DOC DU LIEU

## Warning: package 'readxl' was built under R version 4.5.1
## # A tibble: 6 × 13
##   `Student ID`   Age Gender Height Weight `Blood Type`   BMI Temperature
##          <dbl> <dbl> <chr>   <dbl>  <dbl> <chr>        <dbl>       <dbl>
## 1            1    18 Female   162.   72.4 O             27.6        NA  
## 2            2    NA Male     152.   47.6 B             NA          98.7
## 3            3    32 Female   183.   55.7 A             16.7        98.3
## 4           NA    30 Male     182.   63.3 B             19.1        98.8
## 5            5    23 Female    NA    46.2 O             NA          98.5
## 6            6    32 <NA>     151.   68.6 B             29.9        99.7
## # ℹ 5 more variables: `Heart Rate` <dbl>, `Blood Pressure` <dbl>,
## #   Cholesterol <dbl>, Diabetes <chr>, Smoking <chr>
dim(dataset)
## [1] 200000     13
names(dataset)
##  [1] "Student ID"     "Age"            "Gender"         "Height"        
##  [5] "Weight"         "Blood Type"     "BMI"            "Temperature"   
##  [9] "Heart Rate"     "Blood Pressure" "Cholesterol"    "Diabetes"      
## [13] "Smoking"
sum(duplicated(dataset))
## [1] 7644
colSums(is.na(dataset))
##     Student ID            Age         Gender         Height         Weight 
##          20000          20000          20000          20000          20000 
##     Blood Type            BMI    Temperature     Heart Rate Blood Pressure 
##          20000          20000          20000          20000          20000 
##    Cholesterol       Diabetes        Smoking 
##          20000          20000          20000
variable_meaning <- data.frame(
  Variable = c(
    "Student.ID",
    "Age",
    "Gender",
    "Height",
    "Weight",
    "Blood.Type",
    "BMI",
    "Temperature",
    "Heart.Rate",
    "Blood.Pressure",
    "Cholesterol",
    "Diabetes",
    "Smoking"
  ),
  Meaning = c(
    "Mã số học sinh/bệnh nhân",
    "Tuổi (năm)",
    "Giới tính (Male/Female)",
    "Chiều cao (cm)",
    "Cân nặng (kg)",
    "Nhóm máu (A, B, AB, O)",
    "Chỉ số BMI (khối lượng cơ thể)",
    "Nhiệt độ cơ thể (°C)",
    "Nhịp tim (bpm)",
    "Huyết áp (mmHg)",
    "Cholesterol (mg/dL)",
    "Tình trạng tiểu đường (Yes/No hoặc 1/0)",
    "Tình trạng hút thuốc (Yes/No hoặc lịch sử hút thuốc)"
  ),
  stringsAsFactors = FALSE
)

library(knitr)
## Warning: package 'knitr' was built under R version 4.5.1
kable(variable_meaning, booktabs = TRUE)
Variable Meaning
Student.ID Mã số học sinh/bệnh nhân
Age Tuổi (năm)
Gender Giới tính (Male/Female)
Height Chiều cao (cm)
Weight Cân nặng (kg)
Blood.Type Nhóm máu (A, B, AB, O)
BMI Chỉ số BMI (khối lượng cơ thể)
Temperature Nhiệt độ cơ thể (°C)
Heart.Rate Nhịp tim (bpm)
Blood.Pressure Huyết áp (mmHg)
Cholesterol Cholesterol (mg/dL)
Diabetes Tình trạng tiểu đường (Yes/No hoặc 1/0)
Smoking Tình trạng hút thuốc (Yes/No hoặc lịch sử hút thuốc) 
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.5.1
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
bloodtype_O_data <- dataset %>%
  dplyr::filter("Blood Type" == "O")

head(bloodtype_O_data)
## # A tibble: 0 × 13
## # ℹ 13 variables: Student ID <dbl>, Age <dbl>, Gender <chr>, Height <dbl>,
## #   Weight <dbl>, Blood Type <chr>, BMI <dbl>, Temperature <dbl>,
## #   Heart Rate <dbl>, Blood Pressure <dbl>, Cholesterol <dbl>, Diabetes <chr>,
## #   Smoking <chr>
install.packages("dplyr")
## Warning: package 'dplyr' is in use and will not be installed
female_data <- dataset %>%
  dplyr::filter(Gender == "Female")
head(female_data)
## # A tibble: 6 × 13
##   `Student ID`   Age Gender Height Weight `Blood Type`   BMI Temperature
##          <dbl> <dbl> <chr>   <dbl>  <dbl> <chr>        <dbl>       <dbl>
## 1            1    18 Female   162.   72.4 O             27.6        NA  
## 2            3    32 Female   183.   55.7 A             16.7        98.3
## 3            5    23 Female    NA    46.2 O             NA          98.5
## 4           11    28 Female   153.   73.6 B             31.4        98.4
## 5           12    34 Female   182.   76.4 AB            23.0        98.1
## 6           19    31 Female   159.   46.8 AB            18.6        98.8
## # ℹ 5 more variables: `Heart Rate` <dbl>, `Blood Pressure` <dbl>,
## #   Cholesterol <dbl>, Diabetes <chr>, Smoking <chr>
age_stats <- c(
  Min = min(dataset$Age, na.rm = TRUE),
  Max = max(dataset$Age, na.rm = TRUE),
  Mean = mean(dataset$Age, na.rm = TRUE),
  Median = median(dataset$Age, na.rm = TRUE),
  SD = sd(dataset$Age, na.rm = TRUE),
  Var = var(dataset$Age, na.rm = TRUE)
)
age_stats
##       Min       Max      Mean    Median        SD       Var 
## 18.000000 34.000000 26.021561 26.000000  4.890528 23.917262
bmi_stats <- c(
  Min = min(dataset$BMI, na.rm = TRUE),
  Max = max(dataset$BMI, na.rm = TRUE),
  Mean = mean(dataset$BMI, na.rm = TRUE),
  Median = median(dataset$BMI, na.rm = TRUE),
  SD = sd(dataset$BMI, na.rm = TRUE),
  Var = var(dataset$BMI, na.rm = TRUE)
)
bmi_stats
##       Min       Max      Mean    Median        SD       Var 
## 10.074837 44.355113 23.338869 22.671401  7.033554 49.470878

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