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
def expanding_multiply(values, x):
arr = values[-1]
arr[1] = values[:,0].sum() * x
return arr
df = pd.DataFrame({'id': [1, 2, 3], 'value': [0, 0, 0]})
def call_expanding(x):
expanded = df.expanding(method="table").apply(expanding_multiply, raw=True, engine="numba", args=x)
return expanded
call_expanding(tuple([1]))
# 1.0 1.0
# 2.0 3.0
# 3.0 6.0call_expanding(tuple([2]))
# 1.0 1.0
# 2.0 3.0
# 3.0 6.0Problem description
When using expanding.apply with engine='numba' calling the same function with different arguments gives the same results as the first time it was called. I believe this is because the function is being cached with its arguments.
pandas/pandas/core/window/rolling.py
Lines 1172 to 1175 in e8dbdb0
Expected Output
call_expanding(tuple([2]))
# 1.0 2.0
# 2.0 6.0
# 3.0 12.0Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2dd9e9b
python : 3.7.7.final.0
python-bits : 64
OS : Darwin
OS-release : 19.5.0
Version : Darwin Kernel Version 19.5.0: Thu Apr 30 18:25:59 PDT 2020; root:xnu-6153.121.1~7/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.0rc1
numpy : 1.19.1
pytz : 2019.1
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 : 4.6.3
html5lib : None
pymysql : None
psycopg2 : 2.8.2 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.1