Given a numpy 2d array (or a matrix), I would like to extract all the columns but the i-th.
E. g. from
1 2 3 4
2 4 6 8
3 6 9 12
I would like to have, e.g.
1 2 3
2 4 6
3 6 9
or
1 2 4
2 4 8
3 6 12
I cannot find a pythonic way to do this. I now that you can extract given columns by simply
a[:,n]
or
a[:,[n,n+1,n+5]]
But what about extracting all of them but one?
Since for the general case you are going to be returning a copy anyway, you may find yourself producing more readable code by using np.delete:
>>> a = np.arange(12).reshape(3, 4)
>>> np.delete(a, 2, axis=1)
array([[ 0, 1, 3],
[ 4, 5, 7],
[ 8, 9, 11]])
a matrix. which is what I was expecting.Use a slice that excludes the last element.
In [19]: a[:,:-1]
Out[19]:
array([[1, 2, 3],
[2, 4, 6],
[3, 6, 9]])
If you want something other than the last element I'd just build a list to select with.
In [20]: selector = [x for x in range(a.shape[1]) if x != 2]
In [21]: a[:, selector]
Out[21]:
array([[ 1, 2, 4],
[ 2, 4, 8],
[ 3, 6, 12]])
http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html
.remove doesn't return the array it modifies it in place, so the result of range(a.shape[1]).remove(2) is None. You could use selector = range(a.shape[1]); selector.remove(2)Take a look at numpy's advanced slicing
>>> import numpy as np
>>> a = np.array([[1,2,3,4], [2,4,6,8], [3,6,9,12]])
>>> a[:,np.array([True, True, False, True])]
array([[ 1, 2, 4],
[ 2, 4, 8],
[ 3, 6, 12]])
The answers given already can easily be adapted to selecting all but a list of columns, but here are a couple of explicit examples:
In [1]: import numpy as np
In [2]: a = np.arange(12).reshape(3, 4)
In [3]: a
Out[3]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
In [4]: drop_cols = [0, 3]
# option 1: delete the columns you don't want (like @Jaime)
# (this is really the most straightforward)
In [5]: np.delete(a, drop_cols, axis=1)
Out[5]:
array([[ 1, 2],
[ 5, 6],
[ 9, 10]])
# option 2: pass the indices of columns to keep (like @chrisb)
In [6]: a[:, [i for i in range(a.shape[1]) if i not in drop_cols]]
Out[6]:
array([[ 1, 2],
[ 5, 6],
[ 9, 10]])
# option 3: use an array of T/F for each col (like @Peter Gibson)
In [7]: a[:, [i not in drop_cols for i in range(a.shape[1])]]
Out[7]:
array([[ 1, 2],
[ 5, 6],
[ 9, 10]])
