REGR: DataFrame.to_numpy(dtype=str) raises RuntimeError in pandas 1.1.0 · Issue #35455 · pandas-dev/pandas (original) (raw)

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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 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