TypeError：SparseArray 不支持通过 setitem 进行项目分配

Question

鉴于：

import pandas as pd
print(pd.__version__) # '2.1.0'
df=pd.DataFrame([[1., 0., 1.5], [0., 2., 0.]], dtype=pd.SparseDtype("float32"))

我想在我的切片 pandas 稀疏数据框中分配自定义值，所以我执行以下操作：

df_sliced=df.iloc[0].copy() # OK
df_sliced.iloc[:]=0 # ERROR

我收到以下错误：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/indexing.py", line 885, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/indexing.py", line 1895, in _setitem_with_indexer
    self._setitem_single_block(indexer, value, name)
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/indexing.py", line 2138, in _setitem_single_block
    self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/internals/managers.py", line 399, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/internals/managers.py", line 354, in apply
    applied = getattr(b, f)(**kwargs)
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/internals/blocks.py", line 1758, in setitem
    values[indexer] = value
  File "/CSC_CONTAINER/miniconda/envs/env1/lib/python3.9/site-packages/pandas/core/arrays/sparse/array.py", line 583, in __setitem__
    raise TypeError(msg)
TypeError: SparseArray does not support item assignment via setitem

在 Pandas 中为

SparseDtype

赋值的有效方法（解决方法）是什么？

Answer 1

具有更多上下文的错误回溯是：

SparseArray.__setitem__(self, key, value)
    581 def __setitem__(self, key, value):
    582     # I suppose we could allow setting of non-fill_value elements.
    583     # TODO(SparseArray.__setitem__): remove special cases in
    584     # ExtensionBlock.where
    585     msg = "SparseArray does not support item assignment via setitem"
--> 586     raise TypeError(msg)

这告诉我

SparseArray

仍在开发中，目前设置值不起作用。我知道，通过使用

scipy.sparse

，设置稀疏值需要更多工作，特别是如果

fill

值可能更改为非填充。

scipy.sparse.coo_matrix

格式根本不实现索引 - 获取或设置。用于大多数计算的

csr_matrix

确实实现了索引，但使用

set

给出了效率警告。

set

可能会改变“稀疏性”、零（“填充”）和非零值的混合，从而改变底层索引。