创建一个包含3个元素的矩阵：

In [550]: M = sparse.coo_matrix(([.5,.4,.6],([0,1,2],[0,5,3])), shape=(5,7))

默认显示（repr(M)）：

In [551]: M
Out[551]: 
<5x7 sparse matrix of type '<class 'numpy.float64'>'
    with 3 stored elements in COOrdinate format>

and print display（str（M））-看起来像输入：

In [552]: print(M)
  (0, 0)    0.5
  (1, 5)    0.4
  (2, 3)    0.6

转换为csr：

In [553]: Mc=M.tocsr()
In [554]: Mc[1,:]   # row 1 is another matrix (1 row):
Out[554]: 
<1x7 sparse matrix of type '<class 'numpy.float64'>'
    with 1 stored elements in Compressed Sparse Row format>

In [555]: Mc[1,:].A    # that row as 2d array
Out[555]: array([[ 0. ,  0. ,  0. ,  0. ,  0. ,  0.4,  0. ]])

In [556]: print(Mc[1,:])    # like 2nd element of M except for row number
  (0, 5)    0.4

单个元素：

In [560]: Mc[1,5]
Out[560]: 0.40000000000000002

这些格式的数据属性（如果您想进一步挖掘）

In [562]: Mc.data
Out[562]: array([ 0.5,  0.4,  0.6])
In [563]: Mc.indices
Out[563]: array([0, 5, 3], dtype=int32)
In [564]: Mc.indptr
Out[564]: array([0, 1, 2, 3, 3, 3], dtype=int32)
In [565]: M.data
Out[565]: array([ 0.5,  0.4,  0.6])
In [566]: M.col
Out[566]: array([0, 5, 3], dtype=int32)
In [567]: M.row
Out[567]: array([0, 1, 2], dtype=int32)

我们可以将scipy.sparse.coo_array转换为pandas.DataFrame。
效用函数：

from scipy.sparse import coo_array
import pandas as pd

def coo_to_dataframe(array: coo_array) -> pd.DataFrame:
    """Convert scipy COO sparse array to a pandas data frame."""
    labels = array.data
    columns = array.col
    rows = array.row

    data_frame = pd.DataFrame({"x": columns, "y": rows, "label": labels})

    return data_frame

创建一个稀疏数组（借用自@hpaulj）：

sparse_array = coo_array(([.5, .4, .6], ([0 , 1, 2], [0, 5, 3])), shape=(5, 7))

对于一个小的示例数组，我们可以将其视为密集数组：

sparse_array.toarray()

array([[0.5, 0. , 0. , 0. , 0. , 0. , 0. ],
       [0. , 0. , 0. , 0. , 0. , 0.4, 0. ],
       [0. , 0. , 0. , 0.6, 0. , 0. , 0. ],
       [0. , 0. , 0. , 0. , 0. , 0. , 0. ],
       [0. , 0. , 0. , 0. , 0. , 0. , 0. ]])

最后，我们将稀疏数组转换为DataFrame并绘制它。

dataframe = coo_to_dataframe(sparse_array)

dataframe.plot.scatter("x", "y", title="Sparse labels")