type(A)
<class 'scipy.sparse.csc.csc_matrix'>
A.shape
(8529, 60877)
print A[0,:]
(0, 25) 1.0
(0, 7422) 1.0
(0, 26062) 1.0
(0, 31804) 1.0
(0, 41602) 1.0
(0, 43791) 1.0
print A[1,:]
(0, 7044) 1.0
(0, 31418) 1.0
(0, 42341) 1.0
(0, 47125) 1.0
(0, 54376) 1.0
print A[:,0]
#nothing returned
Now what I don't understand is that A[1,:]
should select elements from the 2nd row, yet I get elements from the 1st row via print A[1,:]
. Also, print A[:,0]
should return the first column but I get nothing printed. Why?
A[1,:]
is itself a sparse matrix with shape (1, 60877). This is what you are printing, and it has only one row, so all the row coordinates are 0.
For example:
In [41]: a = csc_matrix([[1, 0, 0, 0], [0, 0, 10, 11], [0, 0, 0, 99]])
In [42]: a.todense()
Out[42]:
matrix([[ 1, 0, 0, 0],
[ 0, 0, 10, 11],
[ 0, 0, 0, 99]], dtype=int64)
In [43]: print(a[1, :])
(0, 2) 10
(0, 3) 11
In [44]: print(a)
(0, 0) 1
(1, 2) 10
(1, 3) 11
(2, 3) 99
In [45]: print(a[1, :].toarray())
[[ 0 0 10 11]]
You can select columns, but if there are no nonzero elements in the column, nothing is displayed when it is output with print
:
In [46]: a[:, 3].toarray()
Out[46]:
array([[ 0],
[11],
[99]])
In [47]: print(a[:,3])
(1, 0) 11
(2, 0) 99
In [48]: a[:, 1].toarray()
Out[48]:
array([[0],
[0],
[0]])
In [49]: print(a[:, 1])
In [50]:
The last print
call shows no output because the column a[:, 1]
has no nonzero elements.