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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
df = pd.DataFrame({'max': [1, 2, 3]})
df.query('max == 1', engine='numexpr')
# Empty DataFrame
df.query('max < 2', engine='numexpr')
# TypeError: '<' not supported between instances of 'function' and 'int'
Issue Description
DataFrame.query(engine='numexpr') does not work correctly when column name is 'max' or 'min'.
Because numexpr seems to have 'max' and 'min' as built-in reduction function though it is not officially documented, https://github.com/pydata/numexpr/issues/120
These keywords should be checked in pandas like 'sum' and 'prod'. So REDUCTIONS in pandas/core/computation/ops.py may need to be updated.
Expected Behavior
NumExprClobberingError should be raised.
import pandas as pd
df = pd.DataFrame({'max': [1, 2, 3]})
df.query('max == 1', engine='numexpr')
# NumExprClobberingError: Variables in expression "(max) == (1)" overlap with builtins: ('max')
Installed Versions
INSTALLED VERSIONS
------------------
commit : 2e218d10984e9919f0296931d92ea851c6a6faf5
python : 3.9.16.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Japanese_Japan.932
pandas : 1.5.3
numpy : 1.22.3
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 66.1.1
pip : 22.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.8.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : 0.56.3
numexpr : 2.8.4
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None
Comment From: ShisuiUzumaki
I am interested. Do I need to check whether the passed column is a reduction function and, if so, raise the error?
Comment From: bsdfan
pandas already has a such feature.
_check_ne_builtin_clash() checks whether the column name is reserved. https://github.com/pandas-dev/pandas/blob/main/pandas/core/computation/engines.py#L28-L44
For example, if I use 'sum', 'sin' or 'exp' as column name, this function raise NumExprClobberingError. But 'max' and 'min' pass this check because they are not listed as reduction function. https://github.com/pandas-dev/pandas/blob/main/pandas/core/computation/ops.py#L38
On the latest numexpr document, only 'sum' and 'prod' are reduction operation, but 'max' and 'min' seem to be introduced already. https://numexpr.readthedocs.io/projects/NumExpr3/en/latest/user_guide.html#supported-reduction-operations
Comment From: ShisuiUzumaki
pandas already has a such feature.
_check_ne_builtin_clash() checks whether the column name is reserved. https://github.com/pandas-dev/pandas/blob/main/pandas/core/computation/engines.py#L28-L44
For example, if I use 'sum', 'sin' or 'exp' as column name, this function raise NumExprClobberingError. But 'max' and 'min' pass this check because they are not listed as reduction function. https://github.com/pandas-dev/pandas/blob/main/pandas/core/computation/ops.py#L38
On the latest numexpr document, only 'sum' and 'prod' are reduction operation, but 'max' and 'min' seem to be introduced already. https://numexpr.readthedocs.io/projects/NumExpr3/en/latest/user_guide.html#supported-reduction-operations
So, does that mean we only need to ensure that min and max are recognized as reduction operations?
Comment From: bsdfan
So, does that mean we only need to ensure that min and max are recognized as reduction operations?
Yes.
Comment From: ShisuiUzumaki
So, does that mean we only need to ensure that min and max are recognized as reduction operations?
Yes.
Can you give me some pointer on how to do that?
Comment From: bsdfan
I think this is all.
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -35,7 +35,7 @@ from pandas.io.formats.printing import (
pprint_thing_encoded,
)
-REDUCTIONS = ("sum", "prod")
+REDUCTIONS = ("sum", "prod", "max", "min")
_unary_math_ops = (
"sin",
Comment From: ShisuiUzumaki
I think this is all.
```diff --- a/pandas/core/computation/ops.py +++ b/pandas/core/computation/ops.py @@ -35,7 +35,7 @@ from pandas.io.formats.printing import ( pprint_thing_encoded, )
-REDUCTIONS = ("sum", "prod") +REDUCTIONS = ("sum", "prod", "max", "min")
_unary_math_ops = ( "sin", ```
Do we only need to make these changes in this file?
On a side note, should we add mean, median, var, std, skew, and kurt as well?
Comment From: ShisuiUzumaki
take
Comment From: bsdfan
Thanks for your comment.
According to numexpr source code (https://github.com/pydata/numexpr/blob/62cc05148fd6eb8bb32ed1bbcaf102149da6445e/numexpr/expressions.py#L334-L377), mean, median, var, std, skew, and kurt are not pre-defined functions. So you don't need to add.
Comment From: ShisuiUzumaki
Thanks for your comment.
According to numexpr source code (https://github.com/pydata/numexpr/blob/62cc05148fd6eb8bb32ed1bbcaf102149da6445e/numexpr/expressions.py#L334-L377), mean, median, var, std, skew, and kurt are not pre-defined functions. So you don't need to add.
Ok, got it!