04B – Data Interaction • Erin McLeod • 02.09.26

Sleep, Stress, and Daily Habits

An interactive data explorer for exploring cross-sections of sleep, stress, and lifestyle indicators

Sleep plays a critical role in physical health, mental well-being, and daily productivity, yet sleep quality is shaped by a complex mix of lifestyle behaviors and health indicators that are often difficult to examine in isolation.

Rather than focusing on predictive modeling or clinical diagnosis, the goal of this page is to support exploratory learning: identifying notable relationships in the data and using them to inform further questions about the causes of poor sleep.

Guided Examples: How to Use the Data Explorer

The following examples demonstrate how to use the grid to draw insights about sleep quality based on participant-provided data.

Example 1: Stress vs Sleep Quality How to compare stress levels across low/high sleep quality rows
  1. Locate the Quality of Sleep column and scan for rows with lower sleep quality scores.
  2. In those same rows, examine the corresponding values in the Stress Level column.
  3. Click Person ID 81 and Person ID 87 to compare stress and sleep duration together.

Reflect: Do higher stress values consistently appear in rows with lower sleep quality?

Using this cross-section of data, we can plot it on a scatter chart to show that individuals reporting higher stress levels tend to also report lower sleep quality scores, suggesting an inverse relationship between perceived stress and restorative sleep.

Scatter plot showing stress level versus sleep quality
Stress level plotted against self-reported sleep quality.
Example 2: Activity vs Sleep Quality How to compare minutes of activity to sleep quality

Example 2: Comparing Physical Activity and Sleep Outcomes

This example explores how daily movement compares across individuals with varying sleep quality scores.

  1. Identify rows with higher Quality of Sleep scores.
  2. Compare the values in the Physical Activity Level and Daily Steps columns.
  3. Select two individuals with similar Stress Levels but different activity levels.
  4. Click their Person IDs to compare their full profiles in the summary output box.

Reflect: Do higher activity minutes tend to align with higher sleep quality?

When they do not (as in the 76 - 90 minute activity range visualized in the bar chart below), what other indicators might influence the outcome?

Bar chart showing average sleep quality by physical activity range
Average sleep quality grouped by observed physical activity ranges (minutes per day).
Example 3: Disorders as Signals How to view sleep quality by incidence of sleep disorders

Example 3: Examining Sleep Disorders and Associated Signals

This example compares individuals reporting sleep disorders to those without reported conditions.

  1. Locate rows where the Sleep Disorder column indicates Insomnia or Sleep Apnea.
  2. Compare their Sleep Duration, Quality of Sleep, and Stress Level values.
  3. Identify at least one row where the disorder is listed as None.
  4. Click the Person IDs from both groups to generate profile summaries.

Reflect: Do individuals reporting a sleep disorder show consistent differences in sleep quality?

Visualizing this cross-section as a bar chart shows an obvious connection between insomnia and poor sleep quality.

Bar chart comparing average sleep quality by sleep disorder category
Average sleep quality compared across reported sleep disorder categories.

The Sleep Quality Data Explorer

Hover over a row to compare values across columns. Click Person ID to generate a profile summary or to compare summaries of individuals.

Person ID Gender Age Occupation Sleep Duration Quality of Sleep Physical Activity Level Stress Level BMI Category Blood Pressure Heart Rate Daily Steps Sleep Disorder
1 Male 27 Software Engineer 6.1 6 42 6 Overweight 126/83 77 4200 None
2 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
3 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
4 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
5 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
6 Male 28 Software Engineer 5.9 4 30 8 Obese 140/90 85 3000 Insomnia
7 Male 29 Teacher 6.3 6 40 7 Obese 140/90 82 3500 Insomnia
8 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
9 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
10 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
11 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
12 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
13 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
14 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
15 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
16 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
17 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Sleep Apnea
18 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 Sleep Apnea
19 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Insomnia
20 Male 30 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
21 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
22 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
23 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
24 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
25 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
26 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
27 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
28 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
29 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
30 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
31 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Sleep Apnea
32 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Insomnia
33 Female 31 Nurse 7.9 8 75 4 Normal Weight 117/76 69 6800 None
34 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
35 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
36 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
37 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
38 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
39 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
40 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
41 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
42 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
43 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
44 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
45 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
46 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
47 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
48 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
49 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
50 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 Sleep Apnea
51 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
52 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
53 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
54 Male 32 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
55 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
56 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
57 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
58 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
59 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
60 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
61 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
62 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
63 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
64 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
65 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
66 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
67 Male 32 Accountant 7.2 8 50 6 Normal Weight 118/76 68 7000 None
68 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 Insomnia
69 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
70 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
71 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
72 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
73 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
74 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
75 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
76 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
77 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
78 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
79 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
80 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
81 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
82 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
83 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
84 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
85 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
86 Female 35 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
87 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
88 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
89 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
90 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
91 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
92 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
93 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
94 Male 35 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
95 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 Insomnia
96 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
97 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
98 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
99 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
100 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
101 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
102 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
103 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
104 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Sleep Apnea
105 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 Sleep Apnea
106 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Insomnia
107 Female 37 Nurse 6.1 6 42 6 Overweight 126/83 77 4200 None
108 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
109 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
110 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
111 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
112 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
113 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
114 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
115 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
116 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
117 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
118 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
119 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
120 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
121 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
122 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
123 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
124 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
125 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
126 Female 37 Nurse 7.5 8 60 4 Normal Weight 120/80 70 8000 None
127 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
128 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
129 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
130 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
131 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
132 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
133 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
134 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
135 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
136 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
137 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
138 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
139 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
140 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
141 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
142 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
143 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
144 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
145 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 Sleep Apnea
146 Female 38 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
147 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 Insomnia
148 Male 39 Engineer 6.5 5 40 7 Overweight 132/87 80 4000 Insomnia
149 Female 39 Lawyer 6.9 7 50 6 Normal Weight 128/85 75 5500 None
150 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
151 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
152 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
153 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
154 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
155 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
156 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
157 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
158 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
159 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
160 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
161 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
162 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
163 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
164 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
165 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
166 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 Insomnia
167 Male 41 Engineer 7.3 8 70 6 Normal Weight 121/79 72 6200 None
168 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
169 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
170 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
171 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
172 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
173 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
174 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
175 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
176 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
177 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
178 Male 42 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
179 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
180 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
181 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
182 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
183 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
184 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
185 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
186 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
187 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
188 Male 43 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
189 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
190 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
191 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
192 Male 43 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
193 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
194 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
195 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
196 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
197 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
198 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
199 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
200 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
201 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
202 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
203 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
204 Male 43 Engineer 6.9 6 47 7 Normal Weight 117/76 69 6800 None
205 Male 43 Engineer 7.6 8 75 4 Overweight 122/80 68 6800 None
206 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
207 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
208 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
209 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
210 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
211 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
212 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
213 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
214 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
215 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
216 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
217 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
218 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
219 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Sleep Apnea
220 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Sleep Apnea
221 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
222 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
223 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
224 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
225 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
226 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
227 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
228 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
229 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
230 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
231 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
232 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
233 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
234 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
235 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
236 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
237 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
238 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
239 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
240 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
241 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
242 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
243 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
244 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
245 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
246 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
247 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
248 Male 44 Engineer 6.8 7 45 7 Overweight 130/85 78 5000 Insomnia
249 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 None
250 Male 44 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 None
251 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
252 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
253 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
254 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
255 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
256 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
257 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
258 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
259 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
260 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
261 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
262 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
263 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
264 Female 45 Manager 6.9 7 55 5 Overweight 125/82 75 5500 None
265 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
266 Female 48 Nurse 5.9 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
267 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
268 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 None
269 Female 49 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
270 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
271 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
272 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
273 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
274 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
275 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
276 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
277 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
278 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
279 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Insomnia
280 Female 50 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
281 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 None
282 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
283 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
284 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
285 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
286 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
287 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
288 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
289 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
290 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
291 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
292 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
293 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
294 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
295 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
296 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
297 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
298 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
299 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
300 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
301 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
302 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
303 Female 51 Nurse 7.1 7 55 6 Normal Weight 125/82 72 6000 None
304 Female 51 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
305 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
306 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
307 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
308 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
309 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
310 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
311 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
312 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
313 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
314 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
315 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
316 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 Insomnia
317 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
318 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
319 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
320 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
321 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
322 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
323 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
324 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
325 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
326 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
327 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
328 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
329 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
330 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
331 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
332 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
333 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
334 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
335 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
336 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
337 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
338 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
339 Female 54 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
340 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
341 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
342 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
343 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
344 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
345 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
346 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
347 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
348 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
349 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
350 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
351 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
352 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
353 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
354 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
355 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
356 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
357 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
358 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
359 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 None
360 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
361 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
362 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
363 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
364 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
365 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
366 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
367 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
368 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
369 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
370 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
371 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
372 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
373 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
374 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea

Glossary

Hover to see definitions for key terms used in the dataset.

Sleep Duration
Average number of hours slept per day.
Quality of Sleep
Self-reported sleep quality score on a 1–10 scale (higher indicates better perceived sleep).
Stress Level
Self-reported stress score on a 1–10 scale (higher indicates greater perceived stress).
Physical Activity Level
Daily physical activity duration, recorded as minutes per day.
Daily Steps
Number of steps taken in a day.
BMI Category
Body Mass Index classification (e.g., Normal, Overweight, Obese) used as a broad indicator of weight status.
Blood Pressure
Systolic/diastolic blood pressure recorded in mmHg (for example, 120/80).
Sleep Disorder
Reported sleep condition category (None, Insomnia, or Sleep Apnea).

Sources

Data, definitions, and references used to build this page.

Dataset

  • Kaggle: Sleep Cycle & Productivity (Sleep Health and Lifestyle Dataset), uploaded by Adil Shamim. View dataset.

Definitions

  • Insomnia: National Heart, Lung, and Blood Institute (NHLBI), NIH.
  • Sleep Apnea: National Heart, Lung, and Blood Institute (NHLBI), NIH.
  • BMI categories: Centers for Disease Control and Prevention (CDC) — Adult BMI Categories.

Analysis Artifacts

  • Charts and data snippets were created by E. McLeod in Canva using the Kaggle dataset above.

HTML and CSS References