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# numpy.reshape

`numpy.``reshape`(a, newshape, order='C')

  Gives a new shape to an array without changing its data.

  Parameters: | a : array_like Array to be reshaped. newshape : {tuple, int} The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions. order : {‘C’, ‘F’}, optional Determines whether the array data should be viewed as in C (row-major) order or FORTRAN (column-major) order.
  Returns: | reshaped_array : ndarray This will be a new view object if possible; otherwise, it will be a copy.

  See also

  `ndarray.reshape`
    Equivalent method.

  Examples

      >>> a = np.array([[1,2,3], [4,5,6]])
      >>> np.reshape(a, 6)
      array([1, 2, 3, 4, 5, 6])
      >>> np.reshape(a, 6, order='F')
      array([1, 4, 2, 5, 3, 6])
      >>> np.reshape(a, (3,-1))       # the unspecified value is inferred to be 2
      array([[1, 2],
             [3, 4],
             [5, 6]])

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