ValueError in Dataframe Evaluation: Missing Required Columns

ValueError                                Traceback (most recent call last)
Cell In[45], line 24
     12 hallucination_eval_df, qa_correctness_eval_df = run_evals(
     13     dataframe=queries_df,
     14     evaluators=[hallucination_evaluator, qa_correctness_evaluator],
     15     provide_explanation=True,
     16 )
     17 relevance_eval_df = run_evals(
     18     dataframe=retrieved_documents_df,
     19     evaluators=[relevance_evaluator],
     20     provide_explanation=True,
     21 )[0]
     23 px.Client().log_evaluations(
---> 24     SpanEvaluations(eval_name="Hallucination", dataframe=hallucination_eval_df),
     25     SpanEvaluations(eval_name="QA Correctness", dataframe=qa_correctness_eval_df),
     26     DocumentEvaluations(eval_name="Relevance", dataframe=relevance_eval_df),
     27 )

File <string>:6, in __init__(self, eval_name, dataframe)

File C:\.venvs\openai_venv\lib\site-packages\phoenix\trace\span_evaluations.py:117, in Evaluations.__post_init__(self)
    115 def __post_init__(self) -> None:
    116     dataframe = (
--> 117         pd.DataFrame() if self.dataframe.empty else self._clean_dataframe(self.dataframe)
    118     )
    119     object.__setattr__(self, "dataframe", dataframe)

File C:\.venvs\openai_venv\lib\site-packages\phoenix\trace\span_evaluations.py:141, in Evaluations._clean_dataframe(self, dataframe)
    139 # Validate that the dataframe contains result columns of appropriate types.
    140 if not self.is_valid_result_columns(dataframe.dtypes):
--> 141     raise ValueError(
    142         f"The dataframe must contain one of these columns with appropriate "
    143         f"value types: {self.result_column_names.keys()} "
    144     )
    146 # Un-alias to the preferred names.
    147 preferred_names = [self.unalias(name) for name in dataframe.index.names]

ValueError: The dataframe must contain one of these columns with appropriate value types: dict_keys(['score', 'label', 'explanation'])