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# Print the mtcars data set\
mtcars# Use the question mark to get information about the data set
?mtcarsData_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"
[10] "gear" "carb"# Menampilkan fungsi rownames() untuk mendapatkan nama tiap baris di kolom pertama, yang merupakan nama tiap mobil :
Data_Cars <- mtcars
rownames(Data_Cars) [1] "Mazda RX4" "Mazda RX4 Wag"
[3] "Datsun 710" "Hornet 4 Drive"
[5] "Hornet Sportabout" "Valiant"
[7] "Duster 360" "Merc 240D"
[9] "Merc 230" "Merc 280"
[11] "Merc 280C" "Merc 450SE"
[13] "Merc 450SL" "Merc 450SLC"
[15] "Cadillac Fleetwood" "Lincoln Continental"
[17] "Chrysler Imperial" "Fiat 128"
[19] "Honda Civic" "Toyota Corolla"
[21] "Toyota Corona" "Dodge Challenger"
[23] "AMC Javelin" "Camaro Z28"
[25] "Pontiac Firebird" "Fiat X1-9"
[27] "Porsche 914-2" "Lotus Europa"
[29] "Ford Pantera L" "Ferrari Dino"
[31] "Maserati Bora" "Volvo 142E" # Jika Kita ingin mencetak semua nilai yang dimiliki variabel, akses bingkai data dengan menggunakan tanda $, dan nama variabel (misalnya cyl (silinder)) :
Data_Cars <- mtcars
Data_Cars$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# Fungsi sort() untuk mensorting data
Data_Cars <- mtcars
sort(Data_Cars$cyl) [1] 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8# Kita dapat menggunakan fungsi summary() untuk mendapatkan ringkasan statistik dari data
Data_Cars <- mtcars
summary(Data_Cars) mpg cyl disp hp
Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0
1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5
Median :19.20 Median :6.000 Median :196.3 Median :123.0
Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7
3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0
Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0
drat wt qsec vs
Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
Median :3.695 Median :3.325 Median :17.71 Median :0.0000
Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
am gear carb
Min. :0.0000 Min. :3.000 Min. :1.000
1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
Median :0.0000 Median :4.000 Median :2.000
Mean :0.4062 Mean :3.688 Mean :2.812
3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
Max. :1.0000 Max. :5.000 Max. :8.000 # Menemukan nilai terbesar dan terkecil dari variabel hp (hourse power) :
Data_Cars <- mtcars
max(Data_Cars$hp)[1] 335min(Data_Cars$hp)[1] 52# Kita dapat menggunakan fungsi which.max() dan which.min() untuk menemukan posisi index dari nilai max dan min dalam table :
Data_Cars <- mtcars
which.max(Data_Cars$hp)[1] 31which.min(Data_Cars$hp)[1] 19# Kita dapat menggabungkan fungsi which.max() dan which.min() dengan fungsi rownames() untuk mendapatkan nama mobil dengan tenaga kuda terbesar dan terkecil :
Data_Cars <- mtcars
rownames(Data_Cars)[which.max(Data_Cars$hp)][1] "Maserati Bora"rownames(Data_Cars)[which.min(Data_Cars$hp)][1] "Honda Civic"# Menemukan rata-rata dari berat (wt) sebuah mobil :
Data_Cars <- mtcars
mean(Data_Cars$wt)[1] 3.21725# Menemukan nilai tengah dari berat (wt) sebuah mobil:
Data_Cars <- mtcars
median(Data_Cars$wt)[1] 3.325# Menemukan nilai mode dari berat (wt) sebuah mobil :
Data_Cars <- mtcars
names(sort(-table(Data_Cars$wt)))[1][1] "3.44"# 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 Add a new chunk by clicking the Insert Chunk button on the toolbar or by pressing Ctrl+Alt+I.
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