Prepare figures for publication.
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767548b562
commit
4c07ccccf2
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@ -203,7 +203,7 @@ df_session_counts_time_diff = df_session_counts_time_completed.join(
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# %% [markdown]
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# Now, select only the daytime EMAs of interest. Discard the differences between *different day* EMAs.
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# %%
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# %% tags=[]
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time_workday_completed_less_than_1_day = (
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(df_session_counts_time_diff.time == "daytime") # Only take daytime EMAs.
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& ~(
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@ -221,7 +221,7 @@ df_session_workday = df_session_workday.assign(
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)
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# %%
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g1 = sns.displot(df_session_workday["time_diff_minutes"], binwidth=5, height=5)
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g1 = sns.displot(df_session_workday["time_diff_minutes"], binwidth=5, height=5, aspect=1.5, color="#28827C")
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g1.set_axis_labels("Time difference [min]", "Session count")
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#g1.savefig("WorkdayEMAtimeDiff.pdf")
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@ -278,7 +278,7 @@ df_mean_daytime_interval = df_session_workday.groupby("participant_id").median()
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df_mean_daytime_interval.describe()
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# %%
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g2 = sns.displot(df_mean_daytime_interval.time_diff_minutes, binwidth=5, height=5)
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g2 = sns.displot(df_mean_daytime_interval.time_diff_minutes, binwidth=5, height=5, aspect=1.5, color="#28827C")
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g2.set_axis_labels("Median time difference [min]", "Participant count")
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#g2.savefig("WorkdayEMAtimeDiffMedianParticip.pdf")
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@ -303,7 +303,7 @@ df_count_daytime_per_participant = df_session_workday.groupby(
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df_count_daytime_per_participant["time"].describe()
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# %%
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sns.displot(df_count_daytime_per_participant.time, binwidth=1, height=5)
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sns.displot(df_count_daytime_per_participant.time, binwidth=1, height=5, aspect=1.5, color="#28827C")
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# %% [markdown]
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# ## Evening EMA
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@ -334,8 +334,9 @@ s_evening_completed_ratio = (
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s_evening_completed_ratio.describe()
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# %%
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g3 = sns.displot(s_evening_completed_ratio - 0.001, binwidth=0.05, height=5)
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g3 = sns.displot(s_evening_completed_ratio - 0.001, binwidth=0.05, height=5, aspect=1.5, color="#28827C")
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g3.set_axis_labels("Ratio of days with the evening EMA filled out", "Participant count")
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g3.set(xlim=(1.01,0.59))
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#g3.savefig("EveningEMAratioParticip.pdf")
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# %%
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