BUG: DataFrame.assign accepts 2d arrays for single column value

[determ1ne]

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 sys
import pandas as pd
import numpy as np
from numpy import dtype

print('python version: ', sys.version)
print('pandas version: ', pd.__version__)

data_dtype = [('name', dtype(object)), ('value', 'f8'), ('value2', dtype(object)),]
table = pd.DataFrame(np.zeros(0, dtype=data_dtype), index=pd.Index([], dtype=np.int64))
dtypes = table.dtypes
index = np.arange(10, dtype=np.int32)

data_dict = {'value2': np.ones(10, dtype=float), 'value': np.zeros(10, dtype=float),
             'name': np.array([np.arange(13) + x for x in range(10)], dtype=float)}

dd = pd.DataFrame(index=index, columns=table.columns)
dd = dd.assign(**data_dict)
print('**** Original ****')
print(dd.head())
print('**** Bad Copy ****')
print(dd.copy().head())

print('**** 1D ndarray ****')
data_dict['name'] = data_dict['name'][:, 0]
dd = pd.DataFrame(index=index, columns=table.columns)
dd = dd.assign(**data_dict)
print(dd.copy().head())

'''
Program output:
python version:  3.8.16 | packaged by conda-forge | (default, Feb  1 2023, 15:53:35) [MSC v.1929 64 bit (AMD64)]
pandas version:  0+untagged.1.g6169cba
**** Original ****
   name  value  value2
0   0.0    0.0     1.0
1   1.0    0.0     1.0
2   2.0    0.0     1.0
3   3.0    0.0     1.0
4   4.0    0.0     1.0
**** Bad Copy ****
   name  value  value2
0   0.0    2.0     1.0
1   1.0    3.0     2.0
2   2.0    4.0     3.0
3   3.0    5.0     4.0
4   4.0    6.0     5.0
**** 1D ndarray ****
   name  value  value2
0   0.0    0.0     1.0
1   1.0    0.0     1.0
2   2.0    0.0     1.0
3   3.0    0.0     1.0
4   4.0    0.0     1.0
'''

Issue Description

The name Series was assigned using a 2D ndarray, and it works fine. But a DataFrame.copy makes name overwrite value and value2 in the new df. An 1D ndarray will not break the normal behavior.

Expected Behavior

**** Original ****
   name  value  value2
0   0.0    0.0     1.0
1   1.0    0.0     1.0
2   2.0    0.0     1.0
3   3.0    0.0     1.0
4   4.0    0.0     1.0
**** Bad Copy ****
   name  value  value2
0   0.0    0.0     1.0
1   1.0    0.0     1.0
2   2.0    0.0     1.0
3   3.0    0.0     1.0
4   4.0    0.0     1.0
**** 1D ndarray ****
   name  value  value2
0   0.0    0.0     1.0
1   1.0    0.0     1.0
2   2.0    0.0     1.0
3   3.0    0.0     1.0
4   4.0    0.0     1.0

Installed Versions

Fresh install of development environment following pandas doc gave an error from numba, here's another report:

INSTALLED VERSIONS

commit : 2e218d1
python : 3.8.16.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Chinese (Simplified)_China.936
pandas : 1.5.3
numpy : 1.22.0
pytz : 2022.7
dateutil : 2.8.2
setuptools : 65.6.3
pip : 22.3.1
Cython : None
pytest : 7.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.9
lxml.etree : None
html5lib : None
pymysql : 1.0.2
psycopg2 : 2.9.5
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : 1.3.5
brotli :
fastparquet : None
fsspec : 2023.1.0
gcsfs : None
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.0
snappy : None
sqlalchemy : None
tables : 3.7.0
tabulate : None
xarray : 2023.1.0
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[MuhammadNizamani]

If you do it this way it works fine
print('**** Bad Copy ****') cc = dd.copy().head() print(cc)

[determ1ne]

If you do it this way it works fine print('**** Bad Copy ****') cc = dd.copy().head() print(cc)

It doesn't work, and the issue seems to be Windows-specific. Are you trying to use macOS or Linux to reproduce this problem?

[ziyue-pan]

Reproducible on my win10 ltsc machine.

[MuhammadNizamani]

I am using windows 11

[determ1ne]

I am using windows 11

Could you please try again in a fresh environment from https://github.com/pandas-dev/pandas/blob/main/environment.yml and attach your pd.show_versions() result?

[MuhammadNizamani]

I checked it today and now it's showing me the same result as yours, there is some bug.

[topper-123]

Thanks for the report, @determ1ne.

I can confirm this problem using MacOS. data_dict["name"] is a 2d array, so the call to assign should def have failed, similarly to it would failed when instantiating a dataframe from the dict:

>>> pd.DataFrame(data_dict)
ValueError: Per-column arrays must each be 1-dimensional

So there is some checks in assign that needs to be tightened. A PR would be appreciated.