Plotly Dash

Plotly Dash

Plotly
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

Dash & Dash Enterprise let you build & deploy analytic web apps using Python, R, and Julia. No JavaScript or DevOps required. Through Dash, the world's largest companies elevate AI, ML, and Python analytics to business users at 5% the cost of a full-stack development approach. Deliver apps and dashboards that run advanced analytics: ML, NLP, forecasting, computer vision and more. Work in the languages you love: Python, R, and Julia. Reduce costs by migrating legacy, per-seat licensed software to Dash Enterprise's open-core, unlimited end-user pricing model. Move faster by deploying and updating Dash apps without an IT or DevOps team. Create pixel-perfect dashboards & web apps, without writing any CSS. Scale effortlessly with Kubernetes. Support mission-critical Python applications with high availability.

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

Data science teams

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

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
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 4.5 / 5
ease 5.0 / 5
features 4.5 / 5
design 5.0 / 5
support 4.5 / 5

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

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

This software hasn't been reviewed yet. Be the first to provide a review:

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

Plotly
Founded: 2013
Canada
plotly.com

Company Information

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

Company Information

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

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Keepsake

Replicate

Categories

Categories

Categories

Categories

Data Visualization Features

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Integrations

Comet LLM
DagsHub
Dash
F#
Flower
Intel Tiber AI Studio
JSON
Keepsake
MATLAB
Make
Matplotlib
Mocha
NVIDIA RAPIDS
NumPy
PaizaCloud
QUnit
R
Train in Data
Voxel51
scikit-learn

Integrations

Comet LLM
DagsHub
Dash
F#
Flower
Intel Tiber AI Studio
JSON
Keepsake
MATLAB
Make
Matplotlib
Mocha
NVIDIA RAPIDS
NumPy
PaizaCloud
QUnit
R
Train in Data
Voxel51
scikit-learn

Integrations

Comet LLM
DagsHub
Dash
F#
Flower
Intel Tiber AI Studio
JSON
Keepsake
MATLAB
Make
Matplotlib
Mocha
NVIDIA RAPIDS
NumPy
PaizaCloud
QUnit
R
Train in Data
Voxel51
scikit-learn

Integrations

Comet LLM
DagsHub
Dash
F#
Flower
Intel Tiber AI Studio
JSON
Keepsake
MATLAB
Make
Matplotlib
Mocha
NVIDIA RAPIDS
NumPy
PaizaCloud
QUnit
R
Train in Data
Voxel51
scikit-learn
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