# Print the mtcars data set\
mtcars
# Use the question mark to get information about the data set
?mtcars
## starting httpd help server ... done
Data_Cars <- mtcars
# Use dim() to find the dimension of the data set
dim(Data_Cars)
## [1] 32 11
# Use names() to find the names of the variables from the data set
names(Data_Cars)
## [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"
## [11] "carb"
#Menemukan nilai terbesar dan terkecil dari variabel hp (hourse power).:
Data_Cars <- mtcars
rownames(Data_Cars)
## [1] "Mazda RX4" "Mazda RX4 Wag" "Datsun 710"
## [4] "Hornet 4 Drive" "Hornet Sportabout" "Valiant"
## [7] "Duster 360" "Merc 240D" "Merc 230"
## [10] "Merc 280" "Merc 280C" "Merc 450SE"
## [13] "Merc 450SL" "Merc 450SLC" "Cadillac Fleetwood"
## [16] "Lincoln Continental" "Chrysler Imperial" "Fiat 128"
## [19] "Honda Civic" "Toyota Corolla" "Toyota Corona"
## [22] "Dodge Challenger" "AMC Javelin" "Camaro Z28"
## [25] "Pontiac Firebird" "Fiat X1-9" "Porsche 914-2"
## [28] "Lotus Europa" "Ford Pantera L" "Ferrari Dino"
## [31] "Maserati Bora" "Volvo 142E"
#Kita dapat menggunakan fungsi which.max() dan which.min() untuk menemukan posisi index dari nilai max dan min dalam table:
Data_Cars <- mtcars
Data_Cars$cyl
## [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
#Kita dapat menggabungkan fungsi which.max() dan which.min() dengan fungsi rownames() untuk mendapatkan nama mobil dengan tenaga kuda terbesar dan terkecil:
Data_Cars <- mtcars
sort(Data_Cars$cyl)
## [1] 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8
Data_Cars <- mtcars
summary(Data_Cars)
## mpg cyl disp hp
## Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0
## 1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5
## Median :19.20 Median :6.000 Median :196.3 Median :123.0
## Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7
## 3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0
## Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0
## drat wt qsec vs
## Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
## 1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
## Median :3.695 Median :3.325 Median :17.71 Median :0.0000
## Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
## 3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
## Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
## am gear carb
## Min. :0.0000 Min. :3.000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
## Median :0.0000 Median :4.000 Median :2.000
## Mean :0.4062 Mean :3.688 Mean :2.812
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :8.000
MIN MAX
Data_Cars <- mtcars
max(Data_Cars$hp)
## [1] 335
min(Data_Cars$hp)
## [1] 52
Data_Cars <- mtcars
which.max(Data_Cars$hp)
## [1] 31
which.min(Data_Cars$hp)
## [1] 19
Data_Cars <- mtcars
rownames(Data_Cars)[which.max(Data_Cars$hp)]
## [1] "Maserati Bora"
rownames(Data_Cars)[which.min(Data_Cars$hp)]
## [1] "Honda Civic"
R PERCENTILES
#Menemukan Berapa 75.persentil dari berat mobil? Jawabannya adalah 3,61 atau 3.610 lbs,artinya 75% atau berat mobil 3.610 lbs atau kurang:
Data_Cars <- mtcars
# c() specifies which percentile you want
quantile(Data_Cars$wt, c(0.75))
## 75%
## 3.61
#Jika menjalankan fungsi quantile() tanpa menentukan parameter c(), akan didapatkan persentil 0, 25, 50, 75, dan 100:
Data_Cars <- mtcars
quantile(Data_Cars$wt)
## 0% 25% 50% 75% 100%
## 1.51300 2.58125 3.32500 3.61000 5.42400