Reputation: 4213
I have one large numpy.ndarray array that I want to extract the 4th and 5th columns out of and put those columns into a 2D array. The [i,0] element should be the value on the 4th column and [i,1] should be the element from the 5th column.
I trying to use the numpy.hstack function to do this.
a = numpy.asarray([1, 2, 3, 4, 5])
for i in range(5):
a = numpy.vstack([a, numpy.asarray([1, 2, 3, 4, 5])])
combined = np.hstack([a[:,3], a[:,4]])
However, this simply gives me an nx1 array. I have tried multiple approaches using concatenate that look like these examples:
combined = np.concatenate([a[:,3], a[:,4]])
combined = np.concatenate([a[:,3], a[:,4]], axis=1)
combined = np.concatenate([a[:,3].T, a[:,4].T])
I feel like hstack is the function I want, but I can't seem to figure out how to make it give me an nx2 array. Can anyone point me in the right direction? Any help is appreciated.
Upvotes: 11
Views: 16986
Reputation: 1649
Just slice out your data as follows:
X = [[0 1 2 3 4]
[0 1 2 3 4]
[0 1 2 3 4]
[0 1 2 3 4]]
slicedX = X[:,3:5]
results in:
[[3 4]
[3 4]
[3 4]
[3 4]]
Upvotes: 4
Reputation: 22882
You can also use zip
:
>>> c = numpy.array( zip( a[:, 3], a[:, 4]) )
>>> c
array([[4, 5],
[4, 5],
[4, 5],
[4, 5],
[4, 5],
[4, 5]])
Upvotes: 1