from scipy.sparse import *

row =  [0,0,0,1,1,1,2,2,2]#行指标
col =  [0,1,2,0,1,2,0,1,2]#列指标
data = [1,0,1,0,1,1,1,1,0]#在行指标列指标下的数字
team = csr_matrix((data,(row,col)),shape=(3,3))
print(team)
print(team.todense())


输出结果：
 (0, 0)	1
  (0, 1)	0
  (0, 2)	1
  (1, 0)	0
  (1, 1)	1
  (1, 2)	1
  (2, 0)	1
  (2, 1)	1
  (2, 2)	0
[[1 0 1]
 [0 1 1]
 [1 1 0]]

Process finished with exit code 0

row =  [0,0,0,0,1,1,1,1,2,2,2,2]#行指标
col =  [0,1,2,3,0,1,2,3,0,1,2,3]#列指标
data = [1,0,1,1,0,1,1,1,1,0,1,1]#在行指标列指标下的数字
team = csr_matrix((data,(row,col)),shape=(3,4))
# print(team)
# print(team.todense())
team_dok = team.todok()
# print(team_dok)

team_coo = team_dok.tocoo()

item =list(team_coo.col.reshape(-1))
# print(type(item))
print(item)


输出：
[0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]

team_coo = team_dok.tocoo()
item =list(team_coo.col.reshape(-1))
user =list(team_coo.row.reshape(-1))
print("col:",item)
print("row:",user)

输出：
col: [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]
row: [0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2]

Process finished with exit code 0