caikit.interfaces.ts.data_model.timeseries
==========================================

.. py:module:: caikit.interfaces.ts.data_model.timeseries


Attributes
----------

.. autoapisummary::

   caikit.interfaces.ts.data_model.timeseries.log
   caikit.interfaces.ts.data_model.timeseries.error


Classes
-------

.. autoapisummary::

   caikit.interfaces.ts.data_model.timeseries.TimeSeries


Module Contents
---------------

.. py:data:: log

.. py:data:: error

.. py:class:: TimeSeries(*args, **kwargs)

   Bases: :py:obj:`caikit.core.DataObjectBase`


   A DataObject is a data model class that is backed by a @dataclass.

   Data model classes that use the @dataobject decorator must derive from this
   base class.


   .. py:attribute:: timeseries
      :type:  List[caikit.interfaces.ts.data_model._single_timeseries.SingleTimeSeries]


   .. py:attribute:: id_labels
      :type:  List[str]


   .. py:attribute:: producer_id
      :type:  caikit.core.data_model.ProducerId


   .. py:attribute:: _DEFAULT_ID_COL
      :value: '_TS_RESERVED'



   .. py:attribute:: _DEFAULT_TS_COL
      :value: 'timestamp'



   .. py:method:: __len__() -> int

      Return the length of the time series object.

      Returns:
          int: Length



   .. py:method:: __eq__(other: TimeSeries) -> bool

      Equivalence operator for TimeSeries objects.

      Args:
          other (TimeSeries): TimeSeries to test against.

      Returns:
          bool: True if the TimeSeries are equivalent.



   .. py:method:: _get_pd_df() -> Tuple[pandas.DataFrame, Iterable[str], str, Iterable[str]]

      Convert the data to a pandas DataFrame, efficiently if possible



   .. py:method:: as_pandas(include_timestamps: Optional[bool] = None, is_multi: Optional[bool] = None) -> pandas.DataFrame

      Get the view of this timeseries as a pandas DataFrame

      Args:
          include_timestamps (bool, optional): Control the addition or removal of
          timestamps. True will include timestamps, generating if needed, while False will
          remove timestamps. Use None to returned what is available, leaving unchanged.
          Defaults to None.

          is_multi (bool, optional): Controls how id_labels are handled in the output. If
          the id_labels are specified in the data model, they are always returned. If there
          are no id_labels specified, setting is_multi to True will add a new column with
          generated id labels (0), while False or None will not add any id_labels.

      Returns:
          pd.DataFrame: The view of the data as a pandas DataFrame



   .. py:method:: as_spark(include_timestamps: Optional[bool] = None, is_multi: Optional[bool] = None) -> caikit.interfaces.ts.data_model.toolkit.optional_dependencies.pyspark.sql.DataFrame

      Get the view of this timeseries as a spark DataFrame

      Args:
          include_timestamps (bool, optional): Control the addition or removal of
          timestamps. True will include timestamps, generating if needed, while False will
          remove timestamps. Use None to returned what is available, leaving unchanged.
          Defaults to None.

          is_multi (bool, optional): Controls how id_labels are handled in the output. If
          the id_labels are specified in the data model, they are always returned. If there
          are no id_labels specified, setting is_multi to True will add a new column with
          generated id labels (0), while False or None will not add any id_labels.

      Returns:
          pyspark.sql.DataFrame: The view of the data as a spark DataFrame