--- a
+++ b/Notebooks/07_demographic_analysis.py
@@ -0,0 +1,23 @@
+from wearsed.dataset.WearSEDDataset import WearSEDDataset
+from tqdm import tqdm
+import pandas as pd
+
+dataset = WearSEDDataset()
+subject_data = dataset.subject_infos.loc[dataset.mesa_ids][['nsrr_age', 'nsrr_bmi', 'nsrr_sex', 'nsrr_race', 'nsrr_current_smoker', 'nsrr_ever_smoker', 'nsrr_ahi_hp3r_aasm15', 'nsrr_phrnumar_f1', 'nsrr_tst_f1']]
+subject_data.columns = ['nsrr_age', 'nsrr_bmi', 'nsrr_sex', 'nsrr_race', 'nsrr_current_smoker', 'nsrr_ever_smoker', 'nsrr_ahi', 'nsrr_ari', 'nsrr_tst']
+
+ahis = []
+aris = []
+tsts = []  # TST in minutes
+
+for recording_idx in tqdm(range(len(dataset))):
+    recording = dataset[recording_idx]
+    ahis.append(recording.get_ahi())
+    aris.append(recording.get_ari())
+    tsts.append(recording.total_sleep_time_in_sec / 60)
+
+subject_data['self_ahi'] = ahis
+subject_data['self_ari'] = aris
+subject_data['self_tst'] = tsts
+
+subject_data.to_csv('Notebooks/demographic_data.csv')
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