REGR: DataFrame.to_numpy(dtype=str) raises RuntimeError in pandas 1.1.0

[aciba90]

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

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

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

import pandas as pd

df = pd.DataFrame(data=[[pd.Timestamp('2011-07-03 00:00:00'), 6628480.0]])
print(df.to_numpy(dtype=str))

Problem description

I try to convert the DataFrame to a Numpy array with dtype equal to str and I got the next error.

Traceback (most recent call last):
  File "/main.py", line 4, in <module>
    df.to_numpy(dtype=str)
  File "/venv/lib/python3.7/site-packages/pandas/core/frame.py", line 1371, in to_numpy
    transpose=self._AXIS_REVERSED, dtype=dtype, copy=copy, na_value=na_value
  File "/venv/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 826, in as_array
    arr = self._interleave(dtype=dtype, na_value=na_value)
  File "/venv/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 864, in _interleave
    result[rl.indexer] = arr
RuntimeError: The string provided for NumPy ISO datetime formatting was too short, with length 1

Expected Output

[['2011-07-03 00:00:00' '6628480.0']]

Output of pd.show_versions()

INSTALLED VERSIONS

commit : d9fff27
python : 3.7.6.final.0
python-bits : 64
OS : Linux
OS-release : 4.19.104-microsoft-standard
Version : #1 SMP Wed Feb 19 06:37:35 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.0
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 19.2.3
setuptools : 41.2.0
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
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[simonjayhawkins]

Thanks @aciba90 for the report. This is a regression from 1.0.5

>>> pd.__version__
'1.0.5'
>>>
>>> import pandas as pd
>>>
>>> df = pd.DataFrame(data=[[pd.Timestamp('2011-07-03 00:00:00'), 6628480.0]])
>>> print(df.to_numpy(dtype=str))
[['2011-07-03 00:00:00' '6628480.0']]

[simonjayhawkins]

This is a regression from 1.0.5

it appears #33857 is the cause of this regression

4bd6905 is the first bad commit
commit 4bd6905
Author: Daniel Saxton 2658661+dsaxton@users.noreply.github.com
Date: Wed May 13 10:51:28 2020 -0500

ENH: Add na_value argument to DataFrame.to_numpy (#33857)

cc @dsaxton

[simonjayhawkins]

fixed in #35473