MemoryError when using series.rolling().corr(other) with >1.0 · Issue #31789 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example if possible

srs1 = pd.Series(np.random.rand(11521),pd.date_range('2019-08-15', '2019-08-23',freq='1T')) srs2 = pd.Series(np.random.rand(11521),pd.date_range('2019-08-15', '2019-08-23',freq='1T')) srs1.rolling(pd.to_timedelta("12H")).corr(srs2)

Problem description

Running the code above results in the following error Unable to allocate 314. TiB for an array with shape (43200000000000,) and data type int64 on pandas 1.0.1. Confirmed that this used to work on pandas 0.25.3.

Expected Output

The correct calculations

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Darwin
OS-release : 19.2.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.1.0.post20200127
Cython : 0.29.14
pytest : 5.3.5
hypothesis : 5.4.1
sphinx : 2.3.1
blosc : None
feather : None
xlsxwriter : 1.2.7
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.5.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.13.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : None
xarray : 0.13.0
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.7
numba : 0.48.0