DNotebook Tutorial: The Javascript Version of Python's Jupyter Notebook

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DNOTEBOOK

Dnotebook allows you to create and share pages that contain live code, text and visualizations in a textbook-like manner.

We are redesigning Dnotebook to feel more native. Track progress in this epic issue, project board.

Features:

• Easily perform interactive data exploration and analysis using efficient JavaScript packages like Danfo.js.
• Easily build, train and prototype machine learning models using different tools like Tensorflow.js
• Learn JavaScript in an interactive/visual style. This can hasten learning and understanding.
• Plain Experimentation/Prototyping. Any experimentation performed in JavaScript can run on Dnotebooks.

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REFERENCE: https://dnotebook.jsdata.org/getting-started

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TRY RUNNING DNOTEBOOK ON STACKBLITZ

0) You should have a StackBlitz account first.

1) Create a node.js project

2) Enter the following package.json data:

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package.json: { "name": "node-starter", "version": "0.0.0", "scripts": { "test": "echo \"Error: no test specified\" && exit 1" }, "dependencies": { "dnotebook": "^0.1.1" } }

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3) Run (using terminal command)

>npm install

>dnotebook

4) Use dnotebook in the browser

5) Try uploading json data from https://pastebin.com/raw/K8gcmPb4

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You should be getting the following output

Using ObservableHq Online (Notebook) Editor For JavaScript ML Programming Like Python Jupyter Notebook

 

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Observable is not just another JavaScript sandbox. It introduces the notebook paradigm to JavaScript projects, those of you familiar with Jupyter notebooks, this is the equivalent with JavaScript instead of Python. It turns out JavaScript is very well-suited to this type of paradigm.

What’s more, JavaScript developers already have some sort of familiarity with reactivity since most frontend frameworks and view libraries build on it. It’s a different kind of reactivity, in that the library only re-renders or re-computes the section of the application that needs it (cf. Vue, Angular, React).

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https://codewithhugo.com/observablehq-notebooks-for-javascript-demos-and-prototypes/

ObservableHq Tutorial: Introduction to Data (JavaScript ML Notebook Alternative To Python ML Jupyter Notebook)

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Introduction to Data

How do you get data into Observable for analysis and visualization? Depending on its form and where it lives, there are a variety of ways:

• inline - embedded in the notebook as code, for small amounts of data
• files - attached to the notebook, for medium amounts of data (e.g., CSV, SQLite)
• APIs - queried from a remote server, for programmatic access to data
• databases - via an Observable database client, for accessing SQL databases

You can also download generated data from notebooks.

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https://observablehq.com/@observablehq/introduction-to-data

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SQLite

Observable has built-in support for SQLite, “a small, fast, self-contained, high-reliability, full-featured, SQL database engine” and “the most used database engine in the world.” Observable’s SQLite client uses sql.js, an Emscripten port of SQLite.

After attaching a SQLite file to your notebook, create a SQLite database client by calling file.sqlite().

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https://observablehq.com/@observablehq/sqlite

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