Numpy data loaded from file using memmap throws exception when used in formatted output

The following example demonstrates the issue.

>>> import numpy as np
>>> X = np.random.randn(10,3)
>>> np.save("x.npy", X)
>>> Y = np.load("x.npy", "r")
>>> Y.min()
memmap(-2.3064808987512744)

>>> print(Y.min())
-2.3064808987512744

>>> print("{}".format(Y.min()))
-2.3064808987512744

>>> print("{:6.3}".format(Y.min()))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: non-empty format string passed to object.__format__

Without the mode = 'r' in the load function, everything works as expected. Is this a bug? Or, am missing something?

Is there anyway to 'extract' the float value from the memmap to use it directly?

EDIT:

The 'item' method can be used to 'Copy an element of an array to a standard Python scalar and return it'. So, the following code works:

>>> print("{:6.3}".format(Y.min().item(0)))
  -2.31

Is there a rhyme or reason when you need to extract a value to use it?