BUG: 'Series' objects are mutable, thus they cannot be hashed

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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

# Your code here
df = pd.DataFrame({"id":[0, 1, 2], "name":["a", None, None]})
df.query("name.isnull()")

# output:
TypeError: 'Series' objects are mutable, thus they cannot be hashed

Problem description

i’m so sad about this error, cause i do this ‘query’ method a lot of times. But today, this error happend suddenly, i really don’t know what happend with my mac. i just installed mars library which relative with pandas, and nothing else. please help me for this problem, so appreciate！！

Expected Output

id name 1 1 None 2 2 None

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None python : 3.7.6.final.0 python-bits : 64 OS : Darwin OS-release : 19.4.0 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : zh_CN.UTF-8 LOCALE : zh_CN.UTF-8

pandas : 1.0.3 numpy : 1.18.1 pytz : 2019.3 dateutil : 2.8.1 pip : 20.1 setuptools : 46.1.3 Cython : None pytest : 5.0.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.5.0 html5lib : None pymysql : 0.9.3 psycopg2 : None jinja2 : 2.10.1 IPython : 7.13.0 pandas_datareader: None bs4 : None bottleneck : None fastparquet : None gcsfs : None lxml.etree : 4.5.0 matplotlib : 3.1.2 numexpr : 2.7.1 odfpy : None openpyxl : 3.0.0 pandas_gbq : None pyarrow : 0.17.0 pytables : None pytest : 5.0.1 pyxlsb : None s3fs : None scipy : 1.4.1 sqlalchemy : 1.3.13 tables : None tabulate : 0.8.7 xarray : None xlrd : 1.2.0 xlwt : None xlsxwriter : None numba : 0.48.0

[TypeError: ‘Series’ objects are mutable, thus they cannot be hashed]

[JohannHansing]

For the poeple wondering why this bug appears for them and not for others (or vice versa):

If you do not have the numexpr package installed, then python will be automatically used as engine. Thus, you do not need to specify engine='python' in the query method.

Consequently, one quick fix would be to uninstall the numexpr package. This may introduce other issues for you but it worked for me as I didn’t really use numexpr for anything.

[swigicat]

Is there any update on fixing this? Running queries on text data is a very common use-case.

For my case, I want to make a contains query and got this problem immediately. Found out that one needs to specify the NaN handling inside the query as well, otherwise the python engine complains about it. E.g. for a table containing NaNs the two commands below should have the same output –

df = pd.read_csv('test.csv', dtype=str, na_values='')
print(df[df['Column_A'].str.contains('abc', na=False)])
print(df.query("Column_A.str.contains('abc', na=False)", engine='python'))