Create a Table schema from data.
See _as_json_table_type for conversion types. Timedeltas as converted to ISO8601 duration format with 9 decimal places after the secnods field for nanosecond precision.
Categoricals are converted to the any dtype, and use the enum field constraint to list the allowed values. The ordered attribute is included in an ordered field.
>>> df = pd.DataFrame(
... {'A': [1, 2, 3],
... 'B': ['a', 'b', 'c'],
... 'C': pd.date_range('2016-01-01', freq='d', periods=3),
... }, index=pd.Index(range(3), name='idx'))
>>> build_table_schema(df)
{'fields': [{'name': 'idx', 'type': 'integer'},
{'name': 'A', 'type': 'integer'},
{'name': 'B', 'type': 'string'},
{'name': 'C', 'type': 'datetime'}],
'pandas_version': '0.20.0',
'primaryKey': ['idx']}
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