Float indexer to numpy array

575
January 05, 2017, at 08:30 AM

I want to make a numpy array that takes a float as a indexes (like, for example, a Pandas Series would if it had a float-type index). So let me explain. I want something like:

i = np.array([(5.,1), (6.,2)], dtype=[('foo', 'f4'),('bar', 'i4')])

if the first type (the 'foo' type), could be used as a indexer. So I could do

print(i[:5.5])

and it would print 1, or (5., 1).

I'm pretty sure that's possible with Numpy, I just don't know how to.

Answer 1

You might need logical indexing:

i[i['foo'] < 5.5]
# array([(5.0, 1)], 
#       dtype=[('foo', '<f4'), ('bar', '<i4')])
Answer 2

i[:5.5] does not have an obvious meaning.

i[:5] means the first 5 elements of the array (or list). i[:6] the first 6. What is it supposed to do with the 5.5? floor(5.5)? Ceiling? Return 5 and half elements? 5 elements plus a linear interpolation between the 5th and 6th?

Actually :5.5 works (in 1.11) but with a warning:

In [346]: np.arange(10)[:5]
Out[346]: array([0, 1, 2, 3, 4])
In [347]: np.arange(10)[:5.5]
/usr/local/bin/ipython3:1: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future
  #!/usr/bin/python3
Out[347]: array([0, 1, 2, 3, 4])

With your structured array, record indexing works the same way:

In [349]: i = np.array([(5.,1), (6.,2)], dtype=[('foo', 'f4'),('bar', 'i4')])
In [350]: i[:5]

It's ok to slice beyond the end - it just returns everything.

Out[350]: 
array([(5.0, 1), (6.0, 2)], 
      dtype=[('foo', '<f4'), ('bar', '<i4')])
In [351]: i[:5.5]
/usr/local/bin/ipython3:1: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future
  #!/usr/bin/python3
Out[351]: 
array([(5.0, 1), (6.0, 2)], 
      dtype=[('foo', '<f4'), ('bar', '<i4')])

================

Indexing in numpy is just a way of counting. There isn't an indexing or labeling list or array. That's something that pandas has added, but it isn't part of numpy. In your i array, fields do have names, e.g. i['foo']. It can look like column labeling, but it's dangerous to confuse structured fields with 2d columns.

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