BUG: np.log fails with missing pyarrow values

[mattharrison]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import numpy as np

import io
data = '''name,age,test1,test2,teacher
Adam,15,95.0,80,Ashby
Bob,16,81.0,82,Ashby
Dave,16,89.0,84,Jones
Fred,15,,88,Jones'''
scores = pd.read_csv(io.StringIO(data), dtype_backend='pyarrow',
                    engine='pyarrow'
                    )

(scores
 .test1
 .apply(np.log)
)

Issue Description

This throws an exception

AttributeError                            Traceback (most recent call last)
AttributeError: 'float' object has no attribute 'log'

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
Cell In[148], line 17
      5 data = '''name,age,test1,test2,teacher
      6 Adam,15,95.0,80,Ashby
      7 Bob,16,81.0,82,Ashby
      8 Dave,16,89.0,84,Jones
      9 Fred,15,,88,Jones'''
     10 scores = pd.read_csv(io.StringIO(data), dtype_backend='pyarrow',
     11                     engine='pyarrow'
     12                     )
     15 (scores
     16  .test1
---> 17  .apply(np.log)
     18 )

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/series.py:4760, in Series.apply(self, func, convert_dtype, args, by_row, **kwargs)
   4625 def apply(
   4626     self,
   4627     func: AggFuncType,
   (...)
   4632     **kwargs,
   4633 ) -> DataFrame | Series:
   4634     """
   4635     Invoke function on values of Series.
   4636 
   (...)
   4751     dtype: float64
   4752     """
   4753     return SeriesApply(
   4754         self,
   4755         func,
   4756         convert_dtype=convert_dtype,
   4757         by_row=by_row,
   4758         args=args,
   4759         kwargs=kwargs,
-> 4760     ).apply()

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/apply.py:1207, in SeriesApply.apply(self)
   1204     return self.apply_compat()
   1206 # self.func is Callable
-> 1207 return self.apply_standard()

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/apply.py:1269, in SeriesApply.apply_standard(self)
   1267 if isinstance(func, np.ufunc):
   1268     with np.errstate(all="ignore"):
-> 1269         return func(obj, *self.args, **self.kwargs)
   1270 elif not self.by_row:
   1271     return func(obj, *self.args, **self.kwargs)

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/generic.py:2102, in NDFrame.__array_ufunc__(self, ufunc, method, *inputs, **kwargs)
   2098 @final
   2099 def __array_ufunc__(
   2100     self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any
   2101 ):
-> 2102     return arraylike.array_ufunc(self, ufunc, method, *inputs, **kwargs)

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/arraylike.py:396, in array_ufunc(self, ufunc, method, *inputs, **kwargs)
    393 elif self.ndim == 1:
    394     # ufunc(series, ...)
    395     inputs = tuple(extract_array(x, extract_numpy=True) for x in inputs)
--> 396     result = getattr(ufunc, method)(*inputs, **kwargs)
    397 else:
    398     # ufunc(dataframe)
    399     if method == "__call__" and not kwargs:
    400         # for np.<ufunc>(..) calls
    401         # kwargs cannot necessarily be handled block-by-block, so only
    402         # take this path if there are no kwargs

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/arrays/base.py:2167, in ExtensionArray.__array_ufunc__(self, ufunc, method, *inputs, **kwargs)
   2164     if result is not NotImplemented:
   2165         return result
-> 2167 return arraylike.default_array_ufunc(self, ufunc, method, *inputs, **kwargs)

File ~/.envs/menv/lib/python3.10/site-packages/pandas/core/arraylike.py:489, in default_array_ufunc(self, ufunc, method, *inputs, **kwargs)
    485     raise NotImplementedError
    487 new_inputs = [x if x is not self else np.asarray(x) for x in inputs]
--> 489 return getattr(ufunc, method)(*new_inputs, **kwargs)

TypeError: loop of ufunc does not support argument 0 of type float which has no callable log method

Expected Behavior

If we comment out the dtype_backend it works and gives the desired results.

Installed Versions

INSTALLED VERSIONS

commit : e86ed37
python : 3.10.13.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Wed Aug 10 14:28:23 PDT 2022; root:xnu-8020.141.5~2/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : en_US.UTF-8
LANG : None
LOCALE : en_US.UTF-8

pandas : 2.1.1
numpy : 1.23.5
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.6.1
pip : 23.2.1
Cython : 3.0.4
pytest : 7.2.0
hypothesis : 6.81.2
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.1.2
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.8.0
pandas_datareader : None
bs4 : 4.11.1
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.3.0
gcsfs : None
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.0
sqlalchemy : 2.0.21
tables : None
tabulate : 0.9.0
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[rhshadrach]

cc @phofl @jorisvandenbossche - not sure what the expectation should be on using NumPy funcs on pd.NA.

print(np.log([1, np.nan, 3]))
# [0.                nan 1.09861229]

print(np.log([1, pd.NA, 3]))
# raises

[phofl]

The masked array case should work since today,

the culprit here is that we convert to object in numpy, we merged a pr today that fixes this for masked, arrow to follow