ENH: support timezones and uuid in explore #3261
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| @@ -323,6 +325,14 @@ def _colormap_helper(_cmap, n_resample=None, idx=None): | |||
| elif not gdf.crs.equals(4326): | |||
| gdf = gdf.to_crs(4326) | |||
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| # Fields which are not JSON serializable are coerced to strings | |||
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I put this here near the linearring & crs conversions. Originally had it just before producing a featurecollection, but needs to happen before categorical detection happens - if the timestamp is column, then it needs to already be a string to be handled properly, otherwise bins = np.linspace(vmin, vmax, 257)[1:] crashes.
m-richards
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I would do it exactly as you did in here. Automatically cast to strings, with no keywords. The explore API is already a bit large and if you really need to do something else, you can do it before calling explore. I would also not be worried about the performance hit, as explore is unusable for larger dataframes anyway.
That would make sense only for points as anything else would flood the tooltip with a long unreadable string. I'd hold on and do that only if someone feels it is needed. |
m-richards
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Resolves #2378.
A bit uncertain about the api here. If we by default cast timestamps / objects to strings implicitly then users may not realise the performance hit associated with doing so (although I would expect if you are hitting a performance bottleneck in
exploreit is the time taken to render all the geometry on the javascript side, not any input prep we do).We could expose a keyword controling behaviour of handling timestamp columns (coerce,skip,None), defaulting to None, which behaves as coerce, but perhaps warns about conversions happening when the input gdf has more than X rows?
We could also aim to get something simple working in for 1.0, and then consider if there are more performant options as a follow up.
There is also the option we could preserve additional geometry columns as WKT, rather than just drop them as we currently do.