BUG: DataFrame eval will not work with 'Timestamp' column name · Issue #44603 · pandas-dev/pandas (original) (raw)

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas.
• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

import pandas as pd import numpy as np df = pd.DataFrame(np.random.randint(0,100, size=(3000, 2)), columns=['Timestamp', 'col1']) df.eval('Timestamp>6')

Traceback (most recent call last): File "", line 1, in File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\frame.py", line 4191, in eval return _eval(expr, inplace=inplace, **kwargs) File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\computation\eval.py", line 353, in eval ret = eng_inst.evaluate() File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\computation\engines.py", line 80, in evaluate res = self._evaluate() File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\computation\engines.py", line 121, in _evaluate return ne.evaluate(s, local_dict=scope) File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\numexpr\necompiler.py", line 821, in evaluate signature = [(name, getType(arg)) for (name, arg) in File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\numexpr\necompiler.py", line 821, in signature = [(name, getType(arg)) for (name, arg) in File "C:\Users<>\AppData\Local\Programs\Python\Python38\lib\site-packages\numexpr\necompiler.py", line 703, in getType raise ValueError("unknown type %s" % a.dtype.name) ValueError: unknown type object

Issue Description

If 'Timestamp' exists as a column name, and a dataframe eval is performed which includes that column, a ValueError occurs.

Expected Behavior

The expeected behaviour should be that of the same output when applied on the other column that is provided in the example:

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,100, size=(3000, 2)), columns=['Timestamp', 'col1'])
df.eval('col1>6')

output:

0        True
1        True
2        True
3        True
4        True
        ...
2995    False
2996     True
2997     True
2998     True
2999     True
Length: 3000, dtype: bool

Installed Versions

INSTALLED VERSIONS ------------------ commit : 945c9edpython : 3.8.1.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United Kingdom.1252

pandas : 1.3.4
numpy : 1.21.2
pytz : 2020.1
dateutil : 2.8.1
pip : 21.3.1
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.15.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.7.4
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.49.1