Label plot axes.
parent
0409c9e982
commit
2c5a0b4157
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@ -74,15 +74,16 @@ df_esm_PANAS_summary_participant = (
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.reset_index(col_level=1)
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)
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df_esm_PANAS_summary_participant[
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"PANAS_subscale"
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"PANAS subscale"
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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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{8.0: "positive affect", 9.0: "negative affect"}
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)
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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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data=df_esm_PANAS_summary_participant, x="mean", hue="PANAS subscale", binwidth=0.2
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)
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fig1.set_axis_labels(x_var="participant mean", y_var="frequency")
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if save_figs:
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fig1.figure.savefig("PANAS_mean_participant.pdf", dpi=300)
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@ -90,14 +91,15 @@ if save_figs:
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sns.displot(
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data=df_esm_PANAS_summary_participant,
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x="median",
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hue="PANAS_subscale",
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hue="PANAS subscale",
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binwidth=0.2,
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)
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# %%
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fig2 = sns.displot(
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data=df_esm_PANAS_summary_participant, x="std", hue="PANAS_subscale", binwidth=0.05
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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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fig2.set_axis_labels(x_var="participant standard deviation", y_var="frequency")
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if save_figs:
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fig2.figure.savefig("PANAS_std_participant.pdf", dpi=300)
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@ -148,6 +150,9 @@ df_esm_SAM_event_summary_participant = (
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# %%
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fig6 = sns.displot(data=df_esm_SAM_event_summary_participant, x="mean", binwidth=0.1)
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fig6.set_axis_labels(
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x_var="participant proportion of stressful events", y_var="frequency"
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)
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if save_figs:
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fig6.figure.savefig("SAM_events_mean_participant.pdf", dpi=300)
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@ -194,7 +199,7 @@ df_esm_SAM_threat_challenge_summary_participant = df_esm_SAM_summary_participant
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| (df_esm_SAM_summary_participant["questionnaire_id"] == 89)
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]
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df_esm_SAM_threat_challenge_summary_participant[
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"event_subscale"
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"event subscale"
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] = df_esm_SAM_threat_challenge_summary_participant.questionnaire_id.astype(
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"category"
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).cat.rename_categories(
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@ -205,7 +210,7 @@ df_esm_SAM_threat_challenge_summary_participant[
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sns.displot(
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data=df_esm_SAM_threat_challenge_summary_participant,
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x="mean",
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hue="event_subscale",
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hue="event subscale",
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binwidth=0.2,
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)
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@ -213,9 +218,10 @@ sns.displot(
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fig3 = sns.displot(
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data=df_esm_SAM_threat_challenge_summary_participant,
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x="std",
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hue="event_subscale",
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hue="event subscale",
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binwidth=0.1,
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)
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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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@ -263,7 +269,7 @@ df_esm_JCQ_summary_participant = (
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.reset_index(col_level=1)
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)
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df_esm_JCQ_summary_participant[
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"JCQ_subscale"
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"JCQ subscale"
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] = df_esm_JCQ_summary_participant.questionnaire_id.astype(
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"category"
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).cat.rename_categories(
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@ -274,9 +280,10 @@ df_esm_JCQ_summary_participant[
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fig4 = sns.displot(
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data=df_esm_JCQ_summary_participant,
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x="mean",
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hue="JCQ_subscale",
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hue="JCQ subscale",
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binwidth=0.1,
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)
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fig4.set_axis_labels(x_var="participant mean", y_var="frequency")
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if save_figs:
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fig4.figure.savefig("JCQ_mean_participant.pdf", dpi=300)
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@ -284,8 +291,11 @@ if save_figs:
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fig5 = sns.displot(
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data=df_esm_JCQ_summary_participant,
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x="std",
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hue="JCQ_subscale",
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hue="JCQ subscale",
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binwidth=0.05,
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)
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fig6.set_axis_labels(x_var="participant standard deviation", y_var="frequency")
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if save_figs:
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fig5.figure.savefig("JCQ_std_participant.pdf", dpi=300)
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# %%
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