code: def _pad_nans(x, head=None, tail=None):
      if np.ndim(x) == 1:
          if head is None and tail is None:
              return x
          elif head and tail:
              return np.r_[[np.nan] * head, x, [np.nan] * tail]
          elif tail is None:
              return np.r_[[np.nan] * head, x]
          elif head is None:
              return np.r_[x, [np.nan] * tail]
      elif np.ndim(x) == 2:
          if head is None and tail is None:
              return x
          elif head and tail:
              return np.r_[
                  [[np.nan] * x.shape[1]] * head,
                  x,
                  [[np.nan] * x.shape[1]] * tail,
              ]
          elif tail is None:
              return np.r_[[[np.nan] * x.shape[1]] * head, x]
          elif head is None:
              return np.r_[x, [[np.nan] * x.shape[1]] * tail]
      else:
          raise ValueError("Nan-padding for ndim > 2 not implemented")
  
file_path: statsmodels/statsmodels/tsa/filters/filtertools.py
imports: import numpy
  import scipy.fftpack
  from scipy import signal
  from statsmodels.tools.validation import array_like, PandasWrapper
label_desc: Use image node_id 1 for calling a global function with example usage: _pad_nans(x, head, tail) and returns: x, np, x, np, np, np, np, np