ob = read.csv("D:/5. NCKH 2025-2026/Obesity data.csv")
dim(ob)
## [1] 1217 13
dplyr::slice_head(ob, n = 6)
## id gender height weight bmi age WBBMC wbbmd fat lean pcfat hypertension
## 1 1 F 150 49 21.8 53 1312 0.88 17802 28600 37.3 0
## 2 2 M 165 52 19.1 65 1309 0.84 8381 40229 16.8 1
## 3 3 F 157 57 23.1 64 1230 0.84 19221 36057 34.0 1
## 4 4 F 156 53 21.8 56 1171 0.80 17472 33094 33.8 1
## 5 5 M 160 51 19.9 54 1681 0.98 7336 40621 14.8 0
## 6 6 F 153 47 20.1 52 1358 0.91 14904 30068 32.2 1
## diabetes
## 1 1
## 2 0
## 3 0
## 4 0
## 5 0
## 6 0
tail(ob, 6) # Hiển thị 6 quan sát cuối cùng
## id gender height weight bmi age WBBMC wbbmd fat lean pcfat
## 1212 1222 F 153 50 21.4 59 1309 0.87 18328 29147 37.6
## 1213 1223 F 150 44 19.6 44 1474 0.95 12906 28534 30.1
## 1214 1224 F 148 51 23.3 58 1522 0.97 14938 33931 29.6
## 1215 1225 F 149 50 22.5 57 1409 0.93 16777 30598 34.4
## 1216 1226 F 144 49 23.6 67 1266 0.90 20094 27272 41.3
## 1217 1227 F 141 45 22.6 58 1228 0.91 14567 28111 33.2
## hypertension diabetes
## 1212 1 0
## 1213 0 1
## 1214 0 0
## 1215 1 0
## 1216 1 0
## 1217 0 0
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
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"),
ordered_result = TRUE)
ob$fat.kg <- ob$weight * ob$pcfat / 100
ob$lean.kg <- ob$weight - ob$fat.kg
men.overweight <- subset(ob, gender == "Male" & bmi >= 25)
Demo <- ob[, c("id", "age", "gender", "height", "weight", "pcfat")]