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In [1]:

from scipy.sparse import csr_matrix, csc_matrix, coo_matrix

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In [2]:

data = [10, 20, 30, 40]
row = [0, 0, 1, 1]
col = [1, 2, 0, 2]

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In [3]:

print(csr_matrix((data, (row, col))).toarray())

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[[ 0 10 20]
[30  0 40]]

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In [4]:

print(csr_matrix((data, (row, col)), shape=(3, 3)).toarray())

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[[ 0 10 20]
[30  0 40]
[ 0  0  0]]

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In [5]:

print(csr_matrix((data, (row, col)), shape=(4, 4)).toarray())

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[[ 0 10 20  0]
[30  0 40  0]
[ 0  0  0  0]
[ 0  0  0  0]]

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In [6]:

data = [10, 20, 30, 40]
row = [0, 0, 1, 1]
col = [1, 2, 2, 2]

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In [7]:

print(csr_matrix((data, (row, col))))

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(0, 1)	10
(0, 2)	20
(1, 2)	70

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In [8]:

print(csc_matrix((data, (row, col))))

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(0, 1)	10
(0, 2)	20
(1, 2)	70

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In [9]:

print(coo_matrix((data, (row, col))))

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(0, 1)	10
(0, 2)	20
(1, 2)	30
(1, 2)	40

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In [10]:

print(coo_matrix((data, (row, col))).tocsr())

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(0, 1)	10
(0, 2)	20
(1, 2)	70

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In [11]:

print(coo_matrix((data, (row, col))).toarray())

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[[ 0 10 20]
[ 0  0 70]]

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In [12]:

print(csr_matrix(([10, 20, 30, 40], [1, 2, 0, 2], [0, 2, 4, 4]), shape=(3, 3)).toarray())

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[[ 0 10 20]
[30  0 40]
[ 0  0  0]]

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In [13]:

print(csc_matrix(([30, 10, 20, 40], [1, 0, 0, 1], [0, 1, 2, 4]), shape=(3, 3)).toarray())

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[[ 0 10 20]
[30  0 40]
[ 0  0  0]]

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