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I was creating a numpy.empty([0]) array and accidentally typed numpy.empty([]).

This created an numpy array with the string representation

array(0.)

with size

>>> numpy.empty([]).size
1

and shape

>>> numpy.empty([]).shape
()

Question: what is the nature of this object?

I couldn't deduce it from the documentation of numpy.empty. In particular, what I find most confusing is the 0. that appears in the string representation, which seems to be a float(0.0). If it is somehow representing an element, this is not accessible. I was trying to access it as numpy.empty([])[0].

The object is different in nature from the one created by numpy.empty([0]), which has size

>>> numpy.empty([0]).size
0

and shape

>>> numpy.empty([0]).shape
(0,)
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2 Answers 2

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That's a 0-dimensional array. The first argument to numpy.empty indicates how long you want each dimension to be, and passing a length-0 list means you don't want any dimensions.

There is exactly one element in any 0-dimensional array, accessible by indexing it with a tuple of 0 indices:

arr[()]

The element happened to be 0.0 this time, but that's not a guarantee, since you used numpy.empty.

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1 Comment

I guess that they put an element in it due to $\prod_{i\in D}d_i$ being $1$ if $D$ is the empty set.
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  • np.empty([10, 10, 10]) creates a 3-dimensional array, with size 10x10x10 or 103
  • np.empty([10, 10]) creates a 2-dimensional array, with size 10x10 or 102
  • np.empty([10]) creates a 1-dimensional array, with size 10 or 101
  • np.empty([]) creates a 0-dimensional array, with size 1 or 100
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