library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.4.2## Warning: package 'ggplot2' was built under R version 4.4.2## Warning: package 'tibble' was built under R version 4.4.2## Warning: package 'tidyr' was built under R version 4.4.2## Warning: package 'readr' was built under R version 4.4.2## Warning: package 'purrr' was built under R version 4.4.2## Warning: package 'dplyr' was built under R version 4.4.2## Warning: package 'stringr' was built under R version 4.4.2## Warning: package 'forcats' was built under R version 4.4.2## Warning: package 'lubridate' was built under R version 4.4.2## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors?tidyverse## starting httpd help server ... done#DATA MTCARS
library(datasets)
data("mtcars")
mtcars## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2#SUMMARISE
summary <- mtcars %>% summarize(mean(mpg))
summary## mean(mpg)
## 1 20.09062#####menghitung rata-rata mpg (miles per gallon)
summary <- mtcars %>% summarize(mean(qsec))
summary## mean(qsec)
## 1 17.84875#####menghitung rata-rata qsec (quarter mile second)
#ARRANGE
mtcars %>% arrange (hp)## mpg cyl disp hp drat wt qsec vs am gear carb
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8#####mengurutkan dari hp (horsepower) paling rendah
mtcars %>% arrange(desc(hp))## mpg cyl disp hp drat wt qsec vs am gear carb
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2#####mengurutkan dari hp (horsepower) paling tinggi
#FILTER
filtered_mtcars <- filter(mtcars, qsec < mean(qsec))
head(filtered_mtcars)## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3#####menyaring data berdasarkan kategori qsec yang bernilai di bawah rata-rata
#MUTATE
mpq <- mtcars %>% mutate(mpg_per_qsec = mpg/qsec)
mpq## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
## mpg_per_qsec
## Mazda RX4 1.2758202
## Mazda RX4 Wag 1.2338425
## Datsun 710 1.2251478
## Hornet 4 Drive 1.1008230
## Hornet Sportabout 1.0987074
## Valiant 0.8951533
## Duster 360 0.9027778
## Merc 240D 1.2200000
## Merc 230 0.9956332
## Merc 280 1.0491803
## Merc 280C 0.9417989
## Merc 450SE 0.9425287
## Merc 450SL 0.9829545
## Merc 450SLC 0.8444444
## Cadillac Fleetwood 0.5784205
## Lincoln Continental 0.5836139
## Chrysler Imperial 0.8438576
## Fiat 128 1.6640986
## Honda Civic 1.6414687
## Toyota Corolla 1.7035176
## Toyota Corona 1.0744628
## Dodge Challenger 0.9187908
## AMC Javelin 0.8786127
## Camaro Z28 0.8630759
## Pontiac Firebird 1.1260997
## Fiat X1-9 1.4444444
## Porsche 914-2 1.5568862
## Lotus Europa 1.7988166
## Ford Pantera L 1.0896552
## Ferrari Dino 1.2709677
## Maserati Bora 1.0273973
## Volvo 142E 1.1505376#####menghitung hubungan efisiensi kinerja bahan bakar dengan kecepatan akselerasi
#SELECT
mtcars %>% select(mpg,hp,qsec)## mpg hp qsec
## Mazda RX4 21.0 110 16.46
## Mazda RX4 Wag 21.0 110 17.02
## Datsun 710 22.8 93 18.61
## Hornet 4 Drive 21.4 110 19.44
## Hornet Sportabout 18.7 175 17.02
## Valiant 18.1 105 20.22
## Duster 360 14.3 245 15.84
## Merc 240D 24.4 62 20.00
## Merc 230 22.8 95 22.90
## Merc 280 19.2 123 18.30
## Merc 280C 17.8 123 18.90
## Merc 450SE 16.4 180 17.40
## Merc 450SL 17.3 180 17.60
## Merc 450SLC 15.2 180 18.00
## Cadillac Fleetwood 10.4 205 17.98
## Lincoln Continental 10.4 215 17.82
## Chrysler Imperial 14.7 230 17.42
## Fiat 128 32.4 66 19.47
## Honda Civic 30.4 52 18.52
## Toyota Corolla 33.9 65 19.90
## Toyota Corona 21.5 97 20.01
## Dodge Challenger 15.5 150 16.87
## AMC Javelin 15.2 150 17.30
## Camaro Z28 13.3 245 15.41
## Pontiac Firebird 19.2 175 17.05
## Fiat X1-9 27.3 66 18.90
## Porsche 914-2 26.0 91 16.70
## Lotus Europa 30.4 113 16.90
## Ford Pantera L 15.8 264 14.50
## Ferrari Dino 19.7 175 15.50
## Maserati Bora 15.0 335 14.60
## Volvo 142E 21.4 109 18.60#####memilih mobil berdasarkan kategori mpg, hp, qsec
#DUA FUNGSI
duafungsi1 <- mtcars %>%
filter(mpg > mean(mpg)) %>%
arrange(desc(mpg))
duafungsi1## mpg cyl disp hp drat wt qsec vs am gear carb
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4#####menyaring data berdasarkan kategori mpg yang lebih dari rata-rata, lalu mengurutkan dari mpg paling tinggi
duafungsi2 <- mtcars %>%
mutate(mpg_per_qsec = mpg/qsec) %>%
select(hp, mpg, qsec, mpg_per_qsec)
duafungsi2## hp mpg qsec mpg_per_qsec
## Mazda RX4 110 21.0 16.46 1.2758202
## Mazda RX4 Wag 110 21.0 17.02 1.2338425
## Datsun 710 93 22.8 18.61 1.2251478
## Hornet 4 Drive 110 21.4 19.44 1.1008230
## Hornet Sportabout 175 18.7 17.02 1.0987074
## Valiant 105 18.1 20.22 0.8951533
## Duster 360 245 14.3 15.84 0.9027778
## Merc 240D 62 24.4 20.00 1.2200000
## Merc 230 95 22.8 22.90 0.9956332
## Merc 280 123 19.2 18.30 1.0491803
## Merc 280C 123 17.8 18.90 0.9417989
## Merc 450SE 180 16.4 17.40 0.9425287
## Merc 450SL 180 17.3 17.60 0.9829545
## Merc 450SLC 180 15.2 18.00 0.8444444
## Cadillac Fleetwood 205 10.4 17.98 0.5784205
## Lincoln Continental 215 10.4 17.82 0.5836139
## Chrysler Imperial 230 14.7 17.42 0.8438576
## Fiat 128 66 32.4 19.47 1.6640986
## Honda Civic 52 30.4 18.52 1.6414687
## Toyota Corolla 65 33.9 19.90 1.7035176
## Toyota Corona 97 21.5 20.01 1.0744628
## Dodge Challenger 150 15.5 16.87 0.9187908
## AMC Javelin 150 15.2 17.30 0.8786127
## Camaro Z28 245 13.3 15.41 0.8630759
## Pontiac Firebird 175 19.2 17.05 1.1260997
## Fiat X1-9 66 27.3 18.90 1.4444444
## Porsche 914-2 91 26.0 16.70 1.5568862
## Lotus Europa 113 30.4 16.90 1.7988166
## Ford Pantera L 264 15.8 14.50 1.0896552
## Ferrari Dino 175 19.7 15.50 1.2709677
## Maserati Bora 335 15.0 14.60 1.0273973
## Volvo 142E 109 21.4 18.60 1.1505376#####menghitung hubungan efisiensi kinerja bahan bakar dengan kecepatan akselerasi, lalu memilih data berdasarkan kategori hp, mpg, qsec