def as_dataframe(self, pattern='*', max_rows=None):
    """Creates a pandas dataframe from the descriptors that match the filters.

    Args:
      pattern: An optional pattern to further filter the descriptors. This can
          include Unix shell-style wildcards. E.g. ``"aws*"``, ``"*cluster*"``.
      max_rows: The maximum number of descriptors to return. If None, return
          all.

    Returns:
      A pandas dataframe containing matching resource descriptors.
    """
    data = []
    for i, resource in enumerate(self.list(pattern)):
      if max_rows is not None and i >= max_rows:
        break
      labels = ', '. join([l.key for l in resource.labels])
      data.append([resource.type, resource.display_name, labels])

    return pandas.DataFrame(data, columns=self._DISPLAY_HEADERS)
def as_dataframe ( self , pattern = '*' , max_rows = None ) : data = [ ] for i , resource in enumerate ( self . list ( pattern ) ) : if max_rows is not None and i >= max_rows : break labels = ', ' . join ( [ l . key for l in resource . labels ] ) data . append ( [ resource . type , resource . display_name , labels ] ) return pandas . DataFrame ( data , columns = self . _DISPLAY_HEADERS )
Creates a pandas dataframe from the descriptors that match the filters.

    Args:
      pattern: An optional pattern to further filter the descriptors. This can
          include Unix shell-style wildcards. E.g. ``"aws*"``, ``"*cluster*"``.
      max_rows: The maximum number of descriptors to return. If None, return
          all.

    Returns:
      A pandas dataframe containing matching resource descriptors.