, index=True, primary_key=None, version=True)[source]

Create a Table schema from data.


data : Series, DataFrame

index : bool, default True

Whether to include data.index in the schema.

primary_key : bool or None, default True

column names to designate as the primary key. The default None will set ‘primaryKey’ to the index level or levels if the index is unique.

version : bool, default True

Whether to include a field pandas_version with the version of pandas that generated the schema.


schema : dict


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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