Add Jupyter Notebook Examples with Deno Kernel

[beingminimal]

This issue proposes expanding the documentation for Deno examples to include comprehensive examples of Jupyter Notebook use cases with the Deno kernel. Currently, the documentation may lack detailed guidance on leveraging Jupyter Notebooks with Deno.

Motivation:

Jupyter Notebooks provide an interactive environment for data analysis, visualization, and code experimentation. By showcasing diverse use cases with the Deno kernel, we can empower users to effectively integrate Deno into their Jupyter workflows.

Proposed Changes:

We should add examples demonstrating various Jupyter Notebook functionalities with the Deno kernel. These examples should cover a wide range of use cases, including but not limited to:

• Basic Execution: Demonstrating simple Deno code execution within a Jupyter cell. This includes basic console.log statements, variable assignments, and simple calculations. Example:

  // In a Jupyter cell
  console.log("Hello from Deno in Jupyter!");
  
  const x = 10;
  const y = 20;
  console.log(`The sum of ${x} and ${y} is ${x + y}`);

• Module Imports: Showcasing how to import and use Deno modules (both standard and third-party) within a Jupyter Notebook. This should include examples using import statements and handling module resolution (including remote URLs).

• Asynchronous Operations: Demonstrating the use of async/await and Promises within Jupyter cells, highlighting Deno's asynchronous nature. Examples should include fetching data from APIs or performing other asynchronous tasks.

• Data Visualization: Integrating Deno with data visualization libraries (if available or through interoperability with JavaScript libraries like Plotly or Chart.js) to create charts and graphs within the notebook.

• File System Access: Demonstrating how to read and write files using Deno's file system APIs within a Jupyter Notebook.

• Testing: Showing how to incorporate unit tests within a Jupyter Notebook using Deno's built-in testing framework (Deno.test).

• Interoperability with JavaScript Libraries: Demonstrating how to use JavaScript libraries from within the Deno kernel in Jupyter. This is crucial for accessing the wider JavaScript ecosystem. Examples using npm: specifiers should be included.

• Web Workers (if supported): If the Deno kernel supports Web Workers within Jupyter, examples should be provided demonstrating their usage for parallel processing.

• Using specific Deno APIs: Examples using Deno.serve, Deno.connect, Deno.Command, Deno.run, Deno.test, Deno.bench, Deno.cron, Deno.dlopen (if relevant in a notebook context).

• Using different output formats: Showing how to display different output formats in Jupyter cells (e.g., HTML, Markdown, images using display function if available in the kernel).

• Deno OpenTelemetry (OTel) Data Visualization: Demonstrating how to use Deno with OpenTelemetry for tracing and metrics, and then visualizing that data within the Jupyter Notebook. This could involve using libraries or tools that can process and display OTel traces and metrics data. Examples could include visualizing traces as flame graphs or metrics as time-series charts.

Acceptance Criteria:

• The documentation should include clear and concise examples for each of the use cases mentioned above.
• The examples should be well-commented and easy to understand.
• The documentation should be integrated into the existing Deno examples documentation.