Calculate daily means instead of sums.
parent
5362f64941
commit
3bb66e3838
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@ -44,24 +44,24 @@ df_esm_PANAS = df_esm_preprocessed[
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]
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df_esm_PANAS_clean = clean_up_esm(df_esm_PANAS)
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# %%
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df_esm_PANAS_grouped = df_esm_PANAS_clean.groupby(
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["participant_id", "date_lj", "questionnaire_id"]
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)
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# %% [markdown]
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# Group by participants, date, and subscale and calculate daily means.
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# %%
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df_esm_PANAS_daily_sums = (
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df_esm_PANAS_grouped.esm_user_answer_numeric.agg("sum")
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df_esm_PANAS_daily_means = (
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df_esm_PANAS_clean.groupby(
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["participant_id", "date_lj", "questionnaire_id"])
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.esm_user_answer_numeric.agg("mean")
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.reset_index()
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.rename(columns={"esm_user_answer_numeric": "esm_numeric_sum"})
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.rename(columns={"esm_user_answer_numeric": "esm_numeric_mean"})
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)
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# %% [markdown]
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# Group by participants, date, and subscale and calculate daily sums.
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# Next, calculate mean, median, and standard deviation across all days for each participant.
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# %%
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df_esm_PANAS_summary_participant = (
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df_esm_PANAS_daily_sums.groupby(["participant_id", "questionnaire_id"])
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df_esm_PANAS_daily_means.groupby(["participant_id", "questionnaire_id"])
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.agg(["mean", "median", "std"])
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.reset_index(col_level=1)
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)
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@ -70,19 +70,24 @@ df_esm_PANAS_summary_participant.columns = df_esm_PANAS_summary_participant.colu
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)
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df_esm_PANAS_summary_participant[
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"PANAS_subscale"
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] = df_esm_PANAS_daily_sums.questionnaire_id.astype("category").cat.rename_categories(
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] = df_esm_PANAS_daily_means.questionnaire_id.astype("category").cat.rename_categories(
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{8.0: "PA", 9.0: "NA"}
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)
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# %% [markdown]
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# Next, calculate mean and standard deviation across all days for each participant.
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# %%
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sns.displot(
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data=df_esm_PANAS_summary_participant, x="mean", hue="PANAS_subscale", binwidth=2
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data=df_esm_PANAS_summary_participant, x="mean", hue="PANAS_subscale", binwidth=0.2
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)
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# %%
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sns.displot(
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data=df_esm_PANAS_summary_participant, x="std", hue="PANAS_subscale", binwidth=1
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data=df_esm_PANAS_summary_participant, x="median", hue="PANAS_subscale", binwidth=0.2
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)
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# %%
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sns.displot(
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data=df_esm_PANAS_summary_participant, x="std", hue="PANAS_subscale", binwidth=0.05
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)
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# %%
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df_esm_PANAS_summary_participant[df_esm_PANAS_summary_participant["std"] < 0.1]
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@ -242,8 +242,8 @@ df_session_workday[df_session_workday.time_diff_minutes < 30]
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# %%
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df_esm_preprocessed.loc[
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(df_esm_preprocessed.participant_id == 35) & (df_esm_preprocessed.esm_session == 6),
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["esm_trigger", "esm_session", "datetime_lj", "esm_instructions"],
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(df_esm_preprocessed.participant_id == 35) & (df_esm_preprocessed.esm_session == 7) & (df_esm_preprocessed.device_id == "62a44038-3ccb-401e-a69c-6f22152c54a6"),
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["esm_trigger", "esm_session", "datetime_lj", "esm_instructions", "device_id", "_id"],
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]
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# %%
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