BUG: strings fails to convert to nullable Integer dtype in dataframe/series

[scotscotmcc]

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
df = pd.DataFrame({'a':[123,'123']})
df["a"].astype("Int64")

output:

Traceback (most recent call last):
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\arrays\integer.py", line 53, in _safe_cast
    return values.astype(dtype, casting="safe", copy=copy)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'

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

Traceback (most recent call last):
  File "c:\Users\MCCULSXCQY\Scripts\Python\test_pd\test.py", line 4, in <module>
    df["a"].astype("Int64")
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\generic.py", line 6643, in astype
    new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\internals\managers.py", line 430, in astype
    return self.apply(
           ^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\internals\managers.py", line 363, in apply
    applied = getattr(b, f)(**kwargs)
              ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\internals\blocks.py", line 758, in astype
    new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\dtypes\astype.py", line 237, in astype_array_safe
    new_values = astype_array(values, dtype, copy=copy)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\dtypes\astype.py", line 182, in astype_array
    values = _astype_nansafe(values, dtype, copy=copy)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\dtypes\astype.py", line 80, in _astype_nansafe
    return dtype.construct_array_type()._from_sequence(arr, dtype=dtype, copy=copy)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\arrays\masked.py", line 152, in _from_sequence
    values, mask = cls._coerce_to_array(scalars, dtype=dtype, copy=copy)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\arrays\numeric.py", line 272, in _coerce_to_array
    values, mask, _, _ = _coerce_to_data_and_mask(
                         ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\arrays\numeric.py", line 229, in _coerce_to_data_and_mask
    values = dtype_cls._safe_cast(values, dtype, copy=False)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\MCCULSXCQY\Scripts\Python\test_pd\.venv\Lib\site-packages\pandas\core\arrays\integer.py", line 59, in _safe_cast
    raise TypeError(
TypeError: cannot safely cast non-equivalent object to int64

Issue Description

In the example, we get TypeError: cannot safely cast non-equivalent object to int64.

However, if in the example we do df["a"].astype("int64") (lowercase int), we get no error and things seem to work just fine

Expected Behavior

I expect converting to Int64 to work the same, as it relates to strings, as int64. That is, I expect the example to give:

>>> import pandas as pd
>>> df = pd.DataFrame({'a':[123,'123']})
>>> df["a"].astype("Int64")
0    123
1    123
Name: a, dtype: Int64

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.12.1.final.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 154 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252

pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : None
pip : 24.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[Aloqeely]

Thanks for the report! This is a duplicate of #34460, but feel free to submit a PR to fix this

[mroeschke]

Closing as a duplicate of #34460