DataFrame.eval errors with AttributeError: 'UnaryOp'

Code Sample, a copy-pastable example if possible

def test_unary():
    df = pd.DataFrame({'x': np.array([0.11, 0], dtype=np.float32)})
    res = df.eval('(x > 0.1) | (x < -0.1)')
    assert np.array_equal(res, np.array([True, False])), res

Problem description

This is related to #11235. on python 3.6, pandas 20.1, this raises an error the traceback ends with:

  File ".../envs/py3/lib/python3.6/site-packages/pandas/core/computation/expr.py", line 370, in _maybe_downcast_constants
    name = self.env.add_tmp(np.float32(right.value))
AttributeError: 'UnaryOp' object has no attribute 'value'

In that case the right is -(0.1)

INSTALLED VERSIONS ------------------ commit: None python: 3.6.1.final.0 python-bits: 64 OS: Linux OS-release: 4.8.0-49-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8

pandas: 0.20.1 pytest: None pip: 9.0.1 setuptools: 27.2.0 Cython: 0.25.2 numpy: 1.12.1 scipy: 0.19.0 xarray: None IPython: 6.0.0 sphinx: None patsy: None dateutil: 2.6.0 pytz: 2017.2 blosc: None bottleneck: None tables: None numexpr: None feather: None matplotlib: 2.0.2 openpyxl: None xlrd: None xlwt: None xlsxwriter: None lxml: None bs4: None html5lib: None sqlalchemy: None pymysql: None psycopg2: None jinja2: None s3fs: None pandas_gbq: None pandas_datareader: None

Another example:

>>> df = pd.DataFrame({'x':[1,2,3,4,5]})
>>> df.eval('x.shift(-1)')

[alexcwatt]

I ran into this recently and would like to help with a patch. As best I can tell, the problem is that _maybe_downcast_constants not only tries to downcast constants but also UnaryOp’s, which isn’t possible, since UnaryOp instances don’t have a value attribute like constants/scalars do.

I am new to the pandas code, and the expressions code is a bit tricky, but I think we could catch the AttributeError in _maybe_downcast_constants or explicitly check in each case that left or right has the attribute value.

In short, the problem is that an operation like df.eval(x < -.1) fails when x is a np.float32 because the right side of the equation is seen as a UnaryOp node instead of as a np.float32 and is subjected to _maybe_downcast_constants by visit_BinOp. OTOH, df.eval(x < @y) works when y = -.1, because pandas doesn’t have to parse it. I think a small change might fix this, but I could be overlooking something bigger and would appreciate feedback.

[ksw9]

Hi, I am wondering if this is resolved? I’m running into a similar issue using pandas df.query() with negative numbers. Thank you!