Closed
Description
Code Sample
import sys
import pandas
import numpy
print("# sys.version: " + sys.version)
print("# pandas.__version__: " + pandas.__version__)
print("# numpy.__version__: " + numpy.__version__)
d = pandas.DataFrame({
"a": [True, False],
"b": [1, 2],
"c": [3, 4]})
pandas_eval_env = {
"if_else": lambda c, x, y: numpy.where(c, x, y),
}
d.eval("@if_else(a, 1, c)", local_dict=pandas_eval_env, global_dict=None)Problem description
For Python 3.6 the above code runs. For Python 3.7 it errors-out with "TypeError: unhashable type: 'numpy.ndarray'". If I am returning the wrong type (an array instead of a named series or dataframe) I apologize.
Expected Output
For Python 3.6 we get what I expected:
array([1, 4])
For Python 3.7 0.25.1 pandas we get the following:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py", line 3300, in eval
return _eval(expr, inplace=inplace, **kwargs)
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/computation/eval.py", line 327, in eval
ret = eng_inst.evaluate()
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 70, in evaluate
res = self._evaluate()
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 118, in _evaluate
_check_ne_builtin_clash(self.expr)
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 27, in _check_ne_builtin_clash
names = expr.names
File "/Users/johnmount/opt/anaconda3/lib/python3.7/site-packages/pandas/core/computation/expr.py", line 850, in names
return frozenset([self.terms.name])
TypeError: unhashable type: 'numpy.ndarray'
Note: both failing and successful runs are using Pandas 0.25.1 and numpy 1.17.2.
Edit: Pandas 0.25.3 with Python 3.7.5, numpy 1.17.3 works fine. My question then is: is there a work around for when we are using Pandas 0.25.1?
Output of pd.show_versions()
Working version:
sys.version: 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019, 13:42:17)
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
pandas.__version__:0.25.1
numpy.__version__: 1.17.2
Out[4]: array([1, 4])
pandas.show_versions()
INSTALLED VERSIONS
------------------
commit : None
python : 3.6.9.final.0
python-bits : 64
OS : Darwin
OS-release : 17.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.6.0.post20191030
Cython : None
pytest : 5.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
Failing version:
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Darwin
OS-release : 17.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2019.3
dateutil : 2.8.0
pip : 19.2.3
setuptools : 41.4.0
Cython : 0.29.13
pytest : 5.2.1
hypothesis : None
sphinx : 2.2.0
blosc : None
feather : None
xlsxwriter : 1.2.1
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.8.0
pandas_datareader: None
bs4 : 4.8.0
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.3.9
tables : 3.5.2
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.1