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About geocoding there are some features that I think we should highlight somehow, since they are clear differentiators to other geocoding libraries. Not sure if in this guide or in any other place... just writing down my thoughts here by now:
As part of the geocoding result you get, the dataframe and the metadata. The metadata contains very important information for any spatial analysis. If you geocode addresses and you don't get accurate results, then your complete analysis might be wrong. I think to highlight that, we could filter the geocoded results by a threshold of the relevance in the metadata.
Incremental geocoding. There's a very typical case in which you have a source dataframe, you geocode it (it's stored in your account), and then you add more data or new addresses, whatever... That would be a nice case for incremental geocoding.
Maybe it's a bit forced include those features in the guide, so maybe we just move the examples in the Data services reference to concrete sections in the guides. What do you think?
Nice feedback! As you said, sometimes there's something that will make the guide more complex and that might be out of the scope, in those cases it's better to link to an external example / reference as you mention.
About 1. I think this should be included in the guide, it's important and I think this is the best place to add it and highlight it.
About 2. Good catch, I didn't know about this use case. My opinion is that we should add an example of incremental geocoding and add the link in the guide.
[EPIC] #967
Use Location Data Services
Introduction:
Data used:
Consuming Quota
dry_run
option to prevent consuming quota.Geocoding Service
Local Cache
Results: data
Results: metadata
metadata
containsIsolines Service
Isodistances
Isochrones
Conclusion
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