code: def column_stack(tup):
      """
      Stack 1-D arrays as columns into a 2-D array.
  
      Take a sequence of 1-D arrays and stack them as columns
      to make a single 2-D array. 2-D arrays are stacked as-is,
      just like with `hstack`.  1-D arrays are turned into 2-D columns
      first.
  
      Parameters
      ----------
      tup : sequence of 1-D or 2-D arrays.
          Arrays to stack. All of them must have the same first dimension.
  
      Returns
      -------
      stacked : 2-D array
          The array formed by stacking the given arrays.
  
      See Also
      --------
      stack, hstack, vstack, concatenate
  
      Examples
      --------
      >>> a = np.array((1,2,3))
      >>> b = np.array((2,3,4))
      >>> np.column_stack((a,b))
      array([[1, 2],
             [2, 3],
             [3, 4]])
  
      """
      _warn_for_nonsequence(tup)
      arrays = []
      for v in tup:
          arr = array(v, copy=False, subok=True)
          if arr.ndim < 2:
              arr = array(arr, copy=False, subok=True, ndmin=2).T
          arrays.append(arr)
      return _nx.concatenate(arrays, 1)
  
imports: from __future__ import division, absolute_import, print_function
  import functools
  import warnings
  import numpy.core.numeric
  from numpy.core.numeric import asarray, zeros, outer, concatenate, array, asanyarray
  from numpy.core.fromnumeric import product, reshape, transpose
  from numpy.core.multiarray import normalize_axis_index
  from numpy.core import overrides
  from numpy.core import vstack, atleast_3d
  from numpy.core.shape_base import _arrays_for_stack_dispatcher, _warn_for_nonsequence
  from numpy.lib.index_tricks import ndindex
  from numpy.matrixlib.defmatrix import matrix
label_desc: Use image node_id 13 for calling a global function with example usage: column_stack(tup) and returns: _nx