Document functions.
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@ -128,6 +128,25 @@ DICT_COPE_QUESTION_IDS = {
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def reassign_question_ids(df_cope_cleaned: pd.DataFrame) -> pd.DataFrame:
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"""
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Fix question IDs to match their actual content.
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Unfortunately, when altering the protocol to adapt to COVID pandemic,
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we did not retain original question IDs.
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This means that for participants before 2021, they are different
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from for the rest of them.
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This function searches for question IDs by matching their strings.
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Parameters
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----------
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df_cope_cleaned: pd.DataFrame
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A cleaned up dataframe, which must also include esm_user_answer_numeric.
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Returns
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-------
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df_cope_fixed: pd.DataFrame
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The same dataframe but with fixed question IDs.
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"""
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df_esm_cope_unique_questions = (
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df_cope_cleaned.groupby("question_id")
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.esm_instructions.value_counts()
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@ -447,6 +447,25 @@ def extract_event_duration(df_esm_sam_clean: pd.DataFrame) -> pd.DataFrame:
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def reassign_question_ids(df_sam_cleaned: pd.DataFrame) -> pd.DataFrame:
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"""
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Fix question IDs to match their actual content.
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Unfortunately, when altering the protocol to adapt to COVID pandemic,
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we did not retain original question IDs.
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This means that for participants before 2021, they are different
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from for the rest of them.
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This function searches for question IDs by matching their strings.
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Parameters
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----------
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df_sam_cleaned: pd.DataFrame
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A cleaned up dataframe, which must also include esm_user_answer_numeric.
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Returns
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-------
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df_sam_fixed: pd.DataFrame
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The same dataframe but with fixed question IDs.
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"""
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df_esm_sam_unique_questions = (
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df_sam_cleaned.groupby("question_id")
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.esm_instructions.value_counts()
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