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danbri: This is a Github-rendered view of an ipython notebook including data from its last run (on a laptop). danbri: The Python code is the same codebase that runs schema.org, including SPARQL for each section of schemas (core, bib, autos, pending etc.). danbri: Of note: if you wrap a SPARQL resultset in the Python Pandas tabular data API you get better presentation, and some charting machinery from Matplotlib. danbri: The SPARQL queries are just examples. Would welcome suggestions for more interesting queries. danbri: Actually not sure the count-based queries are working properly. But I still find this nice enough to share :)
danbri: The Python code is the same codebase that runs schema.org, including SPARQL for each section of schemas (core, bib, autos, pending etc.).
danbri: Of note: if you wrap a SPARQL resultset in the Python Pandas tabular data API you get better presentation, and some charting machinery from Matplotlib.
danbri: The SPARQL queries are just examples. Would welcome suggestions for more interesting queries.
danbri: Actually not sure the count-based queries are working properly. But I still find this nice enough to share :)