy to install, easy to use, and easy to understand. Blanket.js can be run seamlessly or can be customized for your needs. JavaScript code coverage compliments your existing JavaScript tests by adding code coverage statistics (which lines of your source code are covered by your tests). Parsing the code using Esprima and node-falafel, and instrumenting the file by adding code tracking lines. Connecting to hooks in the test runner to output the coverage details after the tests have been completed. A Grunt plugin has been created to allow you to use Blanket like a "traditional" code coverage tool (creating instrumented copies of physical files, as opposed to live-instrumenting). Runs the QUnit-based Blanket report headlessly using PhantomJS. Results are displayed on the console, and the task will cause Grunt to fail if any of your configured coverage thresholds are not met.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers looking for a Python library for creating static, animated, & interactive visualizations

Audience

Web developers, data analytics

Audience

Developers seeking a solution to manage their code tracking processes and statistics

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

No images available

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Matplotlib
matplotlib.org

Company Information

WebDataRocks
Founded: 2019
United States
www.webdatarocks.com

Company Information

Blanket.js
github.com/alex-seville/blanket

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Alternatives

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MLlib

MLlib

Apache Software Foundation
Kendo UI

Kendo UI

Progress Software
Testwell CTC++

Testwell CTC++

Testwell
Aider

Aider

Aider AI
Ignite UI

Ignite UI

Infragistics
Keepsake

Keepsake

Replicate

Categories

Categories

Categories

Categories

Integrations

Axis LMS
Comet LLM
Dash
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
JavaScript
Kedro
Keepsake
MLJAR Studio
Matplotlib
Mocha
ModelOp
NumPy
PaizaCloud
QUnit
Train in Data
Yandex Data Proc
scikit-learn

Integrations

Axis LMS
Comet LLM
Dash
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
JavaScript
Kedro
Keepsake
MLJAR Studio
Matplotlib
Mocha
ModelOp
NumPy
PaizaCloud
QUnit
Train in Data
Yandex Data Proc
scikit-learn

Integrations

Axis LMS
Comet LLM
Dash
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
JavaScript
Kedro
Keepsake
MLJAR Studio
Matplotlib
Mocha
ModelOp
NumPy
PaizaCloud
QUnit
Train in Data
Yandex Data Proc
scikit-learn

Integrations

Axis LMS
Comet LLM
Dash
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
JavaScript
Kedro
Keepsake
MLJAR Studio
Matplotlib
Mocha
ModelOp
NumPy
PaizaCloud
QUnit
Train in Data
Yandex Data Proc
scikit-learn
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