# pandas.io.json.build_table_schema

`pandas.io.json.``build_table_schema`(data, index=True, primary_key=None, version=True)

  Create a Table schema from `data`.

  Parameters:

  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.

  Returns: | schema : dict

  Notes

  See _as_json_table_type for conversion types. Timedeltas as converted to ISO8601 duration format with 9 decimal places after the seconds 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.

  Examples

      >>> 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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