code: def unsqueeze(data, axis, oldshape):
      """
      Unsqueeze a collapsed array.
  
      Parameters
      ----------
      data : ndarray
          The data to unsqueeze.
      axis : int
          The axis to unsqueeze.
      oldshape : tuple[int]
          The original shape before the squeeze or reduce operation.
  
      Returns
      -------
      ndarray
          The unsqueezed array.
  
      Examples
      --------
      >>> from numpy import mean
      >>> from numpy.random import standard_normal
      >>> x = standard_normal((3,4,5))
      >>> m = mean(x, axis=1)
      >>> m.shape
      (3, 5)
      >>> m = unsqueeze(m, 1, x.shape)
      >>> m.shape
      (3, 1, 5)
      >>>
      """
      newshape = list(oldshape)
      newshape[axis] = 1
      return data.reshape(newshape)
  
imports: import numpy
  import pandas
  import scipy.linalg
  from statsmodels.tools.data import _is_using_pandas
  from statsmodels.tools.validation import array_like
label_desc: Use image node_id 12 for calling a global function with example usage: unsqueeze(data, axis, oldshape) and returns: data