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~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/eval.py in eval(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)
345 eng = ENGINES[engine]
346 eng_inst = eng(parsed_expr)
--> 347 ret = eng_inst.evaluate()
348
349 if parsed_expr.assigner is None:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/engines.py in evaluate(self)
71
72 # make sure no names in resolvers and locals/globals clash
---> 73 res = self._evaluate()
74 return reconstruct_object(
75 self.result_type, res, self.aligned_axes, self.expr.terms.return_type
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/expr.py in names(self)
823 """
824 if is_term(self.terms):
--> 825 return frozenset([self.terms.name])
826 return frozenset(term.name for term in com.flatten(self.terms))
827
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py in hash(self)
1783
1784 def hash(self) -> int:
-> 1785 raise TypeError(
1786 f"{repr(type(self).name)} objects are mutable, "
1787 f"thus they cannot be hashed"
TypeError: 'Series' objects are mutable, thus they cannot be hashed
The text was updated successfully, but these errors were encountered:
When run benchmark.ipynb, got the following error:
TypeError Traceback (most recent call last)
in
8 pool = mp.Pool(processes=n_process)
9
---> 10 df_splitted = [df.query('u_id.isin(@users_subset)') for users_subset in np.array_split(users, n_process)]
11
12 results = [
in (.0)
8 pool = mp.Pool(processes=n_process)
9
---> 10 df_splitted = [df.query('u_id.isin(@users_subset)') for users_subset in np.array_split(users, n_process)]
11
12 results = [
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in query(self, expr, inplace, **kwargs)
3467 kwargs["level"] = kwargs.pop("level", 0) + 1
3468 kwargs["target"] = None
-> 3469 res = self.eval(expr, **kwargs)
3470
3471 try:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in eval(self, expr, inplace, **kwargs)
3597 kwargs["resolvers"] = kwargs.get("resolvers", ()) + tuple(resolvers)
3598
-> 3599 return _eval(expr, inplace=inplace, **kwargs)
3600
3601 def select_dtypes(self, include=None, exclude=None) -> DataFrame:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/eval.py in eval(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)
345 eng = ENGINES[engine]
346 eng_inst = eng(parsed_expr)
--> 347 ret = eng_inst.evaluate()
348
349 if parsed_expr.assigner is None:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/engines.py in evaluate(self)
71
72 # make sure no names in resolvers and locals/globals clash
---> 73 res = self._evaluate()
74 return reconstruct_object(
75 self.result_type, res, self.aligned_axes, self.expr.terms.return_type
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/engines.py in _evaluate(self)
111 env = self.expr.env
112 scope = env.full_scope
--> 113 _check_ne_builtin_clash(self.expr)
114 return ne.evaluate(s, local_dict=scope)
115
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/engines.py in _check_ne_builtin_clash(expr)
27 Terms can contain
28 """
---> 29 names = expr.names
30 overlap = names & _ne_builtins
31
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/computation/expr.py in names(self)
823 """
824 if is_term(self.terms):
--> 825 return frozenset([self.terms.name])
826 return frozenset(term.name for term in com.flatten(self.terms))
827
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py in hash(self)
1783
1784 def hash(self) -> int:
-> 1785 raise TypeError(
1786 f"{repr(type(self).name)} objects are mutable, "
1787 f"thus they cannot be hashed"
TypeError: 'Series' objects are mutable, thus they cannot be hashed
The text was updated successfully, but these errors were encountered: