Add statistics for some scales.
parent
40170339c2
commit
96bbe32f56
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@ -32,7 +32,7 @@ from features.esm_SAM import extract_stressful_events
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# %%
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save_figs = True
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save_figs = False
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# %%
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participants_inactive_usernames = participants.query_db.get_usernames(
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@ -79,6 +79,15 @@ df_esm_PANAS_summary_participant[
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{8.0: "positive affect", 9.0: "negative affect"}
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)
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# %%
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df_esm_PANAS_summary_participant.groupby("PANAS subscale").describe()["mean"]
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# %%
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df_esm_PANAS_summary_participant.groupby("PANAS subscale").describe()["std"]
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# %%
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df_esm_PANAS_summary_participant.query("std == 0")
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# %%
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fig1 = sns.displot(
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data=df_esm_PANAS_summary_participant, x="mean", hue="PANAS subscale", binwidth=0.2
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@ -193,6 +202,20 @@ df_esm_SAM_summary_participant = (
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.reset_index(col_level=1)
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)
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# %%
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df_esm_SAM_event_stressfulness_summary_participant = df_esm_SAM_summary_participant[
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df_esm_SAM_summary_participant["questionnaire_id"] == 87
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]
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df_esm_SAM_event_stressfulness_summary_participant.describe()["mean"]
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# %%
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df_esm_SAM_event_stressfulness_summary_participant.describe()["std"]
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# %%
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sns.displot(
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data=df_esm_SAM_event_stressfulness_summary_participant, x="mean", binwidth=0.2
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)
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# %%
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df_esm_SAM_threat_challenge_summary_participant = df_esm_SAM_summary_participant[
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(df_esm_SAM_summary_participant["questionnaire_id"] == 88)
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@ -225,6 +248,16 @@ fig3.set_axis_labels(x_var="participant standard deviation", y_var="frequency")
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if save_figs:
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fig3.figure.savefig("SAM_std_participant.pdf", dpi=300)
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# %%
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df_esm_SAM_threat_challenge_summary_participant.groupby("event subscale").describe()[
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"mean"
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]
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# %%
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df_esm_SAM_threat_challenge_summary_participant.groupby("event subscale").describe()[
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"std"
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]
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# %% [markdown]
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# ## Stressfulness of period
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@ -233,6 +266,12 @@ df_esm_SAM_period_summary_participant = df_esm_SAM_summary_participant[
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df_esm_SAM_summary_participant["questionnaire_id"] == 93
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]
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# %%
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df_esm_SAM_period_summary_participant.describe()["mean"]
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# %%
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df_esm_SAM_period_summary_participant.describe()["std"]
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# %%
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sns.displot(data=df_esm_SAM_period_summary_participant, x="mean", binwidth=0.2)
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@ -276,6 +315,12 @@ df_esm_JCQ_summary_participant[
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{10: "job demand", 11: "job control"}
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)
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# %%
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df_esm_JCQ_summary_participant.groupby("JCQ subscale").describe()["mean"]
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# %%
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df_esm_JCQ_summary_participant.groupby("JCQ subscale").describe()["std"]
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# %%
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fig4 = sns.displot(
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data=df_esm_JCQ_summary_participant,
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