Create python notebook to explore processed NOM data

[samobermiller]

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kheal commented on 2024-09-10T20:19:14Z
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Define NOM and all other acronyms at the start.

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kheal commented on 2024-09-10T20:19:15Z
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Line #8.    #import nom_functions.py in second_omics_type folder as module to utilize its functions

I think this points to the incorrect location now. Can you separate out this import to a second chunk and explain/point to the other notebook that describes these functions more fully?

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kheal commented on 2024-09-10T20:19:16Z
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Line #9.    import nom_functions as func

Can we import/save as nmdc_api or something similar? The functions are not NOM-specific.

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kheal commented on 2024-09-10T20:19:17Z
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For explicitness, can we change " object ID" to " processed_nom_id "?

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kheal commented on 2024-09-10T20:19:17Z
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ID should be id

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kheal commented on 2024-09-10T20:19:18Z
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Can you add a bit of narrative here about why/how you queried all the fields for this step? Then you can use that to say you'll use the Envo information on the biosamples to label each as a type of sample (which leads into the next step)

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kheal commented on 2024-09-10T20:19:19Z
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How about

"Create final data frame of relevant metadata and NMDC schema information for each NOM processed data object"

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kheal commented on 2024-09-10T20:19:20Z
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I would move this up one chunk (before the "Create final dataframe" step)

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kheal commented on 2024-09-10T20:19:27Z
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Since you're getting warnings with this, I would try to downselect until you do not get warnings or set your settings so warnings are not displayed. We don't want the warnings messages in the notebook.

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kheal commented on 2024-09-10T20:19:28Z
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I would add a bit of narrative here about what a Van Krevelen plot is and how they are used. Nothing extensive - think wikipedia-level (https://en.wikipedia.org/wiki/Van_Krevelen_diagram).

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kheal commented on 2024-09-10T20:19:29Z
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For the Marginal Density Plot, if the OC/HC ratio is in both soil and sand, how does that appear? Consider making the overlapping formula a separate color (black?) which would highlight formula that were only seen in a subset of the sample types.

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kheal commented on 2024-09-10T20:19:30Z
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Line #9.    g.figure.subplots_adjust(top=0.8)

I would split this into two different chunks! One for the top plot, a second with the bottom.

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kheal commented on 2024-09-10T20:19:30Z
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I think these next parts are really cool and the visualizations look awesome, but they make the notebook very long, so I'd vote to cut them.

[samobermiller]

I thought the random state setting was the seed?

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[kheal]

Aha! You're right :)

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