AttributeError: 'DataFrame' object has no attribute 'to

sdf = df.to_sparse() has been deprecated. What's the updated version of this?

CodePudding user response：

These are the updated sparse conversions as of pandas 1.0.0.

To convert dense to sparse

Use DataFrame.astype() with the appropriate SparseDtype() (e.g., int):

>>> df = pd.DataFrame({'A': [1, 0, 0, 1]})
>>> df.dtypes
# A    int64
# dtype: object

>>> df = df.astype(pd.SparseDtype(int, fill_value=0))
>>> df.dtypes
# A    Sparse[int64, 0]
# dtype: object

Or use the string alias for brevity:

>>> df = df.astype('Sparse[int64, 0]')

To convert sparse to dense

Use DataFrame.sparse.to_dense():

>>> from scipy import sparse
>>> df = pd.DataFrame.sparse.from_spmatrix(sparse.eye(3), columns=list('ABC'))
>>> df.dtypes
# A    Sparse[float64, 0]
# B    Sparse[float64, 0]
# C    Sparse[float64, 0]
# dtype: object

>>> df = df.sparse.to_dense()
>>> df.dtypes
# A    float64
# B    float64
# C    float64
# dtype: object

To convert sparse to COO

Use DataFrame.sparse.to_coo():

>>> from scipy import sparse
>>> df = pd.DataFrame.sparse.from_spmatrix(sparse.eye(3), columns=list('ABC'))
>>> df.dtypes
# A    Sparse[float64, 0]
# B    Sparse[float64, 0]
# C    Sparse[float64, 0]
# dtype: object

>>> df = df.sparse.to_coo()
# <3x3 sparse matrix of type '<class 'numpy.float64'>'
#         with 3 stored elements in COOrdinate format>
# (0, 0)    1.0
# (1, 1)    1.0
# (2, 2)    1.0

CodePudding user response：

You can use scipy to create sparse matrix:

scipy.sparse.csr_matrix(df.values)