Things I want to play with: PANDAS. Time series data. RESTful interfaces. Machine learning algorithms.
To that end, I downloaded the WADL spec for data coming from ISO-NE.com. It's complete. There is no point meddling with WADL here, as all the service is read-only for yours truly. The important part of the WADL spec is the < grammars %gt;
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Pandas rocks all socks.
Check out ddlgenerator in PyPI - it's kind of a mess but might do what you need very easily. And then once you've shoved that data into an RDBMS with ddlgenerator, you can use ipython_sql to query it out into Pandas DataFrames.
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The data in question can be represented pretty intuitively as multisheeted spread sheets.
Each sheet belongs to a UID'd entity (e.g. a power generator or a transmission junction), each column on the sheet a numerical observation belonging to it, and each row a point in time.
If ddl-generator figures it out from the JSON output, that would pretty much rock.
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