class_docstr: Prediction results
  
  Parameters
  ----------
  predicted_mean : {ndarray, Series, DataFrame}
      The predicted mean values
  var_pred_mean : {ndarray, Series, DataFrame}
      The variance of the predicted mean values
  dist : {None, "norm", "t", rv_frozen}
      The distribution to use when constructing prediction intervals.
      Default is normal.
  df : int, optional
      The degree of freedom parameter for the t. Not used if dist is None,
      "norm" or a callable.
  row_labels : {Sequence[Hashable], pd.Index}
      Row labels to use for the summary frame. If None, attempts to read the
      index of ``predicted_mean``
code: def _wrap_pandas(self, value, name=None, columns=None):
      if not self._use_pandas:
          return value
      if value.ndim == 1:
          return pd.Series(value, index=self._row_labels, name=name)
      return pd.DataFrame(
          value, index=self._row_labels, columns=columns
      )
  
file_path: statsmodels/statsmodels/tsa/base/prediction.py
imports: import numpy
  import pandas
  from scipy import stats
label_desc: Use image node_id 2 for calling the PredictionResults obj's underlying member method code with example usage: obj._wrap_pandas(value, name, columns) and returns: pd, value, pd