def is_na(self) -> bool:
blk = self.block
if blk.dtype.kind == "V":
return True
if not blk._can_hold_na:
return False
values = blk.values
if values.size == 0:
return True
if isinstance(values.dtype, SparseDtype):
return False
if values.ndim == 1:
# TODO(EA2D): no need for special case with 2D EAs
val = values[0]
if not is_scalar(val) or not isna(val):
# ideally isna_all would do this short-circuiting
return False
return isna_all(values)
else:
val = values[0][0]
if not is_scalar(val) or not isna(val):
# ideally isna_all would do this short-circuiting
return False
return all(isna_all(row) for row in values)
def is_na(self) -> bool:
if self.block is None:
return True
if not self.block._can_hold_na:
return False
values = self.block.values
if isinstance(self.block.values.dtype, SparseDtype):
return False
elif self.block.is_extension:
# TODO(EA2D): no need for special case with 2D EAs
values_flat = values
else:
values_flat = values.ravel(order="K")
return isna_all(values_flat)
def is_na(self) -> bool:
if self.block is None:
return True
if not self.block._can_hold_na:
return False
# Usually it's enough to check but a small fraction of values to see if
# a block is NOT null, chunks should help in such cases. 1000 value
# was chosen rather arbitrarily.
values = self.block.values
if is_sparse(self.block.values.dtype):
return False
elif self.block.is_extension:
# TODO(EA2D): no need for special case with 2D EAs
values_flat = values
else:
values_flat = values.ravel(order="K")
return isna_all(values_flat)
