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BUG: eval fails for ExtensionArray

Open mutricyl opened this issue 1 year ago • 2 comments

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  • [X] I have checked that this issue has not already been reported.

  • [X] I have confirmed this bug exists on the latest version of pandas.

  • [X] I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame({'a': pd.array([1, 2, 3]), 'b': pd.array([4, 5, 6])})

# this works as expected
print(df['a'] / df['b'])
"""
0    0.25
1     0.4
2     0.5
dtype: Float64
"""

# this is not working
print(df.eval('a / b'))
"""
TypeError: Cannot interpret 'Int64Dtype()' as a data type
"""

Issue Description

This issue is coming from pint-pandas#137. ExtensionArray is used for this project and df.eval inlcuding division (\) fails with TypeError.

I was able to able to reproduce the pint-pandas issue with pandas build in IntegerArray as shown in the above example

Traceback (most recent call last):
  File "c:\CALC\DEV\pint pandas debug\test.py", line 17, in <module>
    print(df.eval('a / b'))
          ^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\frame.py", line 4738, in eval
    return _eval(expr, inplace=inplace, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\eval.py", line 340, in eval
    parsed_expr = Expr(expr, engine=engine, parser=parser, env=env)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 809, in __init__
    self.terms = self.parse()
                 ^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 828, in parse
    return self._visitor.visit(self.expr)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 413, in visit
    return visitor(node, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 419, in visit_Module
    return self.visit(expr, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 413, in visit
    return visitor(node, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 422, in visit_Expr
    return self.visit(node.value, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 413, in visit
    return visitor(node, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 535, in visit_BinOp
    return self._maybe_evaluate_binop(op, op_class, left, right)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 502, in _maybe_evaluate_binop
    res = op(lhs, rhs)
          ^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\expr.py", line 538, in <lambda>
    return lambda lhs, rhs: Div(lhs, rhs)
                            ^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\ops.py", line 528, in __init__
    if not isnumeric(lhs.return_type) or not isnumeric(rhs.return_type):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\laurent.mutricy\AppData\Local\miniconda3\Lib\site-packages\pandas\core\computation\ops.py", line 512, in isnumeric
    return issubclass(np.dtype(dtype).type, np.number)
                      ^^^^^^^^^^^^^^^
TypeError: Cannot interpret 'Int64Dtype()' as a data type

Looking at the traceback it seams that pandas\core\computation\ops.isnumeric() does not handle properly dtypes from ExtensionArray class (or subclass). It was suggested to consider _is_numeric class attribute.

def isnumeric(dtype) -> bool:
-    return issubclass(np.dtype(dtype).type, np.number)
+   return getattr(dtype, '_is_numeric', False) or issubclass(np.dtype(dtype).type, np.number)

probably linked to #21374

Expected Behavior

df.eval('a / b') should give the same result than df['a'] / df['b']

Installed Versions

INSTALLED VERSIONS

commit : 4fb94bb09abbfcae536744740b00c987a04eed23 python : 3.11.4.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19045 machine : AMD64 processor : Intel64 Family 6 Model 186 Stepping 2, GenuineIntel byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : fr_FR.cp1252

pandas : 3.0.0.dev0+983.g4fb94bb09a numpy : 1.26.4 pytz : 2024.1 dateutil : 2.8.2 setuptools : 67.8.0 pip : 23.1.2 Cython : None pytest : 8.2.0 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : None pandas_datareader : None adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : None bottleneck : None fastparquet : None fsspec : None gcsfs : None matplotlib : 3.8.3 numba : None numexpr : 2.10.0 odfpy : None openpyxl : 3.1.2 pyarrow : 15.0.0 pyreadstat : None python-calamine : None pyxlsb : None s3fs : None scipy : 1.12.0 sqlalchemy : None tables : None tabulate : 0.9.0 xarray : 2024.2.0 xlrd : None zstandard : 0.19.0 tzdata : 2023.3 qtpy : None pyqt5 : None

mutricyl avatar May 17 '24 09:05 mutricyl

Thanks for the report! Further investigations and PRs to fix are welcome.

rhshadrach avatar May 19 '24 18:05 rhshadrach

Hey @mutricyl @rhshadrach , thank you for mentioning the issue properly and in detailed manner. I have looked into it and have issued a PR as well, do check if any issues in the PR let me know I will work on it, Thanks once again. Cheers

SiddheshBangar avatar May 19 '24 23:05 SiddheshBangar