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  • rgieseke · 1 ✖

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  • Consider data-package as a format for metadata · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
345503897 https://github.com/simonw/datasette/issues/105#issuecomment-345503897 https://api.github.com/repos/simonw/datasette/issues/105 MDEyOklzc3VlQ29tbWVudDM0NTUwMzg5Nw== rgieseke 198537 2017-11-19T09:38:08Z 2017-11-19T09:38:08Z CONTRIBUTOR

Thanks, I wrote this very simple reader because the default approach as described on the Datahub pages seemed to complicated. I had metadata from the datapackage.json attached to the returned DataFrames but removed this due to some attribute handling change in the latest Pandas version.

This could also be useful for getting from Data Package to SQL db: https://github.com/frictionlessdata/tableschema-sql-py

I maintain a few climate science related dataset at https://github.com/openclimatedata/

The Data Retriever (mainly ecological data) by @ethanwhite et al. is also using the Data Package format for metadata and has some tooling for different dbs:

https://frictionlessdata.io/articles/the-data-retriever/ https://github.com/weecology/retriever

The Open Power System Data project also has a couple of datasets that show nicely how CSV is great for assembling and then already make SQLite files available. It's one of the first data sets I tried with Datasette, perfect for the use case of getting an API for putting power stations on a map ...

https://data.open-power-system-data.org/

 
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 Consider data-package as a format for metadata 274314940  

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