Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science. Build an app in a few lines of code with magically simple API. Adding a widget is the same as declaring a variable. No need to write a backend, define routes etc. Effortlessly share, manage, and collaborate on your apps directly from Streamlit. Apps are deployed directly from Github repo.

Streamlit - The fastest way to build data apps in Python

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. It supports over 40 programming languages. 
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Code can produce rich output such as images, videos, LaTeX, and JavaScript. Interactive widgets can be used to manipulate and visualize data in realtime.

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. It supports over 40 programming languages. 

Jupyter - Web-based notebook environment for interactive computing

Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. It easily integrates your data, using either our simple no-code viz builder or state of the art SQL IDE. Superset can query data from any SQL-speaking datastore or data engine (e.g. Presto or Athena) that has a Python DB-API driver and a SQLAlchemy dialect.
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Superset provides:<BR>
<ul>
<li>An intuitive interface for visualizing datasets and
crafting interactive dashboards</li>
<li>A wide array of beautiful visualizations to showcase your data</li>
<li>Code-free visualization builder to extract and present datasets</li>
<li>A world-class SQL IDE for preparing data for visualization, including a rich metadata browser</li>
<li>A lightweight semantic layer which empowers data analysts to quickly define custom dimensions and metrics</li>
<li>Out-of-the-box support for most SQL-speaking databases</li>
<li>Seamless, in-memory asynchronous caching and queries</li>
<li>An extensible security model that allows configuration of very intricate rules on
on who can access which product features and datasets.</li>
<li>Integration with major
authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, etc)</li>
<li>The ability to add custom visualization plugins</li>
<li>An API for programmatic customization</li>
<li>A cloud-native architecture designed from the ground up for scale</li>
</ul>

Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. It easily integrates your data, using either our simple no-code viz builder or state of the art SQL IDE. Superset can query data from any SQL-speaking datastore or data engine (e.g. Presto or Athena) that has a Python DB-API driver and a SQLAlchemy dialect.

Apache Superset is a Data Visualization and Data Exploration Platform 

Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. It supports . interactive data analysis workflows with a large toolbox. 

Orange - Data Mining Suite

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Streamlit - The fastest way to build data apps in Python

Jupyter - Web-based notebook environment for interactive computing

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Orange - Data Mining Suite

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Streamlit - The fastest way to build data apps in Python

Jupyter - Web-based notebook environment for interactive computing

Apache Superset is a Data Visualization and Data Exploration Platform

Orange - Data Mining Suite

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