library(lessR);
##
## lessR 4.4.5 feedback: gerbing@pdx.edu
## --------------------------------------------------------------
## > d <- Read("") Read data file, many formats available, e.g., Excel
## d is default data frame, data= in analysis routines optional
##
## Many examples of reading, writing, and manipulating data,
## graphics, testing means and proportions, regression, factor analysis,
## customization, forecasting, and aggregation from pivot tables
## Enter: browseVignettes("lessR")
##
## View lessR updates, now including time series forecasting
## Enter: news(package="lessR")
##
## Interactive data analysis
## Enter: interact()
library(table1)
##
## Attaching package: 'table1'
## The following object is masked from 'package:lessR':
##
## label
## The following objects are masked from 'package:base':
##
## units, units<-
library(lessR)
library(readr)
Obesity_data <- read_csv("C:/Users/DELL/Downloads/Obesity data.csv")
## Rows: 1217 Columns: 13
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): gender
## dbl (12): id, height, weight, bmi, age, WBBMC, wbbmd, fat, lean, pcfat, hype...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
View(Obesity_data)
ob=Obesity_data
View(ob)
# Xem số quan sát (số dòng)
nrow(ob)
## [1] 1217
# Xem số biến (số cột)
ncol(ob)
## [1] 13
# Hoặc kết hợp lại
dim(ob)
## [1] 1217 13
head(ob, 6)
## # A tibble: 6 × 13
## id gender height weight bmi age WBBMC wbbmd fat lean pcfat
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 F 150 49 21.8 53 1312 0.88 17802 28600 37.3
## 2 2 M 165 52 19.1 65 1309 0.84 8381 40229 16.8
## 3 3 F 157 57 23.1 64 1230 0.84 19221 36057 34
## 4 4 F 156 53 21.8 56 1171 0.8 17472 33094 33.8
## 5 5 M 160 51 19.9 54 1681 0.98 7336 40621 14.8
## 6 6 F 153 47 20.1 52 1358 0.91 14904 30068 32.2
## # ℹ 2 more variables: hypertension <dbl>, diabetes <dbl>
tail(ob, 6)
## # A tibble: 6 × 13
## id gender height weight bmi age WBBMC wbbmd fat lean pcfat
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1222 F 153 50 21.4 59 1309 0.87 18328 29147 37.6
## 2 1223 F 150 44 19.6 44 1474 0.95 12906 28534 30.1
## 3 1224 F 148 51 23.3 58 1522 0.97 14938 33931 29.6
## 4 1225 F 149 50 22.5 57 1409 0.93 16777 30598 34.4
## 5 1226 F 144 49 23.6 67 1266 0.9 20094 27272 41.3
## 6 1227 F 141 45 22.6 58 1228 0.91 14567 28111 33.2
## # ℹ 2 more variables: hypertension <dbl>, diabetes <dbl>
summary(ob)
## id gender height weight
## Min. : 1.0 Length:1217 Min. :136.0 Min. :34.00
## 1st Qu.: 309.0 Class :character 1st Qu.:151.0 1st Qu.:49.00
## Median : 615.0 Mode :character Median :155.0 Median :54.00
## Mean : 614.5 Mean :156.7 Mean :55.14
## 3rd Qu.: 921.0 3rd Qu.:162.0 3rd Qu.:61.00
## Max. :1227.0 Max. :185.0 Max. :95.00
## bmi age WBBMC wbbmd fat
## Min. :14.5 Min. :13.00 Min. : 695 Min. :0.650 Min. : 4277
## 1st Qu.:20.2 1st Qu.:35.00 1st Qu.:1481 1st Qu.:0.930 1st Qu.:13768
## Median :22.2 Median :48.00 Median :1707 Median :1.010 Median :16955
## Mean :22.4 Mean :47.15 Mean :1725 Mean :1.009 Mean :17288
## 3rd Qu.:24.3 3rd Qu.:58.00 3rd Qu.:1945 3rd Qu.:1.090 3rd Qu.:20325
## Max. :37.1 Max. :88.00 Max. :3040 Max. :1.350 Max. :40825
## lean pcfat hypertension diabetes
## Min. :19136 Min. : 9.2 Min. :0.000 Min. :0.0000
## 1st Qu.:30325 1st Qu.:27.0 1st Qu.:0.000 1st Qu.:0.0000
## Median :33577 Median :32.4 Median :1.000 Median :0.0000
## Mean :35463 Mean :31.6 Mean :0.507 Mean :0.1109
## 3rd Qu.:39761 3rd Qu.:36.8 3rd Qu.:1.000 3rd Qu.:0.0000
## Max. :63059 Max. :48.4 Max. :1.000 Max. :1.0000
#viec5
ob$Sex <-ifelse(ob$gender == "F", 1, 0)
ob$obese <- cut(
ob$bmi,
breaks = c(-Inf, 18.5, 25, 30, Inf),
labels = c("Underweight", "Normal", "Overweight", "Obese"),
right = FALSE # để khoảng [18.5, 25.0) đúng như bạn yêu cầu
)
#viec5.3
ob$fat.kg <- ob$weight * ob$pcfat / 100
ob$lean.kg <- ob$weight - ob$fat.kg
#viec5.4
# Kiểm tra tên biến gender trong dữ liệu
unique(ob$gender)
## [1] "F" "M"
# Lọc ra nam giới với BMI >= 25.0
men.overweight <- subset(ob, gender == "M" & bmi >= 25.0)
# Hoặc nếu biến gender là "Male", bạn chỉnh lại
# men.overweight <- subset(ob, gender == "Male" & bmi >= 25.0)
dim(men.overweight)
## [1] 85 17
#viec5.5
Demo <- ob[, c("id", "age", "gender", "height", "weight", "pcfat")]