create row, column, data pandas dataframe from sparse matrix

Question

How can I create a sparse matrix in the format of COO and have the pandas dataframe not unnest to a dense layout but keep the COO format for row,column,data?

import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix

a = np.eye(7)
a_csr = csr_matrix(a)
a_coo = a_csr.tocoo()
print(a_coo)
  (0, 0)    1.0
  (1, 1)    1.0
  (2, 2)    1.0
  (3, 3)    1.0
  (4, 4)    1.0
  (5, 5)    1.0
  (6, 6)    1.0

I.e. how can I obtain a pandas dataframe from this that does not unnest this to

pd.DataFrame.sparse.from_spmatrix(a_coo)

but keeps the row,column,data format as also visualized in the print operation?

Answer 1

The values you want to put in the dataframe are available as

a_coo.row, a_coo.col, a_coo.data