Description
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
# works
foo = np.array([1,2,3,4]).reshape(2,2)
bar = np.zeros_like(foo)
np.add(foo, 1, out=bar)
print(bar)
# doesn't work. bar remains an array of zeros
foo = np.array([1,2,3,4]).reshape(2,2)
df = pd.DataFrame(foo)
bar = np.zeros_like(df)
np.add(df, 1, out=bar)
print(bar)Problem description
Many numpy functions accept an out parameter as a way of storing the result. In the current pandas version (1.2.3), when the numpy function takes in a DataFrame as input, it no longer stores the result to the out array.
In pandas 1.0.1 (and earlier, on my other machine), the behavior works as expected. (see Expected Output). I am using numpy==1.19 for both machines.
Curiously, note that this problem is not seen for pd.Series. The below code works fine:
foo = np.array([1,2,3,4])
series = pd.Series(foo)
bar = np.zeros_like(series)
np.add(series, 1, out=bar)
print(bar)One workaround is to instead use np.add(df.values, 1, out=bar) but I am using several packages that require the older behavior.
Expected Output
>>> print(bar)
[[2 3]
[4 5]]Output of pd.show_versions()
INSTALLED VERSIONS
commit : f2c8480
python : 3.7.4.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1062.1.1.el7.x86_64
Version : #1 SMP Fri Sep 13 22:55:44 UTC 2019
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.2.3
numpy : 1.19.5
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.4.0
Cython : 0.29.21
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.8.2
fastparquet : None
gcsfs : None
matplotlib : 3.1.3
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.13.0
pyxlsb : None
s3fs : 0.5.1
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : 0.8.7
xarray : None
xlrd : 1.2.0
xlwt : None
numba : 0.49.1