Getting to know... ObservableHQ

A couple of weeks ago, I looked at a demo of ObservableHQ and the first interesting difference between an Observable notebook and a Jupyter Notebook is that the output of an Observable notebook is above the code. In any case, today I signed up for an account and was presented with a Quickstart page with 12 different recommended reads. I went through two of them, A Taste of Observable and Learn D3.


A Taste of Observable (7 minute read)

So here are some of the items I noticed after going through this notebook:
- Can import and reuse object from another notebook (shown near the end of the notebook). In the example given, the imported object refers to local variable called `forecast`. However, since that object is being pulled away from it's source, we must assign ("inject") a new object to the variable name.
- Variables can be changed and changes will automatically push forward and update any cells which depend on those variables.
- I mentioned earlier that code output appears above the code input; it also seems that some of the code structure is reversed as well (e.g., imports often being placed at the bottom of the notebook instead of at the top)

Learn D3

This resource presents D3 via a series of Observable notebooks. I have allocated a separate post for it here, because only a small portion of it actually focuses on the functionality of an Observable notebook.


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