1

Using the example given here:

dt = np.dtype([('name', np.unicode_, 16), ('grades', np.float64, (2,))])
x = np.array([('Sarah', (8.0, 7.0)), ('John', (6.0, 7.0))], dtype=dt)

How can I access only the grades at say position 0 in the 'grades' array?

Because of the ambiguitiy of how I can access the grades of a specific person, i.e. because I can either write

>>> x['grades'][0]
>>> [8.0 7.0]

or

>>> x[0]['grades']
>>> [8.0 7.0]

which will both give the same result, I don't see any way for how I would be able to only access the grade at position 0, but for all the persons. Is there a way?

I cannot write

>>> x[0]['grades'][0]
>>> 8.0

or some combination like this

>>> x[:]['grades'][0]
>>> x[0]['grades'][:]

On the same note: Why is the shape of the 'grades' field declared as '(2,)', while '(2)', '[2,]', '[2]' and '2' all seem to give the same results?

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  • 1
    shape is a tuple. The proper display of a 1 element tuple is (2,). (2) is just the number 2, the () are a grouping tool, and ignored in not needed. [2] is a 1 element list. Often 2, [2] and (2,) work the same, but sometimes the distinction between number, list and tuple is significant. Commented Feb 27, 2019 at 17:46
  • I see thank you! I will stick with the proper display then. Commented Feb 28, 2019 at 9:30

1 Answer 1

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3

This will print, for each person, the first grade from grades:

print (x[:]['grades'][:,0])

Alternatively:

print(x['grades'][:,0])

Output:

[8. 6.]

Explanation:

  1. x[:]['grades'] (or x['grades']) produces a 2d array. Actually, it produces a 1d array of the values of grade, but then each value of grade is itself a 1d array. Net result, a 2d array:

    [[8. 7.] [6. 7.]]

  2. From this 2d array, we want to get only the first grade from each grade for all grades, so we then use the indexing [:,0]

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6 Comments

Great answer, thank you so much! Do you also have an explanation for my follow-up question?
@mapf: You're welcome. I'm afraid, I'm also stumped by why (2), [2,], [2] and 2 , all produce the same result as (2,). But you can be sure that no harm can ever come to you if you strictly follow the (n,) notation for a 1d shape. Shapes are always supposed to be represented by tuples, and it is the presence of one or more commas that makes something a tuple -- not the presence of parentheses.
Incidentally, the doc page you've referred to in your post, also has an example, where they create a 1d sub-array by specifying just 4 instead of (4,). So, whoever wrote that page is probably aware of this flexibility. As I said, it is always safe to stick to the (n,) notation for a 1d shape.
I see, thank you so much for the insight. I didn't know about the (n, ) notation or that the comma makes the touple. Very interesting!
It also helps to recall that given any expression (sayx+y) enclosing the expression in parentheses, as in (x+y) is only helpful in enforcing operator precedence (you want the + to be performed first). The parentheses doesn't result in a tuple. If you wanted that to become a tuple with a single value, you'd be using ((x+y),), or, whenever dropping the outer parentheses doesn't result in syntactic ambiguity, you could also be using (x+y), (with a comma, but no outer parentheses).
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