In [1]:

    

import numpy as np
from scipy.sparse import csr_matrix


    

In [2]:

    

l = [[0, 10, 20],
     [30, 0, 40],
     [0, 0, 0]]


    

In [3]:

    

csr = csr_matrix(l)
print(csr)


    

    




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

In [4]:

    

print(type(csr))


    

    




<class 'scipy.sparse.csr.csr_matrix'>

In [5]:

    

print(csr.shape)


    

    




(3, 3)

In [6]:

    

a = np.array(l)
print(a)


    

    




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

In [7]:

    

print(type(a))


    

    




<class 'numpy.ndarray'>

In [8]:

    

csr = csr_matrix(a)
print(csr)


    

    




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

In [9]:

    

print(type(csr))


    

    




<class 'scipy.sparse.csr.csr_matrix'>

In [10]:

    

print(csr_matrix([0, 1, 2]))


    

    




  (0, 1)	1
  (0, 2)	2

In [11]:

    

print(csr_matrix([0, 1, 2]).shape)


    

    




(1, 3)

In [12]:

    

# print(csr_matrix([[[0, 1, 2]]]))
# TypeError: expected dimension <= 2 array or matrix


    

In [13]:

    

print(csr.toarray())


    

    




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

In [14]:

    

print(type(csr.toarray()))


    

    




<class 'numpy.ndarray'>

In [15]:

    

print(csr.toarray().tolist())


    

    




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

In [16]:

    

print(type(csr.toarray().tolist()))


    

    




<class 'list'>

In [17]:

    

print(csr.todense())


    

    




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

In [18]:

    

print(type(csr.todense()))


    

    




<class 'numpy.matrix'>