Exemple #1
0
    def as_dataframe(self, label=None, labels=None):
        """Return all the selected time series as a :mod:`pandas` dataframe.

        .. note::

            Use of this method requires that you have :mod:`pandas` installed.

        Examples::

            # Generate a dataframe with a multi-level column header including
            # the resource type and all available resource and metric labels.
            # This can be useful for seeing what labels are available.
            dataframe = query.as_dataframe()

            # Generate a dataframe using a particular label for the column
            # names.
            dataframe = query.as_dataframe(label='instance_name')

            # Generate a dataframe with a multi-level column header.
            dataframe = query.as_dataframe(labels=['zone', 'instance_name'])

            # Generate a dataframe with a multi-level column header, assuming
            # the metric is issued by more than one type of resource.
            dataframe = query.as_dataframe(
                labels=['resource_type', 'instance_id'])

        :type label: str
        :param label:
            (Optional) The label name to use for the dataframe header.
            This can be the name of a resource label or metric label
            (e.g., ``"instance_name"``), or the string ``"resource_type"``.

        :type labels: list of strings, or None
        :param labels: A list or tuple of label names to use for the dataframe
            header. If more than one label name is provided, the resulting
            dataframe will have a multi-level column header. Providing values
            for both ``label`` and ``labels`` is an error.

        :rtype: :class:`pandas.DataFrame`
        :returns: A dataframe where each column represents one time series.
        """
        return _build_dataframe(self, label, labels)  # pragma: NO COVER
Exemple #2
0
 def _callFUT(self, *args, **kwargs):
     from google.cloud.monitoring._dataframe import _build_dataframe
     return _build_dataframe(*args, **kwargs)