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I finished the project

Browse Source 
I am really glad I was able to get through the lab. I did have some difficulty with creating the differnt visuals, as I didnt fully make them in the pokemon lab,
so I had to use refrences to help me out. I was able to edit accoridngly to fit my project.

I wish I was a bit better at coding so I coudlve takeled even deeper reasearch questions.

I have now learned how to fully work with a data set, and create visuals to compare the data.
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mbhatti4
2025-11-11 16:32:26 -05:00
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commit b64329e20e
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# Project proposal
This planning document will also form the introduction of your argument.
## Overaching question
Which lifestyle factors most strongly influence sleep quality?
### What central question are you interested in exploring? Why are you interested in exploring this question?
Which lifestyle factors most strongly influence sleep quality? I want to see if the self reported factors (such as occupation or physical activity) influence sleep more, or if it is more so things that the person doesn't have control over, such as stress level or BMI. Although the rating for stress is subjective, I think I can compare all the different reports to see how heavily they affect sleep. I am interested in this because I have some sleep issues, and want to know what could be a cause of it, from this specefic data set. It will of course not be concrete and will differ with different data set, but It will help me understand.
### What specific research questions will you investigate?
*List 2-4 specific research questions. Each should be answerable
using your data set.*
Who has more effect on sleep duration: stress and blood pressure or physical activity?
Which occupation gets the most sleep? least?
Does BMI effect the quality of sleep? duration of sleep?
Which combination of age, gender and occupation gets the best qualtiy of sleep?
## Data source
### What data set will you use to answer your overarching question?
Sleep Health and Lifestyle Dataset
https://www.kaggle.com/datasets/uom190346a/sleep-health-and-lifestyle-dataset
### Where is this data from?
*Describe the source of the data set--not just where you downloaded it, but the person or organization who gathered the data. Explain why you trust them.*
I am using Kaggle to get the data set. I trust this because it was a reccomendation from the professor. I also looked up review at how legit kaggle is, and i was shown mostly postive sites that stated it is a good site to use as it is well regarded with data scientists.
Due to this, I feel comfortable using the data that is provided on this site to use for my project.
### What is this data about?
*Describe the nature of the data in the dataset, including the number of rows
and some of the columns which will be important to you.*
There are 374 rows of data, and and 9 columns with information. The qualtiy of sleep, duration, occupation, and BMI columns will be most important to me. Overall, all of it will help me answer my questions.
## Methods
### How will you use your data set to answer your quantitative questions?
*For each research question, explain what you will do with the data set
to answer the question, and how you will present your answer (e.g. a chart or a table).*
Who has more effect on sleep duration: stress and blood pressure or physical activity?
I will find the average hours of sleep for each of hte cetagories. I will then create a chart to compare my findings visually.
Which occupation gets the most sleep? least?
I will find the total number of each occupation. I will then find the average amount of sleept that the occupation got. I will then create a table to compare ocupations and sleep duration.
I can then asnwer both, who gets the most and least.
Does BMI effect the quality of sleep? duration of sleep?
I will find the average quality of sleep for each BMI. Then to the same for the duration of sleep. I may then create a visual of sort to compate the data.
Which combination of age, gender and occupation gets the best qualtiy of sleep?
This question seems a bit trickier. I will have to find the best qualtiy of sleep for each caterogry. I will then have to find a way to visually look at this data and find some intersection that could show me the best age, gender and occouaption.
If this ends up being too difficult, I will switch it to just age and gender to make it easier.

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[project]
name = "project-argument"
version = "0.1.0"
description = ""
authors = [
{name = "Chris Proctor",email = "chris@chrisproctor.net"}
]
license = {text = "MIT"}
readme = "README.md"
requires-python = ">=3.10,<4.0"
dependencies = [
"jupyter (>=1.1.1,<2.0.0)",
"seaborn (>=0.13.2,<0.14.0)",
"pandas (>=2.2.3,<3.0.0)"
]
[build-system]
requires = ["poetry-core>=2.0.0,<3.0.0"]
build-backend = "poetry.core.masonry.api"
[tool.poetry]
package-mode = false

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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
1 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
2 1 Male 27 Software Engineer 6.1 6 42 6 Overweight 126/83 77 4200 None
3 2 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
4 3 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
5 4 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
6 5 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
7 6 Male 28 Software Engineer 5.9 4 30 8 Obese 140/90 85 3000 Insomnia
8 7 Male 29 Teacher 6.3 6 40 7 Obese 140/90 82 3500 Insomnia
9 8 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
10 9 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
11 10 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
12 11 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
13 12 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
14 13 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
15 14 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
16 15 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
17 16 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
18 17 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Sleep Apnea
19 18 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 Sleep Apnea
20 19 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Insomnia
21 20 Male 30 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
22 21 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
23 22 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
24 23 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
25 24 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
26 25 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
27 26 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
28 27 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
29 28 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
30 29 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
31 30 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
32 31 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Sleep Apnea
33 32 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Insomnia
34 33 Female 31 Nurse 7.9 8 75 4 Normal Weight 117/76 69 6800 None
35 34 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
36 35 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
37 36 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
38 37 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
39 38 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
40 39 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
41 40 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
42 41 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
43 42 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
44 43 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
45 44 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
46 45 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
47 46 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
48 47 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
49 48 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
50 49 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
51 50 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 Sleep Apnea
52 51 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
53 52 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
54 53 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
55 54 Male 32 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
56 55 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
57 56 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
58 57 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
59 58 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
60 59 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
61 60 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
62 61 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
63 62 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
64 63 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
65 64 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
66 65 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
67 66 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
68 67 Male 32 Accountant 7.2 8 50 6 Normal Weight 118/76 68 7000 None
69 68 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 Insomnia
70 69 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
71 70 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
72 71 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
73 72 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
74 73 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
75 74 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
76 75 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
77 76 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
78 77 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
79 78 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
80 79 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
81 80 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
82 81 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
83 82 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
84 83 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
85 84 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
86 85 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
87 86 Female 35 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
88 87 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
89 88 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
90 89 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
91 90 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
92 91 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
93 92 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
94 93 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
95 94 Male 35 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
96 95 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 Insomnia
97 96 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
98 97 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
99 98 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
100 99 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
101 100 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
102 101 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
103 102 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
104 103 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
105 104 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Sleep Apnea
106 105 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 Sleep Apnea
107 106 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Insomnia
108 107 Female 37 Nurse 6.1 6 42 6 Overweight 126/83 77 4200 None
109 108 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
110 109 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
111 110 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
112 111 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
113 112 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
114 113 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
115 114 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
116 115 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
117 116 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
118 117 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
119 118 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
120 119 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
121 120 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
122 121 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
123 122 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
124 123 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
125 124 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
126 125 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
127 126 Female 37 Nurse 7.5 8 60 4 Normal Weight 120/80 70 8000 None
128 127 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
129 128 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
130 129 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
131 130 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
132 131 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
133 132 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
134 133 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
135 134 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
136 135 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
137 136 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
138 137 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
139 138 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
140 139 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
141 140 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
142 141 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
143 142 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
144 143 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
145 144 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
146 145 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 Sleep Apnea
147 146 Female 38 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
148 147 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 Insomnia
149 148 Male 39 Engineer 6.5 5 40 7 Overweight 132/87 80 4000 Insomnia
150 149 Female 39 Lawyer 6.9 7 50 6 Normal Weight 128/85 75 5500 None
151 150 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
152 151 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
153 152 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
154 153 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
155 154 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
156 155 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
157 156 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
158 157 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
159 158 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
160 159 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
161 160 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
162 161 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
163 162 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
164 163 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
165 164 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
166 165 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
167 166 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 Insomnia
168 167 Male 41 Engineer 7.3 8 70 6 Normal Weight 121/79 72 6200 None
169 168 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
170 169 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
171 170 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
172 171 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
173 172 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
174 173 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
175 174 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
176 175 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
177 176 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
178 177 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
179 178 Male 42 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
180 179 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
181 180 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
182 181 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
183 182 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
184 183 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
185 184 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
186 185 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
187 186 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
188 187 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
189 188 Male 43 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
190 189 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
191 190 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
192 191 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
193 192 Male 43 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
194 193 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
195 194 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
196 195 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
197 196 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
198 197 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
199 198 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
200 199 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
201 200 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
202 201 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
203 202 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
204 203 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
205 204 Male 43 Engineer 6.9 6 47 7 Normal Weight 117/76 69 6800 None
206 205 Male 43 Engineer 7.6 8 75 4 Overweight 122/80 68 6800 None
207 206 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
208 207 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
209 208 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
210 209 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
211 210 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
212 211 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
213 212 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
214 213 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
215 214 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
216 215 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
217 216 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
218 217 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
219 218 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
220 219 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Sleep Apnea
221 220 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Sleep Apnea
222 221 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
223 222 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
224 223 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
225 224 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
226 225 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
227 226 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
228 227 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
229 228 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
230 229 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
231 230 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
232 231 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
233 232 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
234 233 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
235 234 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
236 235 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
237 236 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
238 237 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
239 238 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
240 239 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
241 240 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
242 241 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
243 242 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
244 243 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
245 244 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
246 245 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
247 246 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
248 247 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
249 248 Male 44 Engineer 6.8 7 45 7 Overweight 130/85 78 5000 Insomnia
250 249 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 None
251 250 Male 44 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 None
252 251 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
253 252 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
254 253 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
255 254 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
256 255 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
257 256 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
258 257 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
259 258 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
260 259 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
261 260 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
262 261 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
263 262 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
264 263 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
265 264 Female 45 Manager 6.9 7 55 5 Overweight 125/82 75 5500 None
266 265 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
267 266 Female 48 Nurse 5.9 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
268 267 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
269 268 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 None
270 269 Female 49 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
271 270 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
272 271 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
273 272 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
274 273 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
275 274 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
276 275 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
277 276 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
278 277 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
279 278 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
280 279 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Insomnia
281 280 Female 50 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
282 281 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 None
283 282 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
284 283 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
285 284 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
286 285 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
287 286 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
288 287 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
289 288 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
290 289 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
291 290 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
292 291 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
293 292 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
294 293 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
295 294 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
296 295 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
297 296 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
298 297 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
299 298 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
300 299 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
301 300 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
302 301 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
303 302 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
304 303 Female 51 Nurse 7.1 7 55 6 Normal Weight 125/82 72 6000 None
305 304 Female 51 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
306 305 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
307 306 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
308 307 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
309 308 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
310 309 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
311 310 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
312 311 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
313 312 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
314 313 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
315 314 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
316 315 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
317 316 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 Insomnia
318 317 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
319 318 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
320 319 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
321 320 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
322 321 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
323 322 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
324 323 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
325 324 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
326 325 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
327 326 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
328 327 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
329 328 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
330 329 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
331 330 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
332 331 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
333 332 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
334 333 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
335 334 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
336 335 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
337 336 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
338 337 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
339 338 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
340 339 Female 54 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
341 340 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
342 341 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
343 342 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
344 343 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
345 344 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
346 345 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
347 346 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
348 347 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
349 348 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
350 349 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
351 350 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
352 351 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
353 352 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
354 353 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
355 354 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
356 355 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
357 356 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
358 357 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
359 358 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
360 359 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 None
361 360 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
362 361 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
363 362 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
364 363 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
365 364 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
366 365 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
367 366 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
368 367 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
369 368 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
370 369 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
371 370 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
372 371 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
373 372 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
374 373 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
375 374 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea

2
proposal.md
View File

@@ -31,7 +31,7 @@ https://www.kaggle.com/datasets/uom190346a/sleep-health-and-lifestyle-dataset
*Describe the source of the data set--not just where you downloaded it, but the person or organization who gathered the data. Explain why you trust them.*
I am using Kaggle to get the data set. I trust this because it was a reccomendation from the proffesor. I also looked up review at how legit kaggle is, and i was shown mostly postive sites that stated it is a good site to use as it is well regarded with data scientists.
I am using Kaggle to get the data set. I trust this because it was a reccomendation from the professor. I also looked up review at how legit kaggle is, and i was shown mostly postive sites that stated it is a good site to use as it is well regarded with data scientists.
Due to this, I feel comfortable using the data that is provided on this site to use for my project.
### What is this data about?