Reputation:
I would like to create a numpy array with mixed types. The other SO questions that I found either create an object
based array or an nested array.
Both I do not want.
How would the syntax look like to have a numpy array with one str
and two int
columns?
This is my present code:
import numpy as np
b = np.empty((0, 3), )
b = np.insert(b, b.shape[0], [[1, 2, 3]], axis=0)
b = np.insert(b, b.shape[0], [[1, 2, 3]], axis=0)
print(b)
print("---")
a = np.empty((0, 3), dtype='S4, int, int')
a = np.insert(a, a.shape[0], ("a", 2, 3), axis=0)
a = np.insert(a, a.shape[0], ("a", 2, 3), axis=0)
print(a)
The output:
[[1. 2. 3.]
[1. 2. 3.]]
---
[[(b'a', 2, 3) (b'a', 2, 3) (b'a', 2, 3)]
[(b'a', 2, 3) (b'a', 2, 3) (b'a', 2, 3)]]
EDIT:
And what I need for the array a
is:
[["a" 2 3]
["a" 2 3]]
Upvotes: 1
Views: 4907
Reputation: 231665
Your second array is close, though I'd do it with indexing rather than insert (which is slower):
In [431]: a = np.zeros(3, dtype='S4, int, int')
In [432]: a[0] = ('a', 2, 3)
In [433]: a[1] = 1
In [434]: a
Out[434]:
array([(b'a', 2, 3), (b'1', 1, 1), (b'', 0, 0)],
dtype=[('f0', 'S4'), ('f1', '<i8'), ('f2', '<i8')])
A list of tuples is also a good way of constructing such an array:
In [436]: a = np.array([('a',2,3),('b',4,5)], dtype='S4, int, int')
In [437]: a
Out[437]:
array([(b'a', 2, 3), (b'b', 4, 5)],
dtype=[('f0', 'S4'), ('f1', '<i8'), ('f2', '<i8')])
Note that the shape is 1d (n,), with 3 fields. The fields don't count as a dimension.
Fields are accessed by name, not 'column' number:
In [438]: a['f1']
Out[438]: array([2, 4])
You made a (2,3) array, and filled each 'row' with the same thing. That's why you have repeats, while I don't.
With a unicode string dtype (default for Py3):
In [439]: a = np.array([('a',2,3),('b',4,5)], dtype='U4, int, int')
In [440]: a
Out[440]:
array([('a', 2, 3), ('b', 4, 5)],
dtype=[('f0', '<U4'), ('f1', '<i8'), ('f2', '<i8')])
In [441]: print(a)
[('a', 2, 3) ('b', 4, 5)]
Upvotes: 2