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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