From 1fe66cca3273cfcabd85e6738a6970004feaefd4 Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 17:17:22 +0100 Subject: [PATCH 01/14] Updated .gitignore file --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index d2c98c52..57901c19 100644 --- a/.gitignore +++ b/.gitignore @@ -6,3 +6,5 @@ notebooks/.env notebooks/.DS_Store .DS_Store *.in +.virtual_documents/ +anaconda_projects/ From e1e916416c414550d409961da427d3d33dda7229 Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 17:18:40 +0100 Subject: [PATCH 02/14] Updated config.yaml file --- config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/config.yaml b/config.yaml index dc28ac67..a59bc469 100644 --- a/config.yaml +++ b/config.yaml @@ -1,5 +1,5 @@ input_data: - file: "../data/raw/raw_data_file.csv" + file: "../data/raw/sleep_health_and_lifestyle_dataset.csv" output_data: file: "../data/clean/cleaned_data_file.csv" From a03c31745e146eb538fa05eb81d52a63f55149d3 Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 17:22:28 +0100 Subject: [PATCH 03/14] Added project data files --- data/clean/cleaned_data_file.csv | 0 data/clean/sleep_health_project_clean.csv | 375 ++++++++++++++++++ data/raw/raw_data_file.csv | 0 .../sleep_health_and_lifestyle_dataset.csv | 375 ++++++++++++++++++ 4 files changed, 750 insertions(+) delete mode 100644 data/clean/cleaned_data_file.csv create mode 100644 data/clean/sleep_health_project_clean.csv delete mode 100644 data/raw/raw_data_file.csv create mode 100644 data/raw/sleep_health_and_lifestyle_dataset.csv diff --git a/data/clean/cleaned_data_file.csv b/data/clean/cleaned_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/data/clean/sleep_health_project_clean.csv b/data/clean/sleep_health_project_clean.csv new file mode 100644 index 00000000..32f9f5d0 --- /dev/null +++ b/data/clean/sleep_health_project_clean.csv @@ -0,0 +1,375 @@ +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, +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000, +3,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000, +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, +9,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +10,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000, +12,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +13,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000, +14,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000, +15,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000, +16,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000, +17,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Sleep Apnea +18,Male,29,Doctor,6.0,6,30,8,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, +21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +22,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +23,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +24,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000, +27,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +28,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000, +29,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000, +30,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000, +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, +34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +36,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +37,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000, +39,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000, +40,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000, +41,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +42,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +43,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +45,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +46,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +47,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +48,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000, +49,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +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, +52,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000, +53,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000, +55,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +56,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +58,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +59,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +60,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000, +61,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +62,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000, +64,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000, +65,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000, +66,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000, +67,Male,32,Accountant,7.2,8,50,6,Normal Weight,118/76,68,7000, +68,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,Insomnia +69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500, +70,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500, +71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +72,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +73,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +74,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000, +75,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +76,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +77,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +78,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +79,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +80,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000, +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, +84,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600, +85,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000, +86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000, +87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000, +88,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000, +89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000, +90,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000, +91,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000, +92,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000, +93,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000, +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, +97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000, +98,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000, +99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000, +100,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000, +101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000, 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+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, +205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800, +206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000, +207,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000, +208,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000, +209,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000, +210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +211,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000, +212,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +213,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +214,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +215,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +216,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +217,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +218,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000, +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, +250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000, +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, +263,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000, +264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500, +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, +269,Female,49,Nurse,6.0,6,90,8,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, +281,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000, +282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +283,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +284,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +285,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +286,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +287,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +288,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +289,Female,50,Nurse,6.0,6,90,8,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,6.0,6,90,8,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,6.0,6,90,8,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,6.0,6,90,8,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, +300,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +301,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +302,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +303,Female,51,Nurse,7.1,7,55,6,Normal Weight,125/82,72,6000, +304,Female,51,Nurse,6.0,6,90,8,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, +314,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +315,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +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, +318,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +320,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +321,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +322,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +323,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +324,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000, +326,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +327,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000, +328,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +329,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000, +330,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +331,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +332,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +334,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +335,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +336,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +337,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +338,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000, +339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000, +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, +343,Female,56,Doctor,8.2,9,90,3,Normal Weight,118/75,65,10000, +344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000, +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,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +354,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +355,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +356,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +357,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +358,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +359,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000, +360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000, +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,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +366,Female,59,Nurse,8.0,9,75,3,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,8.0,9,75,3,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,8.0,9,75,3,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 diff --git a/data/raw/raw_data_file.csv b/data/raw/raw_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/data/raw/sleep_health_and_lifestyle_dataset.csv b/data/raw/sleep_health_and_lifestyle_dataset.csv new file mode 100644 index 00000000..f0be22ac --- /dev/null +++ b/data/raw/sleep_health_and_lifestyle_dataset.csv @@ -0,0 +1,375 @@ +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 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file mode 100644 index 792d6005..00000000 --- a/notebooks/explore_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/functions.py b/notebooks/functions.py index 7804c676..4d3db6bf 100644 --- a/notebooks/functions.py +++ b/notebooks/functions.py @@ -24,3 +24,25 @@ def function_name(input1: data_type1, input2: data_type2,..., opt_arg: data_type return opuput + + +# Importar librerías y cargar datos +import pandas as pd +import numpy as np + +df = pd.read_csv("/Users/patriciaviladomiurecio/Desktop/Ironhack/week4/project/first_project/data/raw/Sleep_health_and_lifestyle_dataset.csv") +sleep_df = pd.read_csv(df, encoding='ISO-8859-1') +sleep_df + +# Estandarizar nombres de columnas +sleep_df.columns = ( + sleep_df.columns + .str.lower() + .str.normalize('NFKD') # quita acentos + .str.encode('ascii', errors='ignore') + .str.decode('utf-8') + .str.replace(' ', '_') + .str.replace('[^0-9a-zA-Z_]', '') +) + + diff --git a/notebooks/load_and_clean_data_username.ipynb b/notebooks/load_and_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/load_and_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/sleep_health_cleaning_pati.ipynb b/notebooks/sleep_health_cleaning_pati.ipynb new file mode 100644 index 00000000..20853974 --- /dev/null +++ b/notebooks/sleep_health_cleaning_pati.ipynb @@ -0,0 +1,2183 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "b5efb23e-690c-4763-9fef-f2545aafc6fb", + "metadata": {}, + "source": [ + "# Data Work" + ] + }, + { + "cell_type": "markdown", + "id": "9130348a-595d-4bce-9d8e-505e0c9f57d5", + "metadata": {}, + "source": [ + "### 1. Importing and exploring the DataFrame" + ] + }, + { + "cell_type": "markdown", + "id": "d614cefb-8d6f-4dec-a6a3-5c7b0cd0212d", + "metadata": {}, + "source": [ + "Importing libraries we will need to clean the Dataset - Sleep Health and Lifestyle." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "ed15ef58-7d76-4aef-bdef-6ccbb7bb318a", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "3ebe0481-88e2-49f1-9588-042f21b56b8d", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "0ec37943-cc03-4702-b4a3-f144cf3191e9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input_data': {'file': '../data/raw/Sleep_health_and_lifestyle_dataset.csv'},\n", + " 'output_data': {'file': '../data/clean/cleaned_data_file.csv'}}" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "config" + ] + }, + { + "cell_type": "markdown", + "id": "6af1d1f5-261a-436d-a7d0-2564bc45951b", + "metadata": {}, + "source": [ + "In this step, we load the Sleep Health and Lifestyle dataset into a pandas DataFrame.\n", + "\n", + "This dataset contains information about individuals' sleep habits, health indicators, lifestyle patterns, and the presence of sleep disorders." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "e80d1833-22d2-4515-b40f-51bb11ec3409", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df = pd.read_csv(config['input_data']['file'], encoding='ISO-8859-1')\n", + "sleep_df.head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "b78cea56-d492-4d29-8dc3-381dcb8f4bea", + "metadata": {}, + "source": [ + "Columns information:\n", + "\n", + "- Person ID: An identifier for each individual.\n", + "- Gender: The gender of the person (Male/Female).\n", + "- Age: The age of the person in years.\n", + "- Occupation: The occupation or profession of the person.\n", + "- Sleep Duration (hours): The number of hours the person sleeps per day.\n", + "- Quality of Sleep (scale: 1-10): A subjective rating of the quality of sleep, ranging from 1 to 10.\n", + "- Physical Activity Level (minutes/day): The number of minutes the person engages in physical activity daily.\n", + "- Stress Level (scale: 1-10): A subjective rating of the stress level experienced by the person, ranging from 1 to 10.\n", + "- BMI Category: The BMI category of the person (e.g., Underweight, Normal, Overweight).\n", + "- Blood Pressure (systolic/diastolic): The blood pressure measurement of the person, indicated as systolic pressure over diastolic pressure.\n", + "- Heart Rate (bpm): The resting heart rate of the person in beats per minute.\n", + "- Daily Steps: The number of steps the person takes per day.\n", + "- Sleep Disorder: The presence or absence of a sleep disorder in the person (None, Insomnia, Sleep Apnea)." + ] + }, + { + "cell_type": "markdown", + "id": "14413245-9908-4bd6-a5dd-a04b16ebfa20", + "metadata": {}, + "source": [ + "Checking the shape of the DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "af483cf4-9c49-4e56-8e92-1fc210108afa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(374, 13)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.shape" + ] + }, + { + "cell_type": "markdown", + "id": "6562c523-34ba-499a-8c18-c8caa11f32db", + "metadata": {}, + "source": [ + "### 2. Cleaning names of columns" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "0e78431f-8625-467f-bc25-936dedc8c000", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
\n", + "
" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.columns = (\n", + " sleep_df.columns\n", + " .str.lower()\n", + " .str.normalize('NFKD') \n", + " .str.encode('ascii', errors='ignore')\n", + " .str.decode('utf-8')\n", + " .str.replace(' ', '_')\n", + " .str.replace('[^0-9a-zA-Z_]', '')\n", + ")\n", + "sleep_df.head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "f224bb0c-d127-4ba3-9691-05acaff42a4c", + "metadata": {}, + "source": [ + "### 3. Cleaning Data" + ] + }, + { + "cell_type": "markdown", + "id": "b4729006-dd91-48a9-9c46-5e65640c2b02", + "metadata": {}, + "source": [ + "Before analysis, we check:\n", + "\n", + "- Missing values\n", + "- Duplicates\n", + "- Incorrect data types\n", + "- Formatting inconsistencies (e.g., \"140/90\" for blood pressure)\n", + "- Inconsistent categories (BMI, occupation, sleep disorder)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ab3f22b9-a7da-456f-b360-4f3659299e35", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 374 entries, 0 to 373\n", + "Data columns (total 13 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 person_id 374 non-null int64 \n", + " 1 gender 374 non-null object \n", + " 2 age 374 non-null int64 \n", + " 3 occupation 374 non-null object \n", + " 4 sleep_duration 374 non-null float64\n", + " 5 quality_of_sleep 374 non-null int64 \n", + " 6 physical_activity_level 374 non-null int64 \n", + " 7 stress_level 374 non-null int64 \n", + " 8 bmi_category 374 non-null object \n", + " 9 blood_pressure 374 non-null object \n", + " 10 heart_rate 374 non-null int64 \n", + " 11 daily_steps 374 non-null int64 \n", + " 12 sleep_disorder 155 non-null object \n", + "dtypes: float64(1), int64(7), object(5)\n", + "memory usage: 38.1+ KB\n" + ] + } + ], + "source": [ + "sleep_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a81fbcd7-b940-4cce-89a7-05d90f985031", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "person_id 0\n", + "gender 0\n", + "age 0\n", + "occupation 0\n", + "sleep_duration 0\n", + "quality_of_sleep 0\n", + "physical_activity_level 0\n", + "stress_level 0\n", + "bmi_category 0\n", + "blood_pressure 0\n", + "heart_rate 0\n", + "daily_steps 0\n", + "sleep_disorder 219\n", + "dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "28cfabf9-b058-430c-928f-dda3248231af", + "metadata": {}, + "source": [ + "Now we can check the unique values of each columns, so we can see if we need to clean them or if they are fine." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e12147fe-0b5e-4b91-92db-c52b4f111eb7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Male', 'Female'], dtype=object)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"gender\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c3b0b4f8-4814-4e71-92e1-b416547506ab", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Software Engineer', 'Doctor', 'Sales Representative', 'Teacher',\n", + " 'Nurse', 'Engineer', 'Accountant', 'Scientist', 'Lawyer',\n", + " 'Salesperson', 'Manager'], dtype=object)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"occupation\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "8bff6d10-4dd5-4135-84a3-f810ca1f82ba", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Overweight', 'Normal', 'Obese', 'Normal Weight'], dtype=object)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"bmi_category\"].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "95758916-ba64-4c3c-9433-fd2d63dd3d40", + "metadata": {}, + "source": [ + "\"Normal\" and \"Normal Weight\" Categories are refering to the same category, so we can rename them. " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "4002460e-4ebb-477a-bbc6-cb25c2beb868", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df.loc[sleep_df[\"bmi_category\"] == \"Normal Weight\", \"bmi_category\"] = \"Normal\"" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "c1c8d6e6-5b0b-4925-bbd3-d90dd961c780", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['126/83', '125/80', '140/90', '120/80', '132/87', '130/86',\n", + " '117/76', '118/76', '128/85', '131/86', '128/84', '115/75',\n", + " '135/88', '129/84', '130/85', '115/78', '119/77', '121/79',\n", + " '125/82', '135/90', '122/80', '142/92', '140/95', '139/91',\n", + " '118/75'], dtype=object)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"blood_pressure\"].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "e8ec181b-43f5-4981-9a84-f6222e979e23", + "metadata": {}, + "source": [ + "We can split blod presure in two:\n", + "- Systolic (upper number)\n", + " Pressure when the heart contracts\n", + "\n", + "- Diastolic (lower number)\n", + " Pressure when the heart relaxes" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "4768c669-a4aa-4120-a97e-6e82d360d6a1", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df[['systolic', 'diastolic']] = sleep_df['blood_pressure'].str.split('/', expand=True)\n", + "sleep_df['systolic'] = pd.to_numeric(sleep_df['systolic'])\n", + "sleep_df['diastolic'] = pd.to_numeric(sleep_df['diastolic'])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "285f5b73-61e9-4074-a2d8-add3764bc5b7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200NaN12683
12Male28Doctor6.26608Normal125/807510000NaN12580
23Male28Doctor6.26608Normal125/807510000NaN12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
................................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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374 rows × 15 columns

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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 NaN 126 \n", + "1 125/80 75 10000 NaN 125 \n", + "2 125/80 75 10000 NaN 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "4 140/90 85 3000 Sleep Apnea 140 \n", + ".. ... ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea 140 \n", + "370 140/95 68 7000 Sleep Apnea 140 \n", + "371 140/95 68 7000 Sleep Apnea 140 \n", + "372 140/95 68 7000 Sleep Apnea 140 \n", + "373 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "2 80 \n", + "3 90 \n", + "4 90 \n", + ".. ... \n", + "369 95 \n", + "370 95 \n", + "371 95 \n", + "372 95 \n", + "373 95 \n", + "\n", + "[374 rows x 15 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "946e4d41-af18-4d51-8090-074d7b24e14d", + "metadata": {}, + "outputs": [], + "source": [ + "# sleep_df.drop(columns=[\"blood_pressure\"], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "d7309aae-b868-47ba-865b-dd588ed24dc6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([nan, 'Sleep Apnea', 'Insomnia'], dtype=object)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "6bd919a5-c18b-4770-9575-fff313786213", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "Sleep Apnea 78\n", + "Insomnia 77\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "a278d4dc-00f8-41e0-a912-194dfb6f79f3", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df.fillna({\"sleep_disorder\": \"No Disorder\"}, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "60d01a0f-6c33-4052-9f57-f066025433fa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "No Disorder 219\n", + "Sleep Apnea 78\n", + "Insomnia 77\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "bad136b1-b525-448b-8d01-6b357bd1894c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
23Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
................................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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374 rows × 15 columns

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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 No Disorder 126 \n", + "1 125/80 75 10000 No Disorder 125 \n", + "2 125/80 75 10000 No Disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "4 140/90 85 3000 Sleep Apnea 140 \n", + ".. ... ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea 140 \n", + "370 140/95 68 7000 Sleep Apnea 140 \n", + "371 140/95 68 7000 Sleep Apnea 140 \n", + "372 140/95 68 7000 Sleep Apnea 140 \n", + "373 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "2 80 \n", + "3 90 \n", + "4 90 \n", + ".. ... \n", + "369 95 \n", + "370 95 \n", + "371 95 \n", + "372 95 \n", + "373 95 \n", + "\n", + "[374 rows x 15 columns]" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "b1b1e5cb-5de7-4ae9-a66d-c6c7f95cd680", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 374 entries, 0 to 373\n", + "Data columns (total 15 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 person_id 374 non-null int64 \n", + " 1 gender 374 non-null object \n", + " 2 age 374 non-null int64 \n", + " 3 occupation 374 non-null object \n", + " 4 sleep_duration 374 non-null float64\n", + " 5 quality_of_sleep 374 non-null int64 \n", + " 6 physical_activity_level 374 non-null int64 \n", + " 7 stress_level 374 non-null int64 \n", + " 8 bmi_category 374 non-null object \n", + " 9 blood_pressure 374 non-null object \n", + " 10 heart_rate 374 non-null int64 \n", + " 11 daily_steps 374 non-null int64 \n", + " 12 sleep_disorder 374 non-null object \n", + " 13 systolic 374 non-null int64 \n", + " 14 diastolic 374 non-null int64 \n", + "dtypes: float64(1), int64(9), object(5)\n", + "memory usage: 44.0+ KB\n" + ] + } + ], + "source": [ + "sleep_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "376012df-d521-4cfd-b4ca-219a4f1b32ae", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(0)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.duplicated().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "e1ccabe6-0748-49a1-b00f-9c47aa493eb1", + "metadata": {}, + "source": [ + "### 4. Checking and deleting duplicated values" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "2a01a636-2679-44af-983e-e9cd579862d6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(242)" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.duplicated(subset= sleep_df.columns.difference(['person_id'])).sum()" + ] + }, + { + "cell_type": "markdown", + "id": "e8fa5e9d-b636-4db6-af76-894a3ae450a2", + "metadata": {}, + "source": [ + "We see that we have 242 duplicated rows, so we can drop them." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "3c16260a-ea21-4073-bd36-25357a3926ac", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000No Disorder14095
359360Female59Nurse8.19753Overweight140/95687000No Disorder14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 No Disorder 126 \n", + "1 125/80 75 10000 No Disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 No Disorder 140 \n", + "359 140/95 68 7000 No Disorder 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean = sleep_df.drop_duplicates(subset=sleep_df.columns.difference(['person_id']), keep='first')\n", + "\n", + "sleep_df_clean" + ] + }, + { + "cell_type": "markdown", + "id": "2e51f62a-7496-4031-ab63-3336b55e5f29", + "metadata": {}, + "source": [ + "### 5. Looking at Statistical summary" + ] + }, + { + "cell_type": "markdown", + "id": "f100248b-9abb-4dd7-8460-c066471c1961", + "metadata": {}, + "source": [ + "#### 5.1 Statistical summary of numerical columns" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "02b81d3a-ce03-40fa-8e64-c6646e638dd8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idagesleep_durationquality_of_sleepphysical_activity_levelstress_levelheart_ratedaily_stepssystolicdiastolic
count132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000
mean171.72727341.1287887.0825767.15151558.3939395.53787971.2045456637.878788128.36363684.537879
std110.4187798.8139420.7753351.26903720.4688401.7404284.8673061766.2886577.8256506.049926
min1.00000027.0000005.8000004.00000030.0000003.00000065.0000003000.000000115.00000075.000000
25%79.50000033.7500006.4000006.00000044.2500004.00000068.0000005000.000000120.75000080.000000
50%166.50000041.0000007.1500007.00000060.0000006.00000070.0000007000.000000130.00000085.000000
75%268.25000049.0000007.7250008.00000075.0000007.00000074.0000008000.000000135.00000088.500000
max367.00000059.0000008.5000009.00000090.0000008.00000086.00000010000.000000142.00000095.000000
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" + ], + "text/plain": [ + " person_id age sleep_duration quality_of_sleep \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 171.727273 41.128788 7.082576 7.151515 \n", + "std 110.418779 8.813942 0.775335 1.269037 \n", + "min 1.000000 27.000000 5.800000 4.000000 \n", + "25% 79.500000 33.750000 6.400000 6.000000 \n", + "50% 166.500000 41.000000 7.150000 7.000000 \n", + "75% 268.250000 49.000000 7.725000 8.000000 \n", + "max 367.000000 59.000000 8.500000 9.000000 \n", + "\n", + " physical_activity_level stress_level heart_rate daily_steps \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 58.393939 5.537879 71.204545 6637.878788 \n", + "std 20.468840 1.740428 4.867306 1766.288657 \n", + "min 30.000000 3.000000 65.000000 3000.000000 \n", + "25% 44.250000 4.000000 68.000000 5000.000000 \n", + "50% 60.000000 6.000000 70.000000 7000.000000 \n", + "75% 75.000000 7.000000 74.000000 8000.000000 \n", + "max 90.000000 8.000000 86.000000 10000.000000 \n", + "\n", + " systolic diastolic \n", + "count 132.000000 132.000000 \n", + "mean 128.363636 84.537879 \n", + "std 7.825650 6.049926 \n", + "min 115.000000 75.000000 \n", + "25% 120.750000 80.000000 \n", + "50% 130.000000 85.000000 \n", + "75% 135.000000 88.500000 \n", + "max 142.000000 95.000000 " + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.describe()" + ] + }, + { + "cell_type": "markdown", + "id": "1d80eb87-18cd-4a94-9160-21149f1a18f4", + "metadata": {}, + "source": [ + "#### 5.2 Statistical summary of categorical columns" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "d90fb11e-ad5f-43e5-b191-eade012048ca", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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genderoccupationbmi_categoryblood_pressuresleep_disorder
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topMaleNurseNormal130/85No Disorder
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" + ], + "text/plain": [ + " gender occupation bmi_category blood_pressure sleep_disorder\n", + "count 132 132 132 132 132\n", + "unique 2 11 3 25 3\n", + "top Male Nurse Normal 130/85 No Disorder\n", + "freq 67 29 73 28 73" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.select_dtypes(include='object').describe()" + ] + }, + { + "cell_type": "markdown", + "id": "1be5620a-0e2f-4648-a0cf-4164f0abd734", + "metadata": {}, + "source": [ + "### 6. Exporting the clean DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "6da8fa73-5375-46bc-9642-a3909c186d38", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "98fdaa01-2254-4312-8083-3e4dd235a829", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "language": "python", + "name": "venv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From b5a7d5bf8fdd0e7851f65321609ca3e14216e47a Mon Sep 17 00:00:00 2001 From: Axelle Date: Mon, 8 Dec 2025 17:30:42 +0100 Subject: [PATCH 05/14] Data cleaning: removed 242 duplicates, handled NaN in Sleep Disorder, split Blood Pressure, standardized BMI Category --- .../Sleep_health_and_lifestyle_dataset.csv | 375 ++ sleep_health_cleaning_carmelina.ipynb | 3256 +++++++++++++++++ 2 files changed, 3631 insertions(+) create mode 100644 data/raw/Sleep_health_and_lifestyle_dataset.csv create mode 100644 sleep_health_cleaning_carmelina.ipynb diff --git a/data/raw/Sleep_health_and_lifestyle_dataset.csv b/data/raw/Sleep_health_and_lifestyle_dataset.csv new file mode 100644 index 00000000..f0be22ac --- /dev/null +++ b/data/raw/Sleep_health_and_lifestyle_dataset.csv @@ -0,0 +1,375 @@ +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 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"metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
..........................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea \n", + ".. ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea \n", + "370 140/95 68 7000 Sleep Apnea \n", + "371 140/95 68 7000 Sleep Apnea \n", + "372 140/95 68 7000 Sleep Apnea \n", + "373 140/95 68 7000 Sleep Apnea \n", + "\n", + "[374 rows x 13 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import yaml\n", + "sleep_data = pd.read_csv(\"data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", + "display(sleep_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "43a9ddf7-38df-498b-b452-37deece8bbed", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\"," + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "b03536e4-fbe1-4ace-8d25-ab07b1104db2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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Person IDAgeSleep DurationQuality of SleepPhysical Activity LevelStress LevelHeart RateDaily Steps
count374.000000374.000000374.000000374.000000374.000000374.000000374.000000374.000000
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
0FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
1FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
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3FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
4FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
..........................................
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000NaN
359360Female59Nurse8.19753Overweight140/95687000NaN
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "5 140/90 85 3000 Insomnia \n", + "6 140/90 82 3500 Insomnia \n", + ".. ... ... ... ... \n", + "358 140/95 68 7000 NaN \n", + "359 140/95 68 7000 NaN \n", + "360 140/95 68 7000 Sleep Apnea \n", + "364 140/95 68 7000 Sleep Apnea \n", + "366 140/95 68 7000 Sleep Apnea \n", + "\n", + "[132 rows x 13 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(subset=sleep_data.columns.difference(['Person ID']), keep='first')\n", + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "48461239-636f-4584-b809-918d1e9fdde1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "deleted: 242 lines\n" + ] + } + ], + "source": [ + "print(f\"deleted: {len(sleep_data) - len(sleep_data_clean)} lines\")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "10c02ad3-2bed-41bf-bc13-cb8146c8cebb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(73)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Sleep Disorder'].isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "87fc2599-08dc-4731-9c0f-9fee942137db", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(\n", + " subset=sleep_data.columns.difference(['Person ID']), \n", + " keep='first'\n", + ").copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "30bd924e-d204-4eaa-ae9f-0abb914cc5ff", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'] = sleep_data_clean['Sleep Disorder'].fillna('None')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "a8b2f914-1adb-4dd8-ac20-14c3b59d08ee", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sleep Disorder\n", + "None 73\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "2e718f68-51f4-4b13-a84e-dd332c72b214", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200None
12Male28Doctor6.26608Normal125/807510000None
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000None
359360Female59Nurse8.19753Overweight140/95687000None
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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132 rows × 13 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 None \n", + "1 125/80 75 10000 None \n", + "3 140/90 85 3000 Sleep Apnea \n", + "5 140/90 85 3000 Insomnia \n", + "6 140/90 82 3500 Insomnia \n", + ".. ... ... ... ... \n", + "358 140/95 68 7000 None \n", + "359 140/95 68 7000 None \n", + "360 140/95 68 7000 Sleep Apnea \n", + "364 140/95 68 7000 Sleep Apnea \n", + "366 140/95 68 7000 Sleep Apnea \n", + "\n", + "[132 rows x 13 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "dccc3086-cc41-45f2-8f3c-b3ffb8ad2a94", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(0)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "7f16417f-afa3-4edf-acd8-fa73d5467f29", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "BMI Category\n", + "Normal 57\n", + "Overweight 52\n", + "Normal Weight 16\n", + "Obese 7\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "41b69fe5-b2c0-4113-abb2-da3465735265", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "BMI Category\n", + "Normal 73\n", + "Overweight 52\n", + "Obese 7\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['BMI Category'] = sleep_data_clean['BMI Category'].replace('Normal Weight', 'Normal')\n", + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "97d849f5-f9fe-4077-84ec-3f8cea7ab19a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Occupation\n", + "Nurse 29\n", + "Doctor 24\n", + "Engineer 22\n", + "Teacher 15\n", + "Lawyer 15\n", + "Accountant 11\n", + "Salesperson 9\n", + "Software Engineer 3\n", + "Scientist 2\n", + "Sales Representative 1\n", + "Manager 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Occupation'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "839b0461-de2d-44f8-ade5-e5431f8c4811", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Gender\n", + "Male 67\n", + "Female 65\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "01c14e17-b36d-4034-a1db-7899043a7235", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Age\n", + "43 11\n", + "36 8\n", + "29 7\n", + "44 7\n", + "30 6\n", + "31 6\n", + "32 6\n", + "35 6\n", + "59 5\n", + "39 5\n", + "45 5\n", + "41 5\n", + "37 5\n", + "38 5\n", + "50 5\n", + "49 5\n", + "53 4\n", + "33 4\n", + "51 4\n", + "52 3\n", + "57 3\n", + "42 3\n", + "28 3\n", + "48 2\n", + "40 2\n", + "54 2\n", + "55 1\n", + "56 1\n", + "34 1\n", + "58 1\n", + "27 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Age'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "73901b72-4095-48c3-9630-c30f6f9c25fc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Blood Pressure\n", + "130/85 28\n", + "140/95 21\n", + "120/80 18\n", + "125/80 18\n", + "115/75 9\n", + "135/90 7\n", + "140/90 3\n", + "132/87 3\n", + "125/82 3\n", + "126/83 2\n", + "129/84 2\n", + "135/88 2\n", + "128/85 2\n", + "117/76 2\n", + "130/86 2\n", + "128/84 1\n", + "131/86 1\n", + "115/78 1\n", + "119/77 1\n", + "121/79 1\n", + "118/76 1\n", + "122/80 1\n", + "142/92 1\n", + "139/91 1\n", + "118/75 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['Blood Pressure'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "50fba77f-6a07-4b4e-b4a0-0dc6b2d0b6f4", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean[['Systolic', 'Diastolic']] = sleep_data_clean['Blood Pressure'].str.split('/', expand=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "a80b7b78-bfca-4e87-80bc-c8a57959ee3c", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Systolic'] = sleep_data_clean['Systolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "35325679-5391-48b0-9a43-15495bf62b5f", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Diastolic'] = sleep_data_clean['Diastolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "314b66c8-f92a-417b-ade0-5033146cc1ef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep DisorderSystolicDiastolic
01Male27Software Engineer6.16426Overweight126/83774200None12683
12Male28Doctor6.26608Normal125/807510000None12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000None14095
359360Female59Nurse8.19753Overweight140/95687000None14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder Systolic \\\n", + "0 126/83 77 4200 None 126 \n", + "1 125/80 75 10000 None 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 None 140 \n", + "359 140/95 68 7000 None 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " Diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "74d1fceb-60b9-4c75-82da-167d7fba37bf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(374, 13)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "8369f9b8-fd0e-4804-ae1d-ed47bfb9c306", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Person ID', 'Gender', 'Age', 'Occupation', 'Sleep Duration',\n", + " 'Quality of Sleep', 'Physical Activity Level', 'Stress Level',\n", + " 'BMI Category', 'Blood Pressure', 'Heart Rate', 'Daily Steps',\n", + " 'Sleep Disorder'],\n", + " dtype='object')" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "80cc3d5a-eaac-4656-8321-b961c1935729", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.rename(columns={\n", + " 'Person ID': 'person_id',\n", + " 'Gender': 'gender',\n", + " 'Age': 'age',\n", + " 'Occupation':'occupation', \n", + " 'Sleep Duration': 'sleep_duration',\n", + " 'Quality of Sleep': 'quality_of_sleep', \n", + " 'Physical Activity Level': 'physical_activity_level', \n", + " 'Stress Level': 'stress_level',\n", + " 'BMI Category': 'bmi_category', \n", + " 'Blood Pressure': 'blood_pressure', \n", + " 'Heart Rate': 'heart_rate', \n", + " 'Daily Steps': 'daily_steps',\n", + " 'Sleep Disorder': 'sleep_disorder',\n", + " 'Systolic': 'systolic',\n", + " 'Diastolic' : 'diastolic'\n", + "})" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "88f13764-ab6c-4e8b-a54a-e888ff32dc2f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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12Male28Doctor6.26608Normal125/807510000None12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000None14095
359360Female59Nurse8.19753Overweight140/95687000None14095
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryheart_ratedaily_stepssleep_disordersystolicdiastolic
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12Male28Doctor6.26608Normal7510000None12580
34Male28Sales Representative5.94308Obese853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese853000Insomnia14090
67Male29Teacher6.36407Obese823500Insomnia14090
.............................................
358359Female59Nurse8.09753Overweight687000None14095
359360Female59Nurse8.19753Overweight687000None14095
360361Female59Nurse8.29753Overweight687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight687000Sleep Apnea14095
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryheart_ratedaily_stepssleep_disordersystolicdiastolic
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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Sales Representative 5.9 \n", + "3 4 Male 28 Software Engineer 5.9 \n", + "4 5 Male 29 Teacher 6.3 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 4 30 8 Obese \n", + "3 4 30 8 Obese \n", + "4 6 40 7 Obese \n", + "\n", + " heart_rate daily_steps sleep_disorder systolic diastolic \n", + "0 77 4200 None 126 83 \n", + "1 75 10000 None 125 80 \n", + "2 85 3000 Sleep Apnea 140 90 \n", + "3 85 3000 Insomnia 140 90 \n", + "4 82 3500 Insomnia 140 90 " + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c48babc0-c799-466b-952b-07119fc87acb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 850005b8f032ae07c51536dd096b429f0e93dc9d Mon Sep 17 00:00:00 2001 From: veroniquefanchonna Date: Mon, 8 Dec 2025 17:54:19 +0100 Subject: [PATCH 06/14] update day 1 --- .../sleep_health_cleaning_veronique.ipynb | 2083 +++++++++++++++++ 1 file changed, 2083 insertions(+) create mode 100644 notebooks/sleep_health_cleaning_veronique.ipynb diff --git a/notebooks/sleep_health_cleaning_veronique.ipynb b/notebooks/sleep_health_cleaning_veronique.ipynb new file mode 100644 index 00000000..1eb48208 --- /dev/null +++ b/notebooks/sleep_health_cleaning_veronique.ipynb @@ -0,0 +1,2083 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "1e0787d1-cc80-44f6-b8dd-289100c76861", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: pandas in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (2.2.3)\n", + "Requirement already satisfied: openpyxl in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (3.1.5)\n", + "Requirement already satisfied: numpy>=1.26.0 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2.1.3)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2.9.0.post0)\n", + "Requirement already satisfied: pytz>=2020.1 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2024.1)\n", + "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2025.2)\n", + "Requirement already satisfied: et-xmlfile in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from openpyxl) (1.1.0)\n", + "Requirement already satisfied: six>=1.5 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n" + ] + } + ], + "source": [ + "!pip install pandas openpyxl" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "3285ae80-c5cc-4865-b5db-a4baea512296", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: xlrd in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (2.0.2)\n" + ] + } + ], + "source": [ + "!pip install xlrd" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "09ac5399-7b97-4b0b-8b40-3ace765b17b7", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "sleep_health = os.listdir(r\"C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\") " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "879cc154-31f8-446a-b48d-3376c745715f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Utilisez le chemin complet et le nom du fichier comme une chaîne de caractères\n", + "#titanic_df = pd.read_csv(url)\n", + "file_path = r'C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\\Sleep_health_and_lifestyle_dataset.csv'\n", + "df = pd.read_csv(file_path)\n", + "\n", + "# Affiche les 5 premières lignes du DataFrame pour vérifier la lecture\n", + "display(df.head())" + ] + }, + { + "attachments": { + "4479a41c-eee1-47c2-a355-6db4f461c513.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "1b591188-bf4a-481c-85f8-7b44874b49a1", + "metadata": {}, + "source": [ + "![image.png](attachment:4479a41c-eee1-47c2-a355-6db4f461c513.png)" + ] + }, + { + "cell_type": "markdown", + "id": "10a76d48-a40f-4494-b2cb-7aa7a7fd55a2", + "metadata": {}, + "source": [ + "# Checking for Null Values (S2D2 - ch 1.1.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "420a3cdd-ac3a-41bd-af27-8ceedad96511", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Person ID', 'Gender', 'Age', 'Occupation', 'Sleep Duration',\n", + " 'Quality of Sleep', 'Physical Activity Level', 'Stress Level',\n", + " 'BMI Category', 'Blood Pressure', 'Heart Rate', 'Daily Steps',\n", + " 'Sleep Disorder'],\n", + " dtype='object')" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Column list\n", + "\"\"\"\n", + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "b267aa4d-84e8-4a8d-b139-6ad253405def", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Person ID False\n", + "Gender False\n", + "Age False\n", + "Occupation False\n", + "Sleep Duration False\n", + "Quality of Sleep False\n", + "Physical Activity Level False\n", + "Stress Level False\n", + "BMI Category False\n", + "Blood Pressure False\n", + "Heart Rate False\n", + "Daily Steps False\n", + "Sleep Disorder True\n", + "dtype: bool" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "check null value True = null in each column\n", + "\"\"\"\n", + "df.isnull().any()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "035cf346-c415-41fc-ab1a-65e5348981d2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Person ID 0\n", + "Gender 0\n", + "Age 0\n", + "Occupation 0\n", + "Sleep Duration 0\n", + "Quality of Sleep 0\n", + "Physical Activity Level 0\n", + "Stress Level 0\n", + "BMI Category 0\n", + "Blood Pressure 0\n", + "Heart Rate 0\n", + "Daily Steps 0\n", + "Sleep Disorder 219\n", + "dtype: int64" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Count null value True each column\n", + "\"\"\"\n", + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "0c21c752-6388-4704-b514-7a1533d585e6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
0FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
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4FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
..........................................
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374 rows × 13 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration Quality of Sleep \\\n", + "0 False False False False False False \n", + "1 False False False False False False \n", + "2 False False False False False False \n", + "3 False False False False False False \n", + "4 False False False False False False \n", + ".. ... ... ... ... ... ... \n", + "369 False False False False False False \n", + "370 False False False False False False \n", + "371 False False False False False False \n", + "372 False False False False False False \n", + "373 False False False False False False \n", + "\n", + " Physical Activity Level Stress Level BMI Category Blood Pressure \\\n", + "0 False False False False \n", + "1 False False False False \n", + "2 False False False False \n", + "3 False False False False \n", + "4 False False False False \n", + ".. ... ... ... ... \n", + "369 False False False False \n", + "370 False False False False \n", + "371 False False False False \n", + "372 False False False False \n", + "373 False False False False \n", + "\n", + " Heart Rate Daily Steps Sleep Disorder \n", + "0 False False True \n", + "1 False False True \n", + "2 False False True \n", + "3 False False False \n", + "4 False False False \n", + ".. ... ... ... \n", + "369 False False False \n", + "370 False False False \n", + "371 False False False \n", + "372 False False False \n", + "373 False False False \n", + "\n", + "[374 rows x 13 columns]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Give null value True in each column + total number of rows. So 219 cells null for 374 rows\n", + "\"\"\"\n", + "df.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "f9df8f13-09ef-4422-a6b3-06493b34e00e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200None
12Male28Doctor6.26608Normal125/807510000None
23Male28Doctor6.26608Normal125/807510000None
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
..........................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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374 rows × 13 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 None \n", + "1 125/80 75 10000 None \n", + "2 125/80 75 10000 None \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea \n", + ".. ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea \n", + "370 140/95 68 7000 Sleep Apnea \n", + "371 140/95 68 7000 Sleep Apnea \n", + "372 140/95 68 7000 Sleep Apnea \n", + "373 140/95 68 7000 Sleep Apnea \n", + "\n", + "[374 rows x 13 columns]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.fillna(\"None\")" + ] + }, + { + "cell_type": "markdown", + "id": "4cfe1793-3b12-4ae3-8586-7da0dcc83f1a", + "metadata": {}, + "source": [ + "# Check duplicate (S2D2 - ch 1.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "f578862f-e607-4359-bc75-40cff188cf0f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(0)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "duplicated() method, which returns a boolean Series indicating\n", + "\"\"\"\n", + "df.duplicated().sum() # no duplicate because python include nID" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "94fb9ac3-4943-4f33-bee1-8d6e51833ae4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(242)" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "duplicated() method, without the id column obviusly \n", + "\"\"\"\n", + "\n", + "df.duplicated(subset=df.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "e60642c7-5105-4e85-a513-cab43436350c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.False_" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.duplicated((subset=df.columns.difference(['Person ID']))).any()" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "d553496b-b0f6-4bd9-97a3-c21cc728d701", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "drop_duplicates() method, remove all duplicate, remain 1 or not? : remain 1\n", + "\"\"\"\n", + "df.drop_duplicates(subset=df.columns.difference(['Person ID']), inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "6ec51d5b-91f3-487b-8fef-65c34974f8c2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(132, 13)" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "79f35f8e-ae56-40a4-a149-3f53be4a0e50", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000NaN
359360Female59Nurse8.19753Overweight140/95687000NaN
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "5 140/90 85 3000 Insomnia \n", + "6 140/90 82 3500 Insomnia \n", + ".. ... ... ... ... \n", + "358 140/95 68 7000 NaN \n", + "359 140/95 68 7000 NaN \n", + "360 140/95 68 7000 Sleep Apnea \n", + "364 140/95 68 7000 Sleep Apnea \n", + "366 140/95 68 7000 Sleep Apnea \n", + "\n", + "[132 rows x 13 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "e2ff896b-e84a-481f-a7fd-0689ae9821f2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200NaN12683
12Male28Doctor6.26608Normal125/807510000NaN12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
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67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder systolic \\\n", + "0 126/83 77 4200 NaN 126 \n", + "1 125/80 75 10000 NaN 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 NaN 140 \n", + "359 140/95 68 7000 NaN 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Name.apply(fonction) create 2 new column with specific blood condition : systolic and the diastolic\n", + "df['systolic'] = df.Name.apply(len)\n", + "\"\"\"\n", + "\n", + "df[['systolic', 'diastolic']] = df['Blood Pressure'].str.split('/', expand=True).astype(int)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "bc6d270b-4f99-4fdf-8343-12734ac8011a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "BMI Category\n", + "Normal 195\n", + "Overweight 148\n", + "Normal Weight 21\n", + "Obese 10\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "be50dcb8-9dcd-4f38-87b7-8103227c3b7e", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "2 categories of \"normal\" to merge in Normal : \n", + "\"\"\"\n", + "df['BMI Category'] = df['BMI Category'].replace('Normal Weight', 'Normal')" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "fa3f7313-47ed-4340-9879-bd53eade9884", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Occupation\n", + "Nurse 29\n", + "Doctor 24\n", + "Engineer 22\n", + "Teacher 15\n", + "Lawyer 15\n", + "Accountant 11\n", + "Salesperson 9\n", + "Software Engineer 3\n", + "Scientist 2\n", + "Sales Representative 1\n", + "Manager 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "df['Occupation'].value_counts()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "3b495677-aacd-4314-84b1-790f10bcb39c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sleep Disorder\n", + "No disorder 73\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "2eb0658b-f7a2-426d-bc25-c0420909b44b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sleep Disorder\n", + "False 132\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Sleep Disorder'].isnull().value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "6ff5dd06-295a-4204-bf9b-720ef36b5f9c", + "metadata": {}, + "outputs": [], + "source": [ + "df['Sleep Disorder'] = df['Sleep Disorder'].fillna('No disorder')" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "a9e0ba8e-2a93-4481-8f6e-759afd4f0a98", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No disorder12683
12Male28Doctor6.26608Normal125/807510000No disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000No disorder14095
359360Female59Nurse8.19753Overweight140/95687000No disorder14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder systolic \\\n", + "0 126/83 77 4200 No disorder 126 \n", + "1 125/80 75 10000 No disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 No disorder 140 \n", + "359 140/95 68 7000 No disorder 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5ccd008-6098-43cc-a757-3bd9f5694b2e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 8acdd64d6eeff01ba095d669a6a25f9122560fa4 Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 18:14:26 +0100 Subject: [PATCH 07/14] Updated README file for day 1 --- README.md | 98 +++++++++++++++++++------------------------------------ 1 file changed, 34 insertions(+), 64 deletions(-) diff --git a/README.md b/README.md index f637438f..6cfb0f05 100644 --- a/README.md +++ b/README.md @@ -1,77 +1,47 @@ -# Project overview -... +## 💤 Sleep Health & Lifestyle Analysis +#### Business Case: Predicting Sleep Disorders -# Installation -1. **Clone the repository**: +### 📌 Project Overview +This project analyzes a Sleep Health & Lifestyle dataset to identify key factors associated with sleep disorders (Insomnia and Sleep Apnea). +The goal is to understand how lifestyle, physiological metrics, and stress levels contribute to sleep disorder risk and to support early intervention strategies. -```bash -git clone https://github.com/YourUsername/repository_name.git -``` -2. **Install UV** +### 🎯 Business Problem +Sleep disorders increase medical costs, stress, and reduce quality of life. +Identifying high-risk individuals early enables: +- Preventive healthcare +- Reduced diagnosis costs +- Targeted wellbeing programs -If you're a MacOS/Linux user type: -```bash -curl -LsSf https://astral.sh/uv/install.sh | sh -``` +### ❓ Research Questions +- Which lifestyle and physiological factors correlate with sleep disorders? +- Can stress, BMI, activity, and sleep patterns predict disorder presence? +- What differentiates insomnia from sleep apnea? -If you're a Windows user open an Anaconda Powershell Prompt and type : -```bash -powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" -``` +### 🧪 Hypotheses +#### Primary Hypothesis (H1) +Individuals with high stress, high BMI, low sleep duration, and poor sleep quality are significantly more likely to have a sleep disorder. +**H0:** Sleep disorder presence is independent of these factors. -3. **Create an environment** +#### Secondary Hypotheses +- **H1a:** Obesity increases likelihood of sleep apnea. (Chi-Square) +- **H1b:** Higher stress correlates with insomnia. (t-Test / ANOVA) +- **H1c:** Sleeping <6 hours increases disorder risk. (Logistic Regression / Chi-Square) +- **H1d:** Low physical activity (<40 min/day) increases disorder prevalence. (t-Test / ANOVA) +- **H1e:** High heart rate / BP increases apnea risk. (Regression) -```bash -uv venv -``` -3. **Activate the environment** +### 🧹 Data Cleaning Summary +- Checked for missing values, incorrect data types, and duplicates. +- Standardized column names and trimmed string formatting. +- Normalized inconsistent categories (e.g., "Normal" vs "Normal Weight"). +- Split Blood Pressure into numeric Systolic and Diastolic columns. +- Converted all relevant columns to numeric types. +- Filled missing Sleep Disorder values with "No Disorder". +- Removed duplicate rows (242 duplicates dropped). -If you're a MacOS/Linux user type (if you're using a bash shell): +Final result: a clean, consistent dataset ready for analysis. -```bash -source ./venv/bin/activate -``` - -If you're a MacOS/Linux user type (if you're using a csh/tcsh shell): - -```bash -source ./venv/bin/activate.csh -``` - -If you're a Windows user type: - -```bash -.\venv\Scripts\activate -``` - -4. **Install dependencies**: - -```bash -uv pip install -r requirements.txt -``` - -# Questions -... - -# Dataset -... - -## Main dataset issues - -- ... -- ... -- ... - -## Solutions for the dataset issues -... - -# Conclussions -... - -# Next steps -... From 40e03a612660b4b2c896258d1d47bf11d8543c48 Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 18:15:29 +0100 Subject: [PATCH 08/14] Updated config.yaml clean dataframe --- config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/config.yaml b/config.yaml index a59bc469..82e339ee 100644 --- a/config.yaml +++ b/config.yaml @@ -2,4 +2,4 @@ input_data: file: "../data/raw/sleep_health_and_lifestyle_dataset.csv" output_data: - file: "../data/clean/cleaned_data_file.csv" + file: "../data/clean/sleep_health_project_clean.csv" From 8d4927efed6701c0491bdb3d38325b318b2bb5df Mon Sep 17 00:00:00 2001 From: Patricia Viladomiu Date: Mon, 8 Dec 2025 18:20:04 +0100 Subject: [PATCH 09/14] Updated notebook file --- notebooks/sleep_health_cleaning_pati.ipynb | 1775 +------------------- 1 file changed, 48 insertions(+), 1727 deletions(-) diff --git a/notebooks/sleep_health_cleaning_pati.ipynb b/notebooks/sleep_health_cleaning_pati.ipynb index 20853974..bfccd888 100644 --- a/notebooks/sleep_health_cleaning_pati.ipynb +++ b/notebooks/sleep_health_cleaning_pati.ipynb @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "id": "ed15ef58-7d76-4aef-bdef-6ccbb7bb318a", "metadata": {}, "outputs": [], @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "3ebe0481-88e2-49f1-9588-042f21b56b8d", "metadata": {}, "outputs": [], @@ -52,22 +52,10 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "0ec37943-cc03-4702-b4a3-f144cf3191e9", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'input_data': {'file': '../data/raw/Sleep_health_and_lifestyle_dataset.csv'},\n", - " 'output_data': {'file': '../data/clean/cleaned_data_file.csv'}}" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "config" ] @@ -84,159 +72,10 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "e80d1833-22d2-4515-b40f-51bb11ec3409", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" - ], - "text/plain": [ - " Person ID Gender Age Occupation Sleep Duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "2 3 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "4 5 Male 28 Sales Representative 5.9 \n", - "\n", - " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "2 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "4 4 30 8 Obese \n", - "\n", - " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", - "0 126/83 77 4200 NaN \n", - "1 125/80 75 10000 NaN \n", - "2 125/80 75 10000 NaN \n", - "3 140/90 85 3000 Sleep Apnea \n", - "4 140/90 85 3000 Sleep Apnea " - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df = pd.read_csv(config['input_data']['file'], encoding='ISO-8859-1')\n", "sleep_df.head(5)" @@ -274,21 +113,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "af483cf4-9c49-4e56-8e92-1fc210108afa", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(374, 13)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df.shape" ] @@ -303,159 +131,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "0e78431f-8625-467f-bc25-936dedc8c000", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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12Male28Doctor6.26608Normal125/807510000NaN
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
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12Male28Doctor6.26608Normal125/807510000NaN12580
23Male28Doctor6.26608Normal125/807510000NaN12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
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369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
23Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
................................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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" - ], - "text/plain": [ - " person_id gender age occupation sleep_duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "2 3 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "4 5 Male 28 Sales Representative 5.9 \n", - ".. ... ... ... ... ... \n", - "369 370 Female 59 Nurse 8.1 \n", - "370 371 Female 59 Nurse 8.0 \n", - "371 372 Female 59 Nurse 8.1 \n", - "372 373 Female 59 Nurse 8.1 \n", - "373 374 Female 59 Nurse 8.1 \n", - "\n", - " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "2 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "4 4 30 8 Obese \n", - ".. ... ... ... ... \n", - "369 9 75 3 Overweight \n", - "370 9 75 3 Overweight \n", - "371 9 75 3 Overweight \n", - "372 9 75 3 Overweight \n", - "373 9 75 3 Overweight \n", - "\n", - " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", - "0 126/83 77 4200 No Disorder 126 \n", - "1 125/80 75 10000 No Disorder 125 \n", - "2 125/80 75 10000 No Disorder 125 \n", - "3 140/90 85 3000 Sleep Apnea 140 \n", - "4 140/90 85 3000 Sleep Apnea 140 \n", - ".. ... ... ... ... ... \n", - "369 140/95 68 7000 Sleep Apnea 140 \n", - "370 140/95 68 7000 Sleep Apnea 140 \n", - "371 140/95 68 7000 Sleep Apnea 140 \n", - "372 140/95 68 7000 Sleep Apnea 140 \n", - "373 140/95 68 7000 Sleep Apnea 140 \n", - "\n", - " diastolic \n", - "0 83 \n", - "1 80 \n", - "2 80 \n", - "3 90 \n", - "4 90 \n", - ".. ... \n", - "369 95 \n", - "370 95 \n", - "371 95 \n", - "372 95 \n", - "373 95 \n", - "\n", - "[374 rows x 15 columns]" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "b1b1e5cb-5de7-4ae9-a66d-c6c7f95cd680", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 374 entries, 0 to 373\n", - "Data columns (total 15 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 person_id 374 non-null int64 \n", - " 1 gender 374 non-null object \n", - " 2 age 374 non-null int64 \n", - " 3 occupation 374 non-null object \n", - " 4 sleep_duration 374 non-null float64\n", - " 5 quality_of_sleep 374 non-null int64 \n", - " 6 physical_activity_level 374 non-null int64 \n", - " 7 stress_level 374 non-null int64 \n", - " 8 bmi_category 374 non-null object \n", - " 9 blood_pressure 374 non-null object \n", - " 10 heart_rate 374 non-null int64 \n", - " 11 daily_steps 374 non-null int64 \n", - " 12 sleep_disorder 374 non-null object \n", - " 13 systolic 374 non-null int64 \n", - " 14 diastolic 374 non-null int64 \n", - "dtypes: float64(1), int64(9), object(5)\n", - "memory usage: 44.0+ KB\n" - ] - } - ], + "outputs": [], "source": [ "sleep_df.info()" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "376012df-d521-4cfd-b4ca-219a4f1b32ae", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.int64(0)" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df.duplicated().sum()" ] @@ -1489,21 +381,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "2a01a636-2679-44af-983e-e9cd579862d6", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.int64(242)" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df.duplicated(subset= sleep_df.columns.difference(['person_id'])).sum()" ] @@ -1518,313 +399,10 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "3c16260a-ea21-4073-bd36-25357a3926ac", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000No Disorder14095
359360Female59Nurse8.19753Overweight140/95687000No Disorder14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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person_idagesleep_durationquality_of_sleepphysical_activity_levelstress_levelheart_ratedaily_stepssystolicdiastolic
count132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000
mean171.72727341.1287887.0825767.15151558.3939395.53787971.2045456637.878788128.36363684.537879
std110.4187798.8139420.7753351.26903720.4688401.7404284.8673061766.2886577.8256506.049926
min1.00000027.0000005.8000004.00000030.0000003.00000065.0000003000.000000115.00000075.000000
25%79.50000033.7500006.4000006.00000044.2500004.00000068.0000005000.000000120.75000080.000000
50%166.50000041.0000007.1500007.00000060.0000006.00000070.0000007000.000000130.00000085.000000
75%268.25000049.0000007.7250008.00000075.0000007.00000074.0000008000.000000135.00000088.500000
max367.00000059.0000008.5000009.00000090.0000008.00000086.00000010000.000000142.00000095.000000
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" - ], - "text/plain": [ - " person_id age sleep_duration quality_of_sleep \\\n", - "count 132.000000 132.000000 132.000000 132.000000 \n", - "mean 171.727273 41.128788 7.082576 7.151515 \n", - "std 110.418779 8.813942 0.775335 1.269037 \n", - "min 1.000000 27.000000 5.800000 4.000000 \n", - "25% 79.500000 33.750000 6.400000 6.000000 \n", - "50% 166.500000 41.000000 7.150000 7.000000 \n", - "75% 268.250000 49.000000 7.725000 8.000000 \n", - "max 367.000000 59.000000 8.500000 9.000000 \n", - "\n", - " physical_activity_level stress_level heart_rate daily_steps \\\n", - "count 132.000000 132.000000 132.000000 132.000000 \n", - "mean 58.393939 5.537879 71.204545 6637.878788 \n", - "std 20.468840 1.740428 4.867306 1766.288657 \n", - "min 30.000000 3.000000 65.000000 3000.000000 \n", - "25% 44.250000 4.000000 68.000000 5000.000000 \n", - "50% 60.000000 6.000000 70.000000 7000.000000 \n", - "75% 75.000000 7.000000 74.000000 8000.000000 \n", - "max 90.000000 8.000000 86.000000 10000.000000 \n", - "\n", - " systolic diastolic \n", - "count 132.000000 132.000000 \n", - "mean 128.363636 84.537879 \n", - "std 7.825650 6.049926 \n", - "min 115.000000 75.000000 \n", - "25% 120.750000 80.000000 \n", - "50% 130.000000 85.000000 \n", - "75% 135.000000 88.500000 \n", - "max 142.000000 95.000000 " - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df_clean.describe()" ] @@ -2046,88 +445,10 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "d90fb11e-ad5f-43e5-b191-eade012048ca", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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genderoccupationbmi_categoryblood_pressuresleep_disorder
count132132132132132
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topMaleNurseNormal130/85No Disorder
freq6729732873
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" - ], - "text/plain": [ - " gender occupation bmi_category blood_pressure sleep_disorder\n", - "count 132 132 132 132 132\n", - "unique 2 11 3 25 3\n", - "top Male Nurse Normal 130/85 No Disorder\n", - "freq 67 29 73 28 73" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sleep_df_clean.select_dtypes(include='object').describe()" ] @@ -2142,7 +463,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "id": "6da8fa73-5375-46bc-9642-a3909c186d38", "metadata": {}, "outputs": [], From 532abb7e2e8778ded16e920ecad5ee0aac5d9037 Mon Sep 17 00:00:00 2001 From: Axelle Date: Tue, 9 Dec 2025 10:01:39 +0100 Subject: [PATCH 10/14] Reorganized project: moved notebook to notebooks folder, removed template files --- data/raw/raw_data_file.csv | 0 notebooks/explore_clean_data_username.ipynb | 1 - notebooks/load_and_clean_data_username.ipynb | 1 - .../sleep_health_cleaning_carmelina.ipynb | 466 +++ sleep_health_cleaning_carmelina.ipynb | 3256 ----------------- 5 files changed, 466 insertions(+), 3258 deletions(-) delete mode 100644 data/raw/raw_data_file.csv delete mode 100644 notebooks/explore_clean_data_username.ipynb delete mode 100644 notebooks/load_and_clean_data_username.ipynb create mode 100644 notebooks/sleep_health_cleaning_carmelina.ipynb delete mode 100644 sleep_health_cleaning_carmelina.ipynb diff --git a/data/raw/raw_data_file.csv b/data/raw/raw_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/notebooks/explore_clean_data_username.ipynb b/notebooks/explore_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/explore_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/load_and_clean_data_username.ipynb b/notebooks/load_and_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/load_and_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/sleep_health_cleaning_carmelina.ipynb b/notebooks/sleep_health_cleaning_carmelina.ipynb new file mode 100644 index 00000000..27b2945a --- /dev/null +++ b/notebooks/sleep_health_cleaning_carmelina.ipynb @@ -0,0 +1,466 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "763adffb-1acd-4d43-b5af-b7c23e427ca0", + "metadata": {}, + "source": [ + "## Importing the data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8abe45d-f572-420e-80a0-b63e5656b5f3", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import yaml\n", + "sleep_data = pd.read_csv(\"..data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", + "display(sleep_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b03536e4-fbe1-4ace-8d25-ab07b1104db2", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60942063-3eb7-4b07-a47f-c976f3891c9a", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58359c05-5cda-4ef9-99df-be6d0c5dff5e", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "afdb0b88-0888-425e-9d93-a9a0d8ac93a7", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1627024-b4d5-442f-9410-927b15a06a11", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull().sum() " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25de34a0-92e7-43ce-9af4-2e44724a5e5d", + "metadata": {}, + "outputs": [], + "source": [ + "print(sleep_data.duplicated().sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e4fc39dd-4089-4f5c-ab56-6e52777830b5", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30df7442-2b3b-4651-a291-9703db05c8f2", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2fc28c0f-a0f7-4a9d-a966-716fe609d27b", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data['Sleep Disorder'].isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9198265a-a986-443e-aaf5-2f13f6795ead", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e6f1d8d9-eccd-419e-b400-1fcef40436e1", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47bf619e-2ae1-4f88-b3f7-acde94200602", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa803e24-f609-4bb0-b7ed-1a849ad15430", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(subset=sleep_data.columns.difference(['Person ID']), keep='first')\n", + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "48461239-636f-4584-b809-918d1e9fdde1", + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"deleted: {len(sleep_data) - len(sleep_data_clean)} lines\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "10c02ad3-2bed-41bf-bc13-cb8146c8cebb", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'].isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87fc2599-08dc-4731-9c0f-9fee942137db", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(\n", + " subset=sleep_data.columns.difference(['Person ID']), \n", + " keep='first'\n", + ").copy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30bd924e-d204-4eaa-ae9f-0abb914cc5ff", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'] = sleep_data_clean['Sleep Disorder'].fillna('None')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8b2f914-1adb-4dd8-ac20-14c3b59d08ee", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e718f68-51f4-4b13-a84e-dd332c72b214", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dccc3086-cc41-45f2-8f3c-b3ffb8ad2a94", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7f16417f-afa3-4edf-acd8-fa73d5467f29", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41b69fe5-b2c0-4113-abb2-da3465735265", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['BMI Category'] = sleep_data_clean['BMI Category'].replace('Normal Weight', 'Normal')\n", + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "97d849f5-f9fe-4077-84ec-3f8cea7ab19a", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Occupation'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "839b0461-de2d-44f8-ade5-e5431f8c4811", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01c14e17-b36d-4034-a1db-7899043a7235", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Age'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73901b72-4095-48c3-9630-c30f6f9c25fc", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Blood Pressure'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "50fba77f-6a07-4b4e-b4a0-0dc6b2d0b6f4", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean[['Systolic', 'Diastolic']] = sleep_data_clean['Blood Pressure'].str.split('/', expand=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a80b7b78-bfca-4e87-80bc-c8a57959ee3c", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Systolic'] = sleep_data_clean['Systolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35325679-5391-48b0-9a43-15495bf62b5f", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Diastolic'] = sleep_data_clean['Diastolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "314b66c8-f92a-417b-ade0-5033146cc1ef", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "74d1fceb-60b9-4c75-82da-167d7fba37bf", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8369f9b8-fd0e-4804-ae1d-ed47bfb9c306", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80cc3d5a-eaac-4656-8321-b961c1935729", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.rename(columns={\n", + " 'Person ID': 'person_id',\n", + " 'Gender': 'gender',\n", + " 'Age': 'age',\n", + " 'Occupation':'occupation', \n", + " 'Sleep Duration': 'sleep_duration',\n", + " 'Quality of Sleep': 'quality_of_sleep', \n", + " 'Physical Activity Level': 'physical_activity_level', \n", + " 'Stress Level': 'stress_level',\n", + " 'BMI Category': 'bmi_category', \n", + " 'Blood Pressure': 'blood_pressure', \n", + " 'Heart Rate': 'heart_rate', \n", + " 'Daily Steps': 'daily_steps',\n", + " 'Sleep Disorder': 'sleep_disorder',\n", + " 'Systolic': 'systolic',\n", + " 'Diastolic' : 'diastolic'\n", + "})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88f13764-ab6c-4e8b-a54a-e888ff32dc2f", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd45122f-5cd7-416e-b784-44024fb11a92", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.drop(columns='blood_pressure')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9aad531-06aa-4c8b-95e3-d799a0be03fa", + "metadata": {}, + "outputs": [], + "source": [ + "display (sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8b908ecb-9142-43cd-b7b5-a246312a6d68", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a12b9e28-3bd8-401b-ad01-470e849bc04f", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['person_id'] = range(1, len(sleep_data_clean) + 1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "699948aa-6e1f-4169-8ca9-8ce8451f9fce", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c48babc0-c799-466b-952b-07119fc87acb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/sleep_health_cleaning_carmelina.ipynb b/sleep_health_cleaning_carmelina.ipynb deleted file mode 100644 index 66021aa2..00000000 --- a/sleep_health_cleaning_carmelina.ipynb +++ /dev/null @@ -1,3256 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "763adffb-1acd-4d43-b5af-b7c23e427ca0", - "metadata": {}, - "source": [ - "## Importing the data" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "b8abe45d-f572-420e-80a0-b63e5656b5f3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
..........................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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" - ], - "text/plain": [ - " Person ID Gender Age Occupation Sleep Duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "2 3 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "4 5 Male 28 Sales Representative 5.9 \n", - ".. ... ... ... ... ... \n", - "369 370 Female 59 Nurse 8.1 \n", - "370 371 Female 59 Nurse 8.0 \n", - "371 372 Female 59 Nurse 8.1 \n", - "372 373 Female 59 Nurse 8.1 \n", - "373 374 Female 59 Nurse 8.1 \n", - "\n", - " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "2 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "4 4 30 8 Obese \n", - ".. ... ... ... ... \n", - "369 9 75 3 Overweight \n", - "370 9 75 3 Overweight \n", - "371 9 75 3 Overweight \n", - "372 9 75 3 Overweight \n", - "373 9 75 3 Overweight \n", - "\n", - " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", - "0 126/83 77 4200 NaN \n", - "1 125/80 75 10000 NaN \n", - "2 125/80 75 10000 NaN \n", - "3 140/90 85 3000 Sleep Apnea \n", - "4 140/90 85 3000 Sleep Apnea \n", - ".. ... ... ... ... \n", - "369 140/95 68 7000 Sleep Apnea \n", - "370 140/95 68 7000 Sleep Apnea \n", - "371 140/95 68 7000 Sleep Apnea \n", - "372 140/95 68 7000 Sleep Apnea \n", - "373 140/95 68 7000 Sleep Apnea \n", - "\n", - "[374 rows x 13 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "import yaml\n", - "sleep_data = pd.read_csv(\"data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", - "display(sleep_data)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "43a9ddf7-38df-498b-b452-37deece8bbed", - "metadata": {}, - "outputs": [], - "source": [ - "try:\n", - " with open(\"../config.yaml\"," - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "b03536e4-fbe1-4ace-8d25-ab07b1104db2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
0FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
1FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
2FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
3FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
4FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
..........................................
369FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
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"Heart Rate 0\n", - "Daily Steps 0\n", - "Sleep Disorder 219\n", - "dtype: int64" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data.isnull().sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "aa803e24-f609-4bb0-b7ed-1a849ad15430", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000NaN
359360Female59Nurse8.19753Overweight140/95687000NaN
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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132 rows × 13 columns

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" - ], - "text/plain": [ - " Person ID Gender Age Occupation Sleep Duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "5 6 Male 28 Software Engineer 5.9 \n", - "6 7 Male 29 Teacher 6.3 \n", - ".. ... ... ... ... ... \n", - "358 359 Female 59 Nurse 8.0 \n", - "359 360 Female 59 Nurse 8.1 \n", - "360 361 Female 59 Nurse 8.2 \n", - "364 365 Female 59 Nurse 8.0 \n", - "366 367 Female 59 Nurse 8.1 \n", - "\n", - " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "5 4 30 8 Obese \n", - "6 6 40 7 Obese \n", - ".. ... ... ... ... \n", - "358 9 75 3 Overweight \n", - "359 9 75 3 Overweight \n", - "360 9 75 3 Overweight \n", - "364 9 75 3 Overweight \n", - "366 9 75 3 Overweight \n", - "\n", - " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", - "0 126/83 77 4200 NaN \n", - "1 125/80 75 10000 NaN \n", - "3 140/90 85 3000 Sleep Apnea \n", - "5 140/90 85 3000 Insomnia \n", - "6 140/90 82 3500 Insomnia \n", - ".. ... ... ... ... \n", - "358 140/95 68 7000 NaN \n", - "359 140/95 68 7000 NaN \n", - "360 140/95 68 7000 Sleep Apnea \n", - "364 140/95 68 7000 Sleep Apnea \n", - "366 140/95 68 7000 Sleep Apnea \n", - "\n", - "[132 rows x 13 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sleep_data_clean = sleep_data.drop_duplicates(subset=sleep_data.columns.difference(['Person ID']), keep='first')\n", - "display(sleep_data_clean)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "48461239-636f-4584-b809-918d1e9fdde1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "deleted: 242 lines\n" - ] - } - ], - "source": [ - "print(f\"deleted: {len(sleep_data) - len(sleep_data_clean)} lines\")" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "10c02ad3-2bed-41bf-bc13-cb8146c8cebb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.int64(73)" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['Sleep Disorder'].isnull().sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "87fc2599-08dc-4731-9c0f-9fee942137db", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean = sleep_data.drop_duplicates(\n", - " subset=sleep_data.columns.difference(['Person ID']), \n", - " keep='first'\n", - ").copy()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "30bd924e-d204-4eaa-ae9f-0abb914cc5ff", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean['Sleep Disorder'] = sleep_data_clean['Sleep Disorder'].fillna('None')" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "a8b2f914-1adb-4dd8-ac20-14c3b59d08ee", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Sleep Disorder\n", - "None 73\n", - "Sleep Apnea 30\n", - "Insomnia 29\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['Sleep Disorder'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "2e718f68-51f4-4b13-a84e-dd332c72b214", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200None
12Male28Doctor6.26608Normal125/807510000None
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000None
359360Female59Nurse8.19753Overweight140/95687000None
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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132 rows × 13 columns

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" - ], - "text/plain": [ - " Person ID Gender Age Occupation Sleep Duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "5 6 Male 28 Software Engineer 5.9 \n", - "6 7 Male 29 Teacher 6.3 \n", - ".. ... ... ... ... ... \n", - "358 359 Female 59 Nurse 8.0 \n", - "359 360 Female 59 Nurse 8.1 \n", - "360 361 Female 59 Nurse 8.2 \n", - "364 365 Female 59 Nurse 8.0 \n", - "366 367 Female 59 Nurse 8.1 \n", - "\n", - " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "5 4 30 8 Obese \n", - "6 6 40 7 Obese \n", - ".. ... ... ... ... \n", - "358 9 75 3 Overweight \n", - "359 9 75 3 Overweight \n", - "360 9 75 3 Overweight \n", - "364 9 75 3 Overweight \n", - "366 9 75 3 Overweight \n", - "\n", - " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", - "0 126/83 77 4200 None \n", - "1 125/80 75 10000 None \n", - "3 140/90 85 3000 Sleep Apnea \n", - "5 140/90 85 3000 Insomnia \n", - "6 140/90 82 3500 Insomnia \n", - ".. ... ... ... ... \n", - "358 140/95 68 7000 None \n", - "359 140/95 68 7000 None \n", - "360 140/95 68 7000 Sleep Apnea \n", - "364 140/95 68 7000 Sleep Apnea \n", - "366 140/95 68 7000 Sleep Apnea \n", - "\n", - "[132 rows x 13 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "display(sleep_data_clean)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "dccc3086-cc41-45f2-8f3c-b3ffb8ad2a94", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.int64(0)" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "7f16417f-afa3-4edf-acd8-fa73d5467f29", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "BMI Category\n", - "Normal 57\n", - "Overweight 52\n", - "Normal Weight 16\n", - "Obese 7\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['BMI Category'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "41b69fe5-b2c0-4113-abb2-da3465735265", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "BMI Category\n", - "Normal 73\n", - "Overweight 52\n", - "Obese 7\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['BMI Category'] = sleep_data_clean['BMI Category'].replace('Normal Weight', 'Normal')\n", - "sleep_data_clean['BMI Category'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "97d849f5-f9fe-4077-84ec-3f8cea7ab19a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Occupation\n", - "Nurse 29\n", - "Doctor 24\n", - "Engineer 22\n", - "Teacher 15\n", - "Lawyer 15\n", - "Accountant 11\n", - "Salesperson 9\n", - "Software Engineer 3\n", - "Scientist 2\n", - "Sales Representative 1\n", - "Manager 1\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['Occupation'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "839b0461-de2d-44f8-ade5-e5431f8c4811", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Gender\n", - "Male 67\n", - "Female 65\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean['Gender'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "01c14e17-b36d-4034-a1db-7899043a7235", - "metadata": {}, - "outputs": [ - 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"outputs": [], - "source": [ - "sleep_data_clean['Diastolic'] = sleep_data_clean['Diastolic'].astype(int)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "314b66c8-f92a-417b-ade0-5033146cc1ef", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep DisorderSystolicDiastolic
01Male27Software Engineer6.16426Overweight126/83774200None12683
12Male28Doctor6.26608Normal125/807510000None12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000None14095
359360Female59Nurse8.19753Overweight140/95687000None14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" - ], - "text/plain": [ - " Person ID Gender Age Occupation Sleep Duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "5 6 Male 28 Software Engineer 5.9 \n", - "6 7 Male 29 Teacher 6.3 \n", - ".. ... ... ... ... ... \n", - "358 359 Female 59 Nurse 8.0 \n", - "359 360 Female 59 Nurse 8.1 \n", - "360 361 Female 59 Nurse 8.2 \n", - "364 365 Female 59 Nurse 8.0 \n", - "366 367 Female 59 Nurse 8.1 \n", - "\n", - " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "5 4 30 8 Obese \n", - "6 6 40 7 Obese \n", - ".. ... ... ... ... \n", - "358 9 75 3 Overweight \n", - "359 9 75 3 Overweight \n", - "360 9 75 3 Overweight \n", - "364 9 75 3 Overweight \n", - "366 9 75 3 Overweight \n", - "\n", - " Blood Pressure Heart Rate Daily Steps Sleep Disorder Systolic \\\n", - "0 126/83 77 4200 None 126 \n", - "1 125/80 75 10000 None 125 \n", - "3 140/90 85 3000 Sleep Apnea 140 \n", - "5 140/90 85 3000 Insomnia 140 \n", - "6 140/90 82 3500 Insomnia 140 \n", - ".. ... ... ... ... ... \n", - "358 140/95 68 7000 None 140 \n", - "359 140/95 68 7000 None 140 \n", - "360 140/95 68 7000 Sleep Apnea 140 \n", - "364 140/95 68 7000 Sleep Apnea 140 \n", - "366 140/95 68 7000 Sleep Apnea 140 \n", - "\n", - " Diastolic \n", - "0 83 \n", - "1 80 \n", - "3 90 \n", - "5 90 \n", - "6 90 \n", - ".. ... \n", - "358 95 \n", - "359 95 \n", - "360 95 \n", - "364 95 \n", - "366 95 \n", - "\n", - "[132 rows x 15 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "display(sleep_data_clean)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "74d1fceb-60b9-4c75-82da-167d7fba37bf", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(374, 13)" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "8369f9b8-fd0e-4804-ae1d-ed47bfb9c306", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['Person ID', 'Gender', 'Age', 'Occupation', 'Sleep Duration',\n", - " 'Quality of Sleep', 'Physical Activity Level', 'Stress Level',\n", - " 'BMI Category', 'Blood Pressure', 'Heart Rate', 'Daily Steps',\n", - " 'Sleep Disorder'],\n", - " dtype='object')" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "80cc3d5a-eaac-4656-8321-b961c1935729", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean = sleep_data_clean.rename(columns={\n", - " 'Person ID': 'person_id',\n", - " 'Gender': 'gender',\n", - " 'Age': 'age',\n", - " 'Occupation':'occupation', \n", - " 'Sleep Duration': 'sleep_duration',\n", - " 'Quality of Sleep': 'quality_of_sleep', \n", - " 'Physical Activity Level': 'physical_activity_level', \n", - " 'Stress Level': 'stress_level',\n", - " 'BMI Category': 'bmi_category', \n", - " 'Blood Pressure': 'blood_pressure', \n", - " 'Heart Rate': 'heart_rate', \n", - " 'Daily Steps': 'daily_steps',\n", - " 'Sleep Disorder': 'sleep_disorder',\n", - " 'Systolic': 'systolic',\n", - " 'Diastolic' : 'diastolic'\n", - "})" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "88f13764-ab6c-4e8b-a54a-e888ff32dc2f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200None12683
12Male28Doctor6.26608Normal125/807510000None12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000None14095
359360Female59Nurse8.19753Overweight140/95687000None14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" - ], - "text/plain": [ - " person_id gender age occupation sleep_duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "5 6 Male 28 Software Engineer 5.9 \n", - "6 7 Male 29 Teacher 6.3 \n", - ".. ... ... ... ... ... \n", - "358 359 Female 59 Nurse 8.0 \n", - "359 360 Female 59 Nurse 8.1 \n", - "360 361 Female 59 Nurse 8.2 \n", - "364 365 Female 59 Nurse 8.0 \n", - "366 367 Female 59 Nurse 8.1 \n", - "\n", - " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "5 4 30 8 Obese \n", - "6 6 40 7 Obese \n", - ".. ... ... ... ... \n", - "358 9 75 3 Overweight \n", - "359 9 75 3 Overweight \n", - "360 9 75 3 Overweight \n", - "364 9 75 3 Overweight \n", - "366 9 75 3 Overweight \n", - "\n", - " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", - "0 126/83 77 4200 None 126 \n", - "1 125/80 75 10000 None 125 \n", - "3 140/90 85 3000 Sleep Apnea 140 \n", - "5 140/90 85 3000 Insomnia 140 \n", - "6 140/90 82 3500 Insomnia 140 \n", - ".. ... ... ... ... ... \n", - "358 140/95 68 7000 None 140 \n", - "359 140/95 68 7000 None 140 \n", - "360 140/95 68 7000 Sleep Apnea 140 \n", - "364 140/95 68 7000 Sleep Apnea 140 \n", - "366 140/95 68 7000 Sleep Apnea 140 \n", - "\n", - " diastolic \n", - "0 83 \n", - "1 80 \n", - "3 90 \n", - "5 90 \n", - "6 90 \n", - ".. ... \n", - "358 95 \n", - "359 95 \n", - "360 95 \n", - "364 95 \n", - "366 95 \n", - "\n", - "[132 rows x 15 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "display(sleep_data_clean)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "dd45122f-5cd7-416e-b784-44024fb11a92", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean = sleep_data_clean.drop(columns='blood_pressure')" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "c9aad531-06aa-4c8b-95e3-d799a0be03fa", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight774200None12683
12Male28Doctor6.26608Normal7510000None12580
34Male28Sales Representative5.94308Obese853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese853000Insomnia14090
67Male29Teacher6.36407Obese823500Insomnia14090
.............................................
358359Female59Nurse8.09753Overweight687000None14095
359360Female59Nurse8.19753Overweight687000None14095
360361Female59Nurse8.29753Overweight687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight687000Sleep Apnea14095
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132 rows × 14 columns

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" - ], - "text/plain": [ - " person_id gender age occupation sleep_duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "3 4 Male 28 Sales Representative 5.9 \n", - "5 6 Male 28 Software Engineer 5.9 \n", - "6 7 Male 29 Teacher 6.3 \n", - ".. ... ... ... ... ... \n", - "358 359 Female 59 Nurse 8.0 \n", - "359 360 Female 59 Nurse 8.1 \n", - "360 361 Female 59 Nurse 8.2 \n", - "364 365 Female 59 Nurse 8.0 \n", - "366 367 Female 59 Nurse 8.1 \n", - "\n", - " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "3 4 30 8 Obese \n", - "5 4 30 8 Obese \n", - "6 6 40 7 Obese \n", - ".. ... ... ... ... \n", - "358 9 75 3 Overweight \n", - "359 9 75 3 Overweight \n", - "360 9 75 3 Overweight \n", - "364 9 75 3 Overweight \n", - "366 9 75 3 Overweight \n", - "\n", - " heart_rate daily_steps sleep_disorder systolic diastolic \n", - "0 77 4200 None 126 83 \n", - "1 75 10000 None 125 80 \n", - "3 85 3000 Sleep Apnea 140 90 \n", - "5 85 3000 Insomnia 140 90 \n", - "6 82 3500 Insomnia 140 90 \n", - ".. ... ... ... ... ... \n", - "358 68 7000 None 140 95 \n", - "359 68 7000 None 140 95 \n", - "360 68 7000 Sleep Apnea 140 95 \n", - "364 68 7000 Sleep Apnea 140 95 \n", - "366 68 7000 Sleep Apnea 140 95 \n", - "\n", - "[132 rows x 14 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "display (sleep_data_clean)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "8b908ecb-9142-43cd-b7b5-a246312a6d68", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean = sleep_data_clean.reset_index(drop=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "a12b9e28-3bd8-401b-ad01-470e849bc04f", - "metadata": {}, - "outputs": [], - "source": [ - "sleep_data_clean['person_id'] = range(1, len(sleep_data_clean) + 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "699948aa-6e1f-4169-8ca9-8ce8451f9fce", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight774200None12683
12Male28Doctor6.26608Normal7510000None12580
23Male28Sales Representative5.94308Obese853000Sleep Apnea14090
34Male28Software Engineer5.94308Obese853000Insomnia14090
45Male29Teacher6.36407Obese823500Insomnia14090
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" - ], - "text/plain": [ - " person_id gender age occupation sleep_duration \\\n", - "0 1 Male 27 Software Engineer 6.1 \n", - "1 2 Male 28 Doctor 6.2 \n", - "2 3 Male 28 Sales Representative 5.9 \n", - "3 4 Male 28 Software Engineer 5.9 \n", - "4 5 Male 29 Teacher 6.3 \n", - "\n", - " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", - "0 6 42 6 Overweight \n", - "1 6 60 8 Normal \n", - "2 4 30 8 Obese \n", - "3 4 30 8 Obese \n", - "4 6 40 7 Obese \n", - "\n", - " heart_rate daily_steps sleep_disorder systolic diastolic \n", - "0 77 4200 None 126 83 \n", - "1 75 10000 None 125 80 \n", - "2 85 3000 Sleep Apnea 140 90 \n", - "3 85 3000 Insomnia 140 90 \n", - "4 82 3500 Insomnia 140 90 " - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sleep_data_clean.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c48babc0-c799-466b-952b-07119fc87acb", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:base] *", - "language": "python", - "name": "conda-base-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 02a7dde0cab130e784ccb308a0337bdb3bbbb013 Mon Sep 17 00:00:00 2001 From: Axelle Date: Tue, 9 Dec 2025 10:36:33 +0100 Subject: [PATCH 11/14] Updated cleaning notebook and replaced clean dataset --- data/clean/cleaned_data_file.csv | 0 data/clean/sleep_health_project_clean.csv | 133 ++++++++++++++++++ .../sleep_health_cleaning_carmelina.ipynb | 6 +- 3 files changed, 137 insertions(+), 2 deletions(-) delete mode 100644 data/clean/cleaned_data_file.csv create mode 100644 data/clean/sleep_health_project_clean.csv diff --git a/data/clean/cleaned_data_file.csv b/data/clean/cleaned_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/data/clean/sleep_health_project_clean.csv b/data/clean/sleep_health_project_clean.csv new file mode 100644 index 00000000..1413f875 --- /dev/null +++ b/data/clean/sleep_health_project_clean.csv @@ -0,0 +1,133 @@ +person_id,gender,age,occupation,sleep_duration,quality_of_sleep,physical_activity_level,stress_level,bmi_category,heart_rate,daily_steps,sleep_disorder,systolic,diastolic +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,77,4200,None,126,83 +2,Male,28,Doctor,6.2,6,60,8,Normal,75,10000,None,125,80 +3,Male,28,Sales Representative,5.9,4,30,8,Obese,85,3000,Sleep Apnea,140,90 +4,Male,28,Software Engineer,5.9,4,30,8,Obese,85,3000,Insomnia,140,90 +5,Male,29,Teacher,6.3,6,40,7,Obese,82,3500,Insomnia,140,90 +6,Male,29,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 +7,Male,29,Doctor,6.1,6,30,8,Normal,70,8000,None,120,80 +8,Male,29,Doctor,6.0,6,30,8,Normal,70,8000,None,120,80 +9,Female,29,Nurse,6.5,5,40,7,Normal,80,4000,Sleep Apnea,132,87 +10,Male,29,Doctor,6.0,6,30,8,Normal,70,8000,Sleep Apnea,120,80 +11,Female,29,Nurse,6.5,5,40,7,Normal,80,4000,Insomnia,132,87 +12,Male,30,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 +13,Male,30,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 +14,Male,30,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 +15,Male,30,Doctor,7.9,7,75,6,Normal,70,8000,None,120,80 +16,Female,30,Nurse,6.4,5,35,7,Normal,78,4100,Sleep Apnea,130,86 +17,Female,30,Nurse,6.4,5,35,7,Normal,78,4100,Insomnia,130,86 +18,Female,31,Nurse,7.9,8,75,4,Normal,69,6800,None,117,76 +19,Male,31,Doctor,6.1,6,30,8,Normal,72,5000,None,125,80 +20,Male,31,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 +21,Male,31,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 +22,Male,31,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 +23,Male,31,Doctor,7.7,7,75,6,Normal,70,8000,Sleep Apnea,120,80 +24,Male,32,Engineer,7.5,8,45,3,Normal,70,8000,None,120,80 +25,Male,32,Doctor,6.0,6,30,8,Normal,72,5000,None,125,80 +26,Male,32,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 +27,Male,32,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 +28,Male,32,Doctor,6.2,6,30,8,Normal,72,5000,None,125,80 +29,Male,32,Accountant,7.2,8,50,6,Normal,68,7000,None,118,76 +30,Male,33,Doctor,6.0,6,30,8,Normal,72,5000,Insomnia,125,80 +31,Female,33,Scientist,6.2,6,50,6,Overweight,76,5500,None,128,85 +32,Male,33,Doctor,6.1,6,30,8,Normal,72,5000,None,125,80 +33,Male,33,Doctor,6.0,6,30,8,Normal,72,5000,None,125,80 +34,Female,34,Scientist,5.8,4,32,8,Overweight,81,5200,Sleep Apnea,131,86 +35,Male,35,Teacher,6.7,7,40,5,Overweight,70,5600,None,128,84 +36,Male,35,Software Engineer,7.5,8,60,5,Normal,70,8000,None,120,80 +37,Female,35,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 +38,Male,35,Engineer,7.2,8,60,4,Normal,65,5000,None,125,80 +39,Male,35,Engineer,7.3,8,60,4,Normal,65,5000,None,125,80 +40,Male,35,Lawyer,7.4,7,60,5,Obese,84,3300,Sleep Apnea,135,88 +41,Female,36,Accountant,7.2,8,60,4,Normal,68,7000,Insomnia,115,75 +42,Female,36,Accountant,7.1,8,60,4,Normal,68,7000,None,115,75 +43,Female,36,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 +44,Female,36,Teacher,7.1,8,60,4,Normal,68,7000,None,115,75 +45,Female,36,Teacher,7.2,8,60,4,Normal,68,7000,None,115,75 +46,Male,36,Teacher,6.6,5,35,7,Overweight,74,4800,Sleep Apnea,129,84 +47,Female,36,Teacher,7.2,8,60,4,Normal,68,7000,Sleep Apnea,115,75 +48,Male,36,Teacher,6.6,5,35,7,Overweight,74,4800,Insomnia,129,84 +49,Female,37,Nurse,6.1,6,42,6,Overweight,77,4200,None,126,83 +50,Male,37,Engineer,7.8,8,70,4,Normal,68,7000,None,120,80 +51,Male,37,Lawyer,7.4,8,60,5,Normal,68,8000,None,130,85 +52,Female,37,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 +53,Female,37,Nurse,7.5,8,60,4,Normal,70,8000,None,120,80 +54,Male,38,Lawyer,7.3,8,60,5,Normal,68,8000,None,130,85 +55,Female,38,Accountant,7.1,8,60,4,Normal,68,7000,None,115,75 +56,Male,38,Lawyer,7.1,8,60,5,Normal,68,8000,None,130,85 +57,Male,38,Lawyer,7.1,8,60,5,Normal,68,8000,Sleep Apnea,130,85 +58,Female,38,Lawyer,7.4,7,60,5,Obese,84,3300,Sleep Apnea,135,88 +59,Male,39,Lawyer,7.2,8,60,5,Normal,68,8000,Insomnia,130,85 +60,Male,39,Engineer,6.5,5,40,7,Overweight,80,4000,Insomnia,132,87 +61,Female,39,Lawyer,6.9,7,50,6,Normal,75,5500,None,128,85 +62,Female,39,Accountant,8.0,9,80,3,Normal,67,7500,None,115,78 +63,Male,39,Lawyer,7.2,8,60,5,Normal,68,8000,None,130,85 +64,Female,40,Accountant,7.2,8,55,6,Normal,73,7300,None,119,77 +65,Male,40,Lawyer,7.9,8,90,5,Normal,68,8000,None,130,85 +66,Male,41,Lawyer,7.6,8,90,5,Normal,70,8000,Insomnia,130,85 +67,Male,41,Engineer,7.3,8,70,6,Normal,72,6200,None,121,79 +68,Male,41,Lawyer,7.1,7,55,6,Overweight,72,6000,None,125,82 +69,Male,41,Lawyer,7.7,8,90,5,Normal,70,8000,None,130,85 +70,Male,41,Lawyer,7.6,8,90,5,Normal,70,8000,None,130,85 +71,Male,42,Salesperson,6.5,6,45,7,Overweight,72,6000,Insomnia,130,85 +72,Male,42,Lawyer,7.8,8,90,5,Normal,70,8000,None,130,85 +73,Female,42,Teacher,6.8,6,45,7,Overweight,78,5000,Sleep Apnea,130,85 +74,Female,43,Teacher,6.7,7,45,4,Overweight,65,6000,Insomnia,135,90 +75,Male,43,Salesperson,6.3,6,45,7,Overweight,72,6000,Insomnia,130,85 +76,Male,43,Salesperson,6.5,6,45,7,Overweight,72,6000,Insomnia,130,85 +77,Male,43,Salesperson,6.4,6,45,7,Overweight,72,6000,Insomnia,130,85 +78,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,Insomnia,130,85 +79,Male,43,Engineer,6.9,6,47,7,Normal,69,6800,None,117,76 +80,Male,43,Engineer,7.6,8,75,4,Overweight,68,6800,None,122,80 +81,Male,43,Engineer,7.7,8,90,5,Normal,70,8000,None,130,85 +82,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,None,130,85 +83,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,Sleep Apnea,130,85 +84,Male,43,Salesperson,6.5,6,45,7,Overweight,72,6000,Sleep Apnea,130,85 +85,Female,44,Teacher,6.6,7,45,4,Overweight,65,6000,Insomnia,135,90 +86,Male,44,Salesperson,6.4,6,45,7,Overweight,72,6000,Insomnia,130,85 +87,Male,44,Salesperson,6.3,6,45,7,Overweight,72,6000,Insomnia,130,85 +88,Female,44,Teacher,6.5,7,45,4,Overweight,65,6000,Insomnia,135,90 +89,Male,44,Engineer,6.8,7,45,7,Overweight,78,5000,Insomnia,130,85 +90,Male,44,Salesperson,6.4,6,45,7,Overweight,72,6000,None,130,85 +91,Male,44,Salesperson,6.5,6,45,7,Overweight,72,6000,None,130,85 +92,Female,45,Teacher,6.8,7,30,6,Overweight,65,6000,Insomnia,135,90 +93,Female,45,Teacher,6.5,7,45,4,Overweight,65,6000,Insomnia,135,90 +94,Female,45,Teacher,6.6,7,45,4,Overweight,65,6000,Insomnia,135,90 +95,Female,45,Teacher,6.6,7,45,4,Overweight,65,6000,None,135,90 +96,Female,45,Manager,6.9,7,55,5,Overweight,75,5500,None,125,82 +97,Male,48,Doctor,7.3,7,65,5,Obese,83,3500,Insomnia,142,92 +98,Female,48,Nurse,5.9,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +99,Female,49,Nurse,6.2,6,90,8,Overweight,75,10000,None,140,95 +100,Female,49,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +101,Female,49,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +102,Female,49,Nurse,6.2,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +103,Male,49,Doctor,8.1,9,85,3,Obese,86,3700,Sleep Apnea,139,91 +104,Female,50,Nurse,6.1,6,90,8,Overweight,75,10000,Insomnia,140,95 +105,Female,50,Engineer,8.3,9,30,3,Normal,65,5000,None,125,80 +106,Female,50,Nurse,6.0,6,90,8,Overweight,75,10000,None,140,95 +107,Female,50,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +108,Female,50,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +109,Female,51,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 +110,Female,51,Nurse,7.1,7,55,6,Normal,72,6000,None,125,82 +111,Female,51,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +112,Female,51,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 +113,Female,52,Accountant,6.5,7,45,7,Overweight,72,6000,Insomnia,130,85 +114,Female,52,Accountant,6.6,7,45,7,Overweight,72,6000,Insomnia,130,85 +115,Female,52,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 +116,Female,53,Engineer,8.3,9,30,3,Normal,65,5000,Insomnia,125,80 +117,Female,53,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 +118,Female,53,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 +119,Female,53,Engineer,8.3,9,30,3,Normal,65,5000,None,125,80 +120,Female,54,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 +121,Female,54,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 +122,Female,55,Nurse,8.1,9,75,4,Overweight,72,5000,Sleep Apnea,140,95 +123,Female,56,Doctor,8.2,9,90,3,Normal,65,10000,None,118,75 +124,Female,57,Nurse,8.1,9,75,3,Overweight,68,7000,None,140,95 +125,Female,57,Nurse,8.2,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +126,Female,57,Nurse,8.1,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +127,Female,58,Nurse,8.0,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +128,Female,59,Nurse,8.0,9,75,3,Overweight,68,7000,None,140,95 +129,Female,59,Nurse,8.1,9,75,3,Overweight,68,7000,None,140,95 +130,Female,59,Nurse,8.2,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +131,Female,59,Nurse,8.0,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +132,Female,59,Nurse,8.1,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 diff --git a/notebooks/sleep_health_cleaning_carmelina.ipynb b/notebooks/sleep_health_cleaning_carmelina.ipynb index 27b2945a..67cd0201 100644 --- a/notebooks/sleep_health_cleaning_carmelina.ipynb +++ b/notebooks/sleep_health_cleaning_carmelina.ipynb @@ -18,7 +18,7 @@ "import pandas as pd\n", "import numpy as np\n", "import yaml\n", - "sleep_data = pd.read_csv(\"..data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", + "sleep_data = pd.read_csv(\"data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", "display(sleep_data)" ] }, @@ -439,7 +439,9 @@ "id": "c48babc0-c799-466b-952b-07119fc87acb", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "sleep_data_clean.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')" + ] } ], "metadata": { From 8c12b1c33a981cd0d8c52d43d3e4fff0cbb157b9 Mon Sep 17 00:00:00 2001 From: pativiladomiu Date: Tue, 9 Dec 2025 10:59:30 +0100 Subject: [PATCH 12/14] Format secondary hypotheses for clarity --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 6cfb0f05..f684bdd6 100644 --- a/README.md +++ b/README.md @@ -27,11 +27,11 @@ Individuals with high stress, high BMI, low sleep duration, and poor sleep quali **H0:** Sleep disorder presence is independent of these factors. #### Secondary Hypotheses -- **H1a:** Obesity increases likelihood of sleep apnea. (Chi-Square) -- **H1b:** Higher stress correlates with insomnia. (t-Test / ANOVA) -- **H1c:** Sleeping <6 hours increases disorder risk. (Logistic Regression / Chi-Square) -- **H1d:** Low physical activity (<40 min/day) increases disorder prevalence. (t-Test / ANOVA) -- **H1e:** High heart rate / BP increases apnea risk. (Regression) +- **H1a:** Obesity increases likelihood of sleep apnea. +- **H1b:** Higher stress correlates with insomnia. +- **H1c:** Sleeping <6 hours increases disorder risk. +- **H1d:** Low physical activity (<40 min/day) increases disorder prevalence. +- **H1e:** High heart rate / BP increases apnea risk. ### 🧹 Data Cleaning Summary From b6323c57420b5af45453a44b537b89287b465b18 Mon Sep 17 00:00:00 2001 From: veroniquefanchonna Date: Tue, 9 Dec 2025 11:13:17 +0100 Subject: [PATCH 13/14] update 2 day 1 --- archive.zip | Bin 0 -> 2604 bytes data/clean/cleaned_data_file.csv | 0 .../Sleep_health_and_lifestyle_dataset.csv | 375 ++++++++++++++++++ data/raw/raw_data_file.csv | 0 .../sleep_health_cleaning_veronique.ipynb | 148 +++---- notebooks/sleep_health_project_clean.csv | 133 +++++++ 6 files changed, 574 insertions(+), 82 deletions(-) create mode 100644 archive.zip delete mode 100644 data/clean/cleaned_data_file.csv create mode 100644 data/raw/Sleep_health_and_lifestyle_dataset.csv delete mode 100644 data/raw/raw_data_file.csv create mode 100644 notebooks/sleep_health_project_clean.csv diff --git a/archive.zip b/archive.zip new file mode 100644 index 0000000000000000000000000000000000000000..32940cfe853eae6525b7342b32287934b3cad0f5 GIT binary patch literal 2604 zcmbW3Wmpr87ROms)pKs^+S(-C2D$&uMJxk}Vt8O>Cx`jXekEH3i z>8vp*RDcT_<%S7CySVuwT`=CBsNj%D49W%R7UC9+3Q_h54x^{zq=P%t{gLgte><_@ zqu(X%3yEJDR)vn~9zg3OT81!TUVv-ty27rcH$}p*`x5;4f)4+7WKBL&WG94oTRKiD zHkN0gc*F0m_w|hxx1&$`)Hm8c7Yk;asfl;nnxmr@oWAujG~Y$%^$k;>O_KXg4R(dU z%Dc9zUD!- zdZ0!@(?0Jr|K_BQP2$RskF=JBsH<^S$H)EC$RpShU&@l8aw)j|%C+T)Nqmf=NW0KCnbQo@;qS} ze=*ygWgc46jlIvrb8*T#07t8Mg1rYs*8znz%V5}!x{@z9dM|6vsRAxx}Pg~aHoQ)%mgal0}uz&rZ4sxBhf!9(Y^UdCVNVU^yD%0=C7*0rx4 zn~LLESbY@HFI~finwy(ftY^i9l}ojee}g%`=1YtYkqV!5jai|O*W(gCb!3u6|&9%GGMkCcWyE z>4!za>`u>+T%jgU`xj<~Q)Xt8iqfIR(26i%)TL)BouaFl_vNOpSm%6D>MImMM{jGx z(jFU?4r3C|is0^_pZA)iwNVci4m)qzwdtOJkcsu^45ahui!OZOZtEarp|{i`DVE(h 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+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 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+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 \ No newline at end of file diff --git a/data/raw/raw_data_file.csv b/data/raw/raw_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/notebooks/sleep_health_cleaning_veronique.ipynb b/notebooks/sleep_health_cleaning_veronique.ipynb index 1eb48208..c411cb32 100644 --- a/notebooks/sleep_health_cleaning_veronique.ipynb +++ b/notebooks/sleep_health_cleaning_veronique.ipynb @@ -5,24 +5,9 @@ "execution_count": 1, "id": "1e0787d1-cc80-44f6-b8dd-289100c76861", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: pandas in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (2.2.3)\n", - "Requirement already satisfied: openpyxl in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (3.1.5)\n", - "Requirement already satisfied: numpy>=1.26.0 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2.1.3)\n", - "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2.9.0.post0)\n", - "Requirement already satisfied: pytz>=2020.1 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2024.1)\n", - "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from pandas) (2025.2)\n", - "Requirement already satisfied: et-xmlfile in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from openpyxl) (1.1.0)\n", - "Requirement already satisfied: six>=1.5 in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n" - ] - } - ], + "outputs": [], "source": [ - "!pip install pandas openpyxl" + "#!pip install pandas openpyxl" ] }, { @@ -30,17 +15,9 @@ "execution_count": 2, "id": "3285ae80-c5cc-4865-b5db-a4baea512296", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: xlrd in c:\\users\\utilisateur\\anaconda3\\lib\\site-packages (2.0.2)\n" - ] - } - ], + "outputs": [], "source": [ - "!pip install xlrd" + "#!pip install xlrd" ] }, { @@ -56,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "id": "879cc154-31f8-446a-b48d-3376c745715f", "metadata": {}, "outputs": [ @@ -213,7 +190,7 @@ "\n", "# Utilisez le chemin complet et le nom du fichier comme une chaîne de caractères\n", "#titanic_df = pd.read_csv(url)\n", - "file_path = r'C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\\Sleep_health_and_lifestyle_dataset.csv'\n", + "file_path = r'C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\\data\\raw\\Sleep_health_and_lifestyle_dataset.csv'\n", "df = pd.read_csv(file_path)\n", "\n", "# Affiche les 5 premières lignes du DataFrame pour vérifier la lecture\n", @@ -243,7 +220,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 5, "id": "420a3cdd-ac3a-41bd-af27-8ceedad96511", "metadata": {}, "outputs": [ @@ -257,7 +234,7 @@ " dtype='object')" ] }, - "execution_count": 31, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -271,7 +248,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 6, "id": "b267aa4d-84e8-4a8d-b139-6ad253405def", "metadata": {}, "outputs": [ @@ -294,7 +271,7 @@ "dtype: bool" ] }, - "execution_count": 32, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -308,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 7, "id": "035cf346-c415-41fc-ab1a-65e5348981d2", "metadata": {}, "outputs": [ @@ -331,7 +308,7 @@ "dtype: int64" ] }, - "execution_count": 33, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -345,7 +322,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 8, "id": "0c21c752-6388-4704-b514-7a1533d585e6", "metadata": {}, "outputs": [ @@ -610,7 +587,7 @@ "[374 rows x 13 columns]" ] }, - "execution_count": 22, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -624,7 +601,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 9, "id": "f9df8f13-09ef-4422-a6b3-06493b34e00e", "metadata": { "scrolled": true @@ -891,7 +868,7 @@ "[374 rows x 13 columns]" ] }, - "execution_count": 26, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -910,7 +887,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 10, "id": "f578862f-e607-4359-bc75-40cff188cf0f", "metadata": {}, "outputs": [ @@ -920,7 +897,7 @@ "np.int64(0)" ] }, - "execution_count": 37, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -934,7 +911,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 14, "id": "94fb9ac3-4943-4f33-bee1-8d6e51833ae4", "metadata": {}, "outputs": [ @@ -944,7 +921,7 @@ "np.int64(242)" ] }, - "execution_count": 36, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -959,28 +936,17 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 15, "id": "e60642c7-5105-4e85-a513-cab43436350c", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.False_" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "df.duplicated((subset=df.columns.difference(['Person ID']))).any()" + "#df.duplicated((subset==df.columns.difference(['Person ID']))).sum()" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 16, "id": "d553496b-b0f6-4bd9-97a3-c21cc728d701", "metadata": {}, "outputs": [], @@ -993,7 +959,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 17, "id": "6ec51d5b-91f3-487b-8fef-65c34974f8c2", "metadata": {}, "outputs": [ @@ -1003,7 +969,7 @@ "(132, 13)" ] }, - "execution_count": 47, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1014,7 +980,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 18, "id": "79f35f8e-ae56-40a4-a149-3f53be4a0e50", "metadata": {}, "outputs": [ @@ -1289,7 +1255,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 19, "id": "e2ff896b-e84a-481f-a7fd-0689ae9821f2", "metadata": {}, "outputs": [ @@ -1591,7 +1557,7 @@ "[132 rows x 15 columns]" ] }, - "execution_count": 56, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1608,7 +1574,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 20, "id": "bc6d270b-4f99-4fdf-8343-12734ac8011a", "metadata": {}, "outputs": [ @@ -1616,14 +1582,14 @@ "data": { "text/plain": [ "BMI Category\n", - "Normal 195\n", - "Overweight 148\n", - "Normal Weight 21\n", - "Obese 10\n", + "Normal 57\n", + "Overweight 52\n", + "Normal Weight 16\n", + "Obese 7\n", "Name: count, dtype: int64" ] }, - "execution_count": 28, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1634,7 +1600,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 21, "id": "be50dcb8-9dcd-4f38-87b7-8103227c3b7e", "metadata": {}, "outputs": [], @@ -1647,7 +1613,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 22, "id": "fa3f7313-47ed-4340-9879-bd53eade9884", "metadata": {}, "outputs": [ @@ -1669,7 +1635,7 @@ "Name: count, dtype: int64" ] }, - "execution_count": 69, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1681,7 +1647,7 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 23, "id": "3b495677-aacd-4314-84b1-790f10bcb39c", "metadata": {}, "outputs": [ @@ -1689,13 +1655,12 @@ "data": { "text/plain": [ "Sleep Disorder\n", - "No disorder 73\n", "Sleep Apnea 30\n", "Insomnia 29\n", "Name: count, dtype: int64" ] }, - "execution_count": 70, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1706,7 +1671,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 24, "id": "2eb0658b-f7a2-426d-bc25-c0420909b44b", "metadata": {}, "outputs": [ @@ -1714,11 +1679,12 @@ "data": { "text/plain": [ "Sleep Disorder\n", - "False 132\n", + "True 73\n", + "False 59\n", "Name: count, dtype: int64" ] }, - "execution_count": 71, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1729,7 +1695,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 25, "id": "6ff5dd06-295a-4204-bf9b-720ef36b5f9c", "metadata": {}, "outputs": [], @@ -1739,7 +1705,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 26, "id": "a9e0ba8e-2a93-4481-8f6e-759afd4f0a98", "metadata": {}, "outputs": [ @@ -2041,7 +2007,7 @@ "[132 rows x 15 columns]" ] }, - "execution_count": 72, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -2052,10 +2018,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "c5ccd008-6098-43cc-a757-3bd9f5694b2e", "metadata": {}, "outputs": [], + "source": [ + "df.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b327a050-4dec-4f69-9aa0-741cd30b07d1", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd22573f-b04f-47bc-acff-fb4cc492cf71", + "metadata": {}, + "outputs": [], "source": [] } ], diff --git a/notebooks/sleep_health_project_clean.csv b/notebooks/sleep_health_project_clean.csv new file mode 100644 index 00000000..e9314158 --- /dev/null +++ b/notebooks/sleep_health_project_clean.csv @@ -0,0 +1,133 @@ +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,systolic,diastolic +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,No disorder,126,83 +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,No disorder,125,80 +4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea,140,90 +6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia,140,90 +7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia,140,90 +8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,No disorder,120,80 +14,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,No disorder,120,80 +17,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Sleep Apnea,132,87 +18,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,Sleep Apnea,120,80 +19,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Insomnia,132,87 +20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +31,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Sleep Apnea,130,86 +32,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Insomnia,130,86 +33,Female,31,Nurse,7.9,8,75,4,Normal,117/76,69,6800,No disorder,117,76 +34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No disorder,125,80 +35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea,120,80 +51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,No disorder,120,80 +53,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No disorder,125,80 +54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 +63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,No disorder,125,80 +67,Male,32,Accountant,7.2,8,50,6,Normal,118/76,68,7000,No disorder,118,76 +68,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,Insomnia,125,80 +69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,No disorder,128,85 +71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No disorder,125,80 +75,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No disorder,125,80 +81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea,131,86 +83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,No disorder,128,84 +85,Male,35,Software Engineer,7.5,8,60,5,Normal,120/80,70,8000,No disorder,120,80 +86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,No disorder,125,80 +89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,No disorder,125,80 +94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia,115,75 +96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea,129,84 +105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea,115,75 +106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia,129,84 +107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,No disorder,126,83 +108,Male,37,Engineer,7.8,8,70,4,Normal,120/80,68,7000,No disorder,120,80 +110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,No disorder,130,85 +111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +126,Female,37,Nurse,7.5,8,60,4,Normal,120/80,70,8000,No disorder,120,80 +127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,No disorder,130,85 +128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 +138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,No disorder,130,85 +145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea,130,85 +146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia,130,85 +148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia,132,87 +149,Female,39,Lawyer,6.9,7,50,6,Normal,128/85,75,5500,No disorder,128,85 +150,Female,39,Accountant,8.0,9,80,3,Normal,115/78,67,7500,No disorder,115,78 +152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,No disorder,130,85 +162,Female,40,Accountant,7.2,8,55,6,Normal,119/77,73,7300,No disorder,119,77 +164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,No disorder,130,85 +166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +167,Male,41,Engineer,7.3,8,70,6,Normal,121/79,72,6200,No disorder,121,79 +168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,No disorder,125,82 +170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,No disorder,130,85 +175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,No disorder,130,85 +178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,No disorder,130,85 +185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea,130,85 +187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +204,Male,43,Engineer,6.9,6,47,7,Normal,117/76,69,6800,No disorder,117,76 +205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,No disorder,122,80 +206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,No disorder,130,85 +210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,No disorder,130,85 +219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea,130,85 +220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea,130,85 +221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia,130,85 +249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,No disorder,130,85 +250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,No disorder,130,85 +251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia,135,90 +253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,No disorder,135,90 +264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,No disorder,125,82 +265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia,142,92 +266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,No disorder,140,95 +269,Female,49,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea,139,91 +279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia,140,95 +280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +281,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,No disorder,140,95 +282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +283,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +303,Female,51,Nurse,7.1,7,55,6,Normal,125/82,72,6000,No disorder,125,82 +304,Female,51,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia,125,80 +317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 +340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea,140,95 +342,Female,56,Doctor,8.2,9,90,3,Normal,118/75,65,10000,No disorder,118,75 +344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 +345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +353,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +359,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 +360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 +361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +365,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 From 5f530f8acfb49992edf65e92faf63cf5c2a47b10 Mon Sep 17 00:00:00 2001 From: veroniquefanchonna Date: Tue, 9 Dec 2025 17:59:16 +0100 Subject: [PATCH 14/14] H1 hypothesys day 2 --- data/clean/sleep_health_project_clean.csv | 266 +++++++++--------- .../sleep_health_analysis_veronique.ipynb | 225 +++++++++++++++ notebooks/sleep_health_project_clean.csv | 133 --------- 3 files changed, 358 insertions(+), 266 deletions(-) create mode 100644 notebooks/sleep_health_analysis_veronique.ipynb delete mode 100644 notebooks/sleep_health_project_clean.csv diff --git a/data/clean/sleep_health_project_clean.csv b/data/clean/sleep_health_project_clean.csv index 1413f875..cc93b280 100644 --- a/data/clean/sleep_health_project_clean.csv +++ b/data/clean/sleep_health_project_clean.csv @@ -1,133 +1,133 @@ -person_id,gender,age,occupation,sleep_duration,quality_of_sleep,physical_activity_level,stress_level,bmi_category,heart_rate,daily_steps,sleep_disorder,systolic,diastolic -1,Male,27,Software Engineer,6.1,6,42,6,Overweight,77,4200,None,126,83 -2,Male,28,Doctor,6.2,6,60,8,Normal,75,10000,None,125,80 -3,Male,28,Sales Representative,5.9,4,30,8,Obese,85,3000,Sleep Apnea,140,90 -4,Male,28,Software Engineer,5.9,4,30,8,Obese,85,3000,Insomnia,140,90 -5,Male,29,Teacher,6.3,6,40,7,Obese,82,3500,Insomnia,140,90 -6,Male,29,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 -7,Male,29,Doctor,6.1,6,30,8,Normal,70,8000,None,120,80 -8,Male,29,Doctor,6.0,6,30,8,Normal,70,8000,None,120,80 -9,Female,29,Nurse,6.5,5,40,7,Normal,80,4000,Sleep Apnea,132,87 -10,Male,29,Doctor,6.0,6,30,8,Normal,70,8000,Sleep Apnea,120,80 -11,Female,29,Nurse,6.5,5,40,7,Normal,80,4000,Insomnia,132,87 -12,Male,30,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 -13,Male,30,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 -14,Male,30,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 -15,Male,30,Doctor,7.9,7,75,6,Normal,70,8000,None,120,80 -16,Female,30,Nurse,6.4,5,35,7,Normal,78,4100,Sleep Apnea,130,86 -17,Female,30,Nurse,6.4,5,35,7,Normal,78,4100,Insomnia,130,86 -18,Female,31,Nurse,7.9,8,75,4,Normal,69,6800,None,117,76 -19,Male,31,Doctor,6.1,6,30,8,Normal,72,5000,None,125,80 -20,Male,31,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 -21,Male,31,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 -22,Male,31,Doctor,7.8,7,75,6,Normal,70,8000,None,120,80 -23,Male,31,Doctor,7.7,7,75,6,Normal,70,8000,Sleep Apnea,120,80 -24,Male,32,Engineer,7.5,8,45,3,Normal,70,8000,None,120,80 -25,Male,32,Doctor,6.0,6,30,8,Normal,72,5000,None,125,80 -26,Male,32,Doctor,7.6,7,75,6,Normal,70,8000,None,120,80 -27,Male,32,Doctor,7.7,7,75,6,Normal,70,8000,None,120,80 -28,Male,32,Doctor,6.2,6,30,8,Normal,72,5000,None,125,80 -29,Male,32,Accountant,7.2,8,50,6,Normal,68,7000,None,118,76 -30,Male,33,Doctor,6.0,6,30,8,Normal,72,5000,Insomnia,125,80 -31,Female,33,Scientist,6.2,6,50,6,Overweight,76,5500,None,128,85 -32,Male,33,Doctor,6.1,6,30,8,Normal,72,5000,None,125,80 -33,Male,33,Doctor,6.0,6,30,8,Normal,72,5000,None,125,80 -34,Female,34,Scientist,5.8,4,32,8,Overweight,81,5200,Sleep Apnea,131,86 -35,Male,35,Teacher,6.7,7,40,5,Overweight,70,5600,None,128,84 -36,Male,35,Software Engineer,7.5,8,60,5,Normal,70,8000,None,120,80 -37,Female,35,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 -38,Male,35,Engineer,7.2,8,60,4,Normal,65,5000,None,125,80 -39,Male,35,Engineer,7.3,8,60,4,Normal,65,5000,None,125,80 -40,Male,35,Lawyer,7.4,7,60,5,Obese,84,3300,Sleep Apnea,135,88 -41,Female,36,Accountant,7.2,8,60,4,Normal,68,7000,Insomnia,115,75 -42,Female,36,Accountant,7.1,8,60,4,Normal,68,7000,None,115,75 -43,Female,36,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 -44,Female,36,Teacher,7.1,8,60,4,Normal,68,7000,None,115,75 -45,Female,36,Teacher,7.2,8,60,4,Normal,68,7000,None,115,75 -46,Male,36,Teacher,6.6,5,35,7,Overweight,74,4800,Sleep Apnea,129,84 -47,Female,36,Teacher,7.2,8,60,4,Normal,68,7000,Sleep Apnea,115,75 -48,Male,36,Teacher,6.6,5,35,7,Overweight,74,4800,Insomnia,129,84 -49,Female,37,Nurse,6.1,6,42,6,Overweight,77,4200,None,126,83 -50,Male,37,Engineer,7.8,8,70,4,Normal,68,7000,None,120,80 -51,Male,37,Lawyer,7.4,8,60,5,Normal,68,8000,None,130,85 -52,Female,37,Accountant,7.2,8,60,4,Normal,68,7000,None,115,75 -53,Female,37,Nurse,7.5,8,60,4,Normal,70,8000,None,120,80 -54,Male,38,Lawyer,7.3,8,60,5,Normal,68,8000,None,130,85 -55,Female,38,Accountant,7.1,8,60,4,Normal,68,7000,None,115,75 -56,Male,38,Lawyer,7.1,8,60,5,Normal,68,8000,None,130,85 -57,Male,38,Lawyer,7.1,8,60,5,Normal,68,8000,Sleep Apnea,130,85 -58,Female,38,Lawyer,7.4,7,60,5,Obese,84,3300,Sleep Apnea,135,88 -59,Male,39,Lawyer,7.2,8,60,5,Normal,68,8000,Insomnia,130,85 -60,Male,39,Engineer,6.5,5,40,7,Overweight,80,4000,Insomnia,132,87 -61,Female,39,Lawyer,6.9,7,50,6,Normal,75,5500,None,128,85 -62,Female,39,Accountant,8.0,9,80,3,Normal,67,7500,None,115,78 -63,Male,39,Lawyer,7.2,8,60,5,Normal,68,8000,None,130,85 -64,Female,40,Accountant,7.2,8,55,6,Normal,73,7300,None,119,77 -65,Male,40,Lawyer,7.9,8,90,5,Normal,68,8000,None,130,85 -66,Male,41,Lawyer,7.6,8,90,5,Normal,70,8000,Insomnia,130,85 -67,Male,41,Engineer,7.3,8,70,6,Normal,72,6200,None,121,79 -68,Male,41,Lawyer,7.1,7,55,6,Overweight,72,6000,None,125,82 -69,Male,41,Lawyer,7.7,8,90,5,Normal,70,8000,None,130,85 -70,Male,41,Lawyer,7.6,8,90,5,Normal,70,8000,None,130,85 -71,Male,42,Salesperson,6.5,6,45,7,Overweight,72,6000,Insomnia,130,85 -72,Male,42,Lawyer,7.8,8,90,5,Normal,70,8000,None,130,85 -73,Female,42,Teacher,6.8,6,45,7,Overweight,78,5000,Sleep Apnea,130,85 -74,Female,43,Teacher,6.7,7,45,4,Overweight,65,6000,Insomnia,135,90 -75,Male,43,Salesperson,6.3,6,45,7,Overweight,72,6000,Insomnia,130,85 -76,Male,43,Salesperson,6.5,6,45,7,Overweight,72,6000,Insomnia,130,85 -77,Male,43,Salesperson,6.4,6,45,7,Overweight,72,6000,Insomnia,130,85 -78,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,Insomnia,130,85 -79,Male,43,Engineer,6.9,6,47,7,Normal,69,6800,None,117,76 -80,Male,43,Engineer,7.6,8,75,4,Overweight,68,6800,None,122,80 -81,Male,43,Engineer,7.7,8,90,5,Normal,70,8000,None,130,85 -82,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,None,130,85 -83,Male,43,Engineer,7.8,8,90,5,Normal,70,8000,Sleep Apnea,130,85 -84,Male,43,Salesperson,6.5,6,45,7,Overweight,72,6000,Sleep Apnea,130,85 -85,Female,44,Teacher,6.6,7,45,4,Overweight,65,6000,Insomnia,135,90 -86,Male,44,Salesperson,6.4,6,45,7,Overweight,72,6000,Insomnia,130,85 -87,Male,44,Salesperson,6.3,6,45,7,Overweight,72,6000,Insomnia,130,85 -88,Female,44,Teacher,6.5,7,45,4,Overweight,65,6000,Insomnia,135,90 -89,Male,44,Engineer,6.8,7,45,7,Overweight,78,5000,Insomnia,130,85 -90,Male,44,Salesperson,6.4,6,45,7,Overweight,72,6000,None,130,85 -91,Male,44,Salesperson,6.5,6,45,7,Overweight,72,6000,None,130,85 -92,Female,45,Teacher,6.8,7,30,6,Overweight,65,6000,Insomnia,135,90 -93,Female,45,Teacher,6.5,7,45,4,Overweight,65,6000,Insomnia,135,90 -94,Female,45,Teacher,6.6,7,45,4,Overweight,65,6000,Insomnia,135,90 -95,Female,45,Teacher,6.6,7,45,4,Overweight,65,6000,None,135,90 -96,Female,45,Manager,6.9,7,55,5,Overweight,75,5500,None,125,82 -97,Male,48,Doctor,7.3,7,65,5,Obese,83,3500,Insomnia,142,92 -98,Female,48,Nurse,5.9,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -99,Female,49,Nurse,6.2,6,90,8,Overweight,75,10000,None,140,95 -100,Female,49,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -101,Female,49,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -102,Female,49,Nurse,6.2,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -103,Male,49,Doctor,8.1,9,85,3,Obese,86,3700,Sleep Apnea,139,91 -104,Female,50,Nurse,6.1,6,90,8,Overweight,75,10000,Insomnia,140,95 -105,Female,50,Engineer,8.3,9,30,3,Normal,65,5000,None,125,80 -106,Female,50,Nurse,6.0,6,90,8,Overweight,75,10000,None,140,95 -107,Female,50,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -108,Female,50,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -109,Female,51,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 -110,Female,51,Nurse,7.1,7,55,6,Normal,72,6000,None,125,82 -111,Female,51,Nurse,6.0,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -112,Female,51,Nurse,6.1,6,90,8,Overweight,75,10000,Sleep Apnea,140,95 -113,Female,52,Accountant,6.5,7,45,7,Overweight,72,6000,Insomnia,130,85 -114,Female,52,Accountant,6.6,7,45,7,Overweight,72,6000,Insomnia,130,85 -115,Female,52,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 -116,Female,53,Engineer,8.3,9,30,3,Normal,65,5000,Insomnia,125,80 -117,Female,53,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 -118,Female,53,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 -119,Female,53,Engineer,8.3,9,30,3,Normal,65,5000,None,125,80 -120,Female,54,Engineer,8.4,9,30,3,Normal,65,5000,None,125,80 -121,Female,54,Engineer,8.5,9,30,3,Normal,65,5000,None,125,80 -122,Female,55,Nurse,8.1,9,75,4,Overweight,72,5000,Sleep Apnea,140,95 -123,Female,56,Doctor,8.2,9,90,3,Normal,65,10000,None,118,75 -124,Female,57,Nurse,8.1,9,75,3,Overweight,68,7000,None,140,95 -125,Female,57,Nurse,8.2,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 -126,Female,57,Nurse,8.1,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 -127,Female,58,Nurse,8.0,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 -128,Female,59,Nurse,8.0,9,75,3,Overweight,68,7000,None,140,95 -129,Female,59,Nurse,8.1,9,75,3,Overweight,68,7000,None,140,95 -130,Female,59,Nurse,8.2,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 -131,Female,59,Nurse,8.0,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 -132,Female,59,Nurse,8.1,9,75,3,Overweight,68,7000,Sleep Apnea,140,95 +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,systolic,diastolic +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,No Disorder,126,83 +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,No Disorder,125,80 +4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea,140,90 +6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia,140,90 +7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia,140,90 +8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,No Disorder,120,80 +14,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,No Disorder,120,80 +17,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Sleep Apnea,132,87 +18,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,Sleep Apnea,120,80 +19,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Insomnia,132,87 +20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +31,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Sleep Apnea,130,86 +32,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Insomnia,130,86 +33,Female,31,Nurse,7.9,8,75,4,Normal,117/76,69,6800,No Disorder,117,76 +34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea,120,80 +51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,No Disorder,120,80 +53,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +67,Male,32,Accountant,7.2,8,50,6,Normal,118/76,68,7000,No Disorder,118,76 +68,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,Insomnia,125,80 +69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,No Disorder,128,85 +71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +75,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea,131,86 +83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,No Disorder,128,84 +85,Male,35,Software Engineer,7.5,8,60,5,Normal,120/80,70,8000,No Disorder,120,80 +86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,No Disorder,125,80 +89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,No Disorder,125,80 +94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia,115,75 +96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea,129,84 +105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea,115,75 +106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia,129,84 +107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,No Disorder,126,83 +108,Male,37,Engineer,7.8,8,70,4,Normal,120/80,68,7000,No Disorder,120,80 +110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +126,Female,37,Nurse,7.5,8,60,4,Normal,120/80,70,8000,No Disorder,120,80 +127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea,130,85 +146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia,130,85 +148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia,132,87 +149,Female,39,Lawyer,6.9,7,50,6,Normal,128/85,75,5500,No Disorder,128,85 +150,Female,39,Accountant,8.0,9,80,3,Normal,115/78,67,7500,No Disorder,115,78 +152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +162,Female,40,Accountant,7.2,8,55,6,Normal,119/77,73,7300,No Disorder,119,77 +164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,No Disorder,130,85 +166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +167,Male,41,Engineer,7.3,8,70,6,Normal,121/79,72,6200,No Disorder,121,79 +168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,No Disorder,125,82 +170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea,130,85 +187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +204,Male,43,Engineer,6.9,6,47,7,Normal,117/76,69,6800,No Disorder,117,76 +205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,No Disorder,122,80 +206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea,130,85 +220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea,130,85 +221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia,130,85 +249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,No Disorder,130,85 +250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,No Disorder,130,85 +251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia,135,90 +253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,No Disorder,135,90 +264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,No Disorder,125,82 +265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia,142,92 +266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,No Disorder,140,95 +269,Female,49,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea,139,91 +279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia,140,95 +280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +281,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,No Disorder,140,95 +282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +283,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +303,Female,51,Nurse,7.1,7,55,6,Normal,125/82,72,6000,No Disorder,125,82 +304,Female,51,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia,125,80 +317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea,140,95 +342,Female,56,Doctor,8.2,9,90,3,Normal,118/75,65,10000,No Disorder,118,75 +344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +353,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +359,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +365,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 diff --git a/notebooks/sleep_health_analysis_veronique.ipynb b/notebooks/sleep_health_analysis_veronique.ipynb new file mode 100644 index 00000000..aac24354 --- /dev/null +++ b/notebooks/sleep_health_analysis_veronique.ipynb @@ -0,0 +1,225 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "92ab6a0f-c295-4fb0-9cdd-6aa0f9c2ec7a", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0631176b-cbaf-4a1d-aacd-6aa66a2e0881", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa23d506-b5b9-4ea4-b835-21af5490c385", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df_clean = pd.read_csv(config['output_data']['file'], encoding='ISO-8859-1')\n", + "sleep_df_clean.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "129d48b9-1550-4014-b808-068e184cba56", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "proportion of obese in sleep apnea\n", + "\"\"\"\n", + "proportion_table_by_bmi = pd.crosstab(sleep_df_clean['bmi_category'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "\n", + "print(\"Proportion of obese per sleep apnea ( %) :\")\n", + "print(proportion_table_by_bmi.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "4affd665-1679-4639-a6e1-d106fa46c8d5", + "metadata": {}, + "source": [ + "# Conclusion H1a: Obesity increases likelihood of sleep apnea\n", + "The table indicates that obese people are more affected by both insomnia and sleep apnea than the rest of the population.\n", + "Furthermore, the data suggests that in this sample, no obese person is entirely free of a sleep disorder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85b7ce64-3827-4e77-a173-1a867f1d4e96", + "metadata": {}, + "outputs": [], + "source": [ + "proportion_table_stress = pd.crosstab(sleep_df_clean['stress_level'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "\n", + "print(\"Proportion of stress per insomnia ( %) :\")\n", + "print(proportion_table_stress.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "2efa62ce-2918-4a5e-8a3f-baf2fc7669b2", + "metadata": {}, + "source": [ + "# Conclusion H1b: Higher stress correlates with insomnia.\n", + "\n", + "This table does not show correlation between higher stress and indomnia. Furthermore, individuals with no sleep disorder have significantly higher stress levels than those with insomnia." + ] + }, + { + "cell_type": "markdown", + "id": "a4d6b24e-4c23-4efd-82d1-557b35fd39f8", + "metadata": {}, + "source": [ + "# To observe the disorder risk for slipping less yhan 6h, we considere:\n", + "bmi_category = obese\n", + "Blood Pressure (systolic/diastolic) > 140/90\n", + "100 < Heart Rate (bpm) < 60\n", + "Sleep Disorder \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bae269b5-d8c0-4478-8cb6-6dc04ad66933", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "Create a temporary column retruning True when sleep apnea then 1or 0 whyit .astype(int)\n", + "sleep_df_clean['has_hypertension'] = (sleep_df_clean['diastolic'] > 90 ).astype(int)\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c6ee18d-76ec-4635-8088-cbfeaf233f0e", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df_clean['has_disorder'] = (\n", + " (sleep_df_clean['diastolic'] > 90) | \n", + " (sleep_df_clean['bmi_category'] == 'obese') | \n", + " (sleep_df_clean['systolic'] > 140) |\n", + " (sleep_df_clean['heart_rate'] > 100) |\n", + " (sleep_df_clean['heart_rate'] < 60) |\n", + " (sleep_df_clean['sleep_disorder'] != 'No Disorder')\n", + " ).astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f70e2bb1-0fd7-46f8-9ddd-e7097efa6dd0", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_duration_sleep = pd.crosstab(sleep_df_clean['sleep_duration'] < 6, sleep_df_clean['has_disorder'] == 1, normalize='index') * 100\n", + "\n", + "print(\"Proportion of duration sleep < 6h increase disorder ( %) :\")\n", + "print(proportion_table_duration_sleep.round(1))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "89cc47fc-2dd1-48af-a10f-3b458772782c", + "metadata": {}, + "source": [ + "# Conclusion H1c: Sleeping <6 hours increases disorder risk.\n", + "There is a correllation between the less sleeping and the disorder because, when i combine all the parametter, the risks is very hi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b8e2151-cd4a-4ab3-991a-99b230b4dbd6", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_physical_activity_level = pd.crosstab(sleep_df_clean['physical_activity_level']<40, sleep_df_clean['has_disorder'] == 1, normalize='index') * 100\n", + "\n", + "print(\"Proportion of physical_activity_level per risk disorder ( %) :\")\n", + "print(proportion_table_physical_activity_level.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "92d4fb68-d70d-4bac-8299-be802cd0d5d1", + "metadata": {}, + "source": [ + "# H1d: Low physical activity (<40 min/day) increases disorder prevalence.\n", + "Their is no correllation between less than 40mi/day of activity and disorder prevalence. Furthumore, doing more does not impact the capability to have desorder. Maybe because when your have health issu, the first medical recommandation is to have sprt activity to maintain your status. This last statement must be verify by another dataset (part of the population with activity with and without desorder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4ac757a5-4476-4734-8c0e-94031e1c4629", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_heart_rate = pd.crosstab(sleep_df_clean['heart_rate'] > 100, sleep_df_clean['sleep_disorder'] == \"Sleep Apnea\", normalize='index') * 100\n", + "\n", + "print(\"Proportion of heart rate< 100 increase sleep apnea ( %) :\")\n", + "print(proportion_table_heart_rate.round(1))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "4c881661-dbea-4909-8300-0dbab1f7f48b", + "metadata": {}, + "source": [ + "# H1e: Hight heart rate (> 100 bpm) does not increases sleep apnea." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sleep_health_project_clean.csv b/notebooks/sleep_health_project_clean.csv deleted file mode 100644 index e9314158..00000000 --- a/notebooks/sleep_health_project_clean.csv +++ /dev/null @@ -1,133 +0,0 @@ -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,systolic,diastolic -1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,No disorder,126,83 -2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,No disorder,125,80 -4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea,140,90 -6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia,140,90 -7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia,140,90 -8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,No disorder,120,80 -14,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,No disorder,120,80 -17,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Sleep Apnea,132,87 -18,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,Sleep Apnea,120,80 -19,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Insomnia,132,87 -20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -31,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Sleep Apnea,130,86 -32,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Insomnia,130,86 -33,Female,31,Nurse,7.9,8,75,4,Normal,117/76,69,6800,No disorder,117,76 -34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No disorder,125,80 -35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea,120,80 -51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,No disorder,120,80 -53,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No disorder,125,80 -54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No disorder,120,80 -63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,No disorder,125,80 -67,Male,32,Accountant,7.2,8,50,6,Normal,118/76,68,7000,No disorder,118,76 -68,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,Insomnia,125,80 -69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,No disorder,128,85 -71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No disorder,125,80 -75,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No disorder,125,80 -81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea,131,86 -83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,No disorder,128,84 -85,Male,35,Software Engineer,7.5,8,60,5,Normal,120/80,70,8000,No disorder,120,80 -86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,No disorder,125,80 -89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,No disorder,125,80 -94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 -95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia,115,75 -96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea,129,84 -105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea,115,75 -106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia,129,84 -107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,No disorder,126,83 -108,Male,37,Engineer,7.8,8,70,4,Normal,120/80,68,7000,No disorder,120,80 -110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,No disorder,130,85 -111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -126,Female,37,Nurse,7.5,8,60,4,Normal,120/80,70,8000,No disorder,120,80 -127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,No disorder,130,85 -128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No disorder,115,75 -138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,No disorder,130,85 -145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea,130,85 -146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 -147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia,130,85 -148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia,132,87 -149,Female,39,Lawyer,6.9,7,50,6,Normal,128/85,75,5500,No disorder,128,85 -150,Female,39,Accountant,8.0,9,80,3,Normal,115/78,67,7500,No disorder,115,78 -152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,No disorder,130,85 -162,Female,40,Accountant,7.2,8,55,6,Normal,119/77,73,7300,No disorder,119,77 -164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,No disorder,130,85 -166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 -167,Male,41,Engineer,7.3,8,70,6,Normal,121/79,72,6200,No disorder,121,79 -168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,No disorder,125,82 -170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,No disorder,130,85 -175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,No disorder,130,85 -178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,No disorder,130,85 -185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea,130,85 -187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 -188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 -204,Male,43,Engineer,6.9,6,47,7,Normal,117/76,69,6800,No disorder,117,76 -205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,No disorder,122,80 -206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,No disorder,130,85 -210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,No disorder,130,85 -219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea,130,85 -220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea,130,85 -221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 -222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 -248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia,130,85 -249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,No disorder,130,85 -250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,No disorder,130,85 -251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia,135,90 -253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 -257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 -262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,No disorder,135,90 -264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,No disorder,125,82 -265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia,142,92 -266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,No disorder,140,95 -269,Female,49,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea,139,91 -279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia,140,95 -280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -281,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,No disorder,140,95 -282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -283,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -303,Female,51,Nurse,7.1,7,55,6,Normal,125/82,72,6000,No disorder,125,82 -304,Female,51,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 -307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 -313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia,125,80 -317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No disorder,125,80 -340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea,140,95 -342,Female,56,Doctor,8.2,9,90,3,Normal,118/75,65,10000,No disorder,118,75 -344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 -345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 -350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 -353,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 -359,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 -360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No disorder,140,95 -361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 -365,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 -367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95