library(ggplot2)
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library(tidyverse)
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## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ lubridate 1.9.4 ✔ tibble 3.2.1
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library(dplyr)
data(mtcars)
glimpse(mtcars)
## Rows: 32
## Columns: 11
## $ mpg <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,…
## $ cyl <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,…
## $ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16…
## $ hp <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180…
## $ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,…
## $ wt <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.…
## $ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18…
## $ vs <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,…
## $ am <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,…
## $ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,…
## $ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,…
summary(mtcars)
## 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
mtcars2 = within(mtcars, {
vs = factor(vs,labels = c("V","S"))
am = factor (am,labels = c("automatic","manual"))
cyl = ordered(cyl)
gear = ordered(gear)
carb = ordered(carb)
})
mtcars2 %>%
filter (am=="automatic")
## mpg cyl disp hp drat wt qsec vs am gear carb
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 S automatic 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 V automatic 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 S automatic 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 V automatic 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 S automatic 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 S automatic 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 S automatic 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 S automatic 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 V automatic 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 V automatic 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 V automatic 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 V automatic 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 V automatic 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 V automatic 3 4
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 S automatic 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 V automatic 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 V automatic 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 V automatic 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 V automatic 3 2
summary(mtcars2)
## mpg cyl disp hp drat
## Min. :10.40 4:11 Min. : 71.1 Min. : 52.0 Min. :2.760
## 1st Qu.:15.43 6: 7 1st Qu.:120.8 1st Qu.: 96.5 1st Qu.:3.080
## Median :19.20 8:14 Median :196.3 Median :123.0 Median :3.695
## Mean :20.09 Mean :230.7 Mean :146.7 Mean :3.597
## 3rd Qu.:22.80 3rd Qu.:326.0 3rd Qu.:180.0 3rd Qu.:3.920
## Max. :33.90 Max. :472.0 Max. :335.0 Max. :4.930
## wt qsec vs am gear carb
## Min. :1.513 Min. :14.50 V:18 automatic:19 3:15 1: 7
## 1st Qu.:2.581 1st Qu.:16.89 S:14 manual :13 4:12 2:10
## Median :3.325 Median :17.71 5: 5 3: 3
## Mean :3.217 Mean :17.85 4:10
## 3rd Qu.:3.610 3rd Qu.:18.90 6: 1
## Max. :5.424 Max. :22.90 8: 1
mtcars2 %>%
filter(cyl == 4)%>%
arrange(wt)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 S manual 5 2
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 S manual 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 S manual 4 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 S manual 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 V manual 5 2
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 S manual 4 1
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 S manual 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 S automatic 3 1
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 S manual 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 S automatic 4 2
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 S automatic 4 2
mtcars2 %>%
filter(mpg > 20) %>%
arrange(hp)%>%
head()
## 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 S manual 4 2
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 S automatic 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 S manual 4 1
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 S manual 4 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 S manual 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 V manual 5 2
mtcars2 %>%
filter(between(mpg, 15, 25))
## 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 V manual 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 V manual 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 S manual 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 S automatic 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 V automatic 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 S automatic 3 1
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 S automatic 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 S automatic 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 S automatic 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 S automatic 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 V automatic 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 V automatic 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 V automatic 3 3
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 S automatic 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 V automatic 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 V automatic 3 2
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 V automatic 3 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 V manual 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 V manual 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 V manual 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 S manual 4 2
mtcars2 %>%
select(cyl,wt,am)
## cyl wt am
## Mazda RX4 6 2.620 manual
## Mazda RX4 Wag 6 2.875 manual
## Datsun 710 4 2.320 manual
## Hornet 4 Drive 6 3.215 automatic
## Hornet Sportabout 8 3.440 automatic
## Valiant 6 3.460 automatic
## Duster 360 8 3.570 automatic
## Merc 240D 4 3.190 automatic
## Merc 230 4 3.150 automatic
## Merc 280 6 3.440 automatic
## Merc 280C 6 3.440 automatic
## Merc 450SE 8 4.070 automatic
## Merc 450SL 8 3.730 automatic
## Merc 450SLC 8 3.780 automatic
## Cadillac Fleetwood 8 5.250 automatic
## Lincoln Continental 8 5.424 automatic
## Chrysler Imperial 8 5.345 automatic
## Fiat 128 4 2.200 manual
## Honda Civic 4 1.615 manual
## Toyota Corolla 4 1.835 manual
## Toyota Corona 4 2.465 automatic
## Dodge Challenger 8 3.520 automatic
## AMC Javelin 8 3.435 automatic
## Camaro Z28 8 3.840 automatic
## Pontiac Firebird 8 3.845 automatic
## Fiat X1-9 4 1.935 manual
## Porsche 914-2 4 2.140 manual
## Lotus Europa 4 1.513 manual
## Ford Pantera L 8 3.170 manual
## Ferrari Dino 6 2.770 manual
## Maserati Bora 8 3.570 manual
## Volvo 142E 4 2.780 manual
mtcars2 %>%
select(where(is.character))
## data frame with 0 columns and 32 rows
mtcars2 %>%
select(where(is.factor))
## cyl vs am gear carb
## Mazda RX4 6 V manual 4 4
## Mazda RX4 Wag 6 V manual 4 4
## Datsun 710 4 S manual 4 1
## Hornet 4 Drive 6 S automatic 3 1
## Hornet Sportabout 8 V automatic 3 2
## Valiant 6 S automatic 3 1
## Duster 360 8 V automatic 3 4
## Merc 240D 4 S automatic 4 2
## Merc 230 4 S automatic 4 2
## Merc 280 6 S automatic 4 4
## Merc 280C 6 S automatic 4 4
## Merc 450SE 8 V automatic 3 3
## Merc 450SL 8 V automatic 3 3
## Merc 450SLC 8 V automatic 3 3
## Cadillac Fleetwood 8 V automatic 3 4
## Lincoln Continental 8 V automatic 3 4
## Chrysler Imperial 8 V automatic 3 4
## Fiat 128 4 S manual 4 1
## Honda Civic 4 S manual 4 2
## Toyota Corolla 4 S manual 4 1
## Toyota Corona 4 S automatic 3 1
## Dodge Challenger 8 V automatic 3 2
## AMC Javelin 8 V automatic 3 2
## Camaro Z28 8 V automatic 3 4
## Pontiac Firebird 8 V automatic 3 2
## Fiat X1-9 4 S manual 4 1
## Porsche 914-2 4 V manual 5 2
## Lotus Europa 4 S manual 5 2
## Ford Pantera L 8 V manual 5 4
## Ferrari Dino 6 V manual 5 6
## Maserati Bora 8 V manual 5 8
## Volvo 142E 4 S manual 4 2
mtcars2 %>%
select(where(is.numeric))
## mpg disp hp drat wt qsec
## Mazda RX4 21.0 160.0 110 3.90 2.620 16.46
## Mazda RX4 Wag 21.0 160.0 110 3.90 2.875 17.02
## Datsun 710 22.8 108.0 93 3.85 2.320 18.61
## Hornet 4 Drive 21.4 258.0 110 3.08 3.215 19.44
## Hornet Sportabout 18.7 360.0 175 3.15 3.440 17.02
## Valiant 18.1 225.0 105 2.76 3.460 20.22
## Duster 360 14.3 360.0 245 3.21 3.570 15.84
## Merc 240D 24.4 146.7 62 3.69 3.190 20.00
## Merc 230 22.8 140.8 95 3.92 3.150 22.90
## Merc 280 19.2 167.6 123 3.92 3.440 18.30
## Merc 280C 17.8 167.6 123 3.92 3.440 18.90
## Merc 450SE 16.4 275.8 180 3.07 4.070 17.40
## Merc 450SL 17.3 275.8 180 3.07 3.730 17.60
## Merc 450SLC 15.2 275.8 180 3.07 3.780 18.00
## Cadillac Fleetwood 10.4 472.0 205 2.93 5.250 17.98
## Lincoln Continental 10.4 460.0 215 3.00 5.424 17.82
## Chrysler Imperial 14.7 440.0 230 3.23 5.345 17.42
## Fiat 128 32.4 78.7 66 4.08 2.200 19.47
## Honda Civic 30.4 75.7 52 4.93 1.615 18.52
## Toyota Corolla 33.9 71.1 65 4.22 1.835 19.90
## Toyota Corona 21.5 120.1 97 3.70 2.465 20.01
## Dodge Challenger 15.5 318.0 150 2.76 3.520 16.87
## AMC Javelin 15.2 304.0 150 3.15 3.435 17.30
## Camaro Z28 13.3 350.0 245 3.73 3.840 15.41
## Pontiac Firebird 19.2 400.0 175 3.08 3.845 17.05
## Fiat X1-9 27.3 79.0 66 4.08 1.935 18.90
## Porsche 914-2 26.0 120.3 91 4.43 2.140 16.70
## Lotus Europa 30.4 95.1 113 3.77 1.513 16.90
## Ford Pantera L 15.8 351.0 264 4.22 3.170 14.50
## Ferrari Dino 19.7 145.0 175 3.62 2.770 15.50
## Maserati Bora 15.0 301.0 335 3.54 3.570 14.60
## Volvo 142E 21.4 121.0 109 4.11 2.780 18.60
mtcars2 %>%
mutate(weight_kg = wt*1000*0.45)%>%
select(everything())
## 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 V manual 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 V manual 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 S manual 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 S automatic 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 V automatic 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 S automatic 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 V automatic 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 S automatic 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 S automatic 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 S automatic 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 S automatic 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 V automatic 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 V automatic 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 V automatic 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 V automatic 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 V automatic 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 V automatic 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 S manual 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 S manual 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 S manual 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 S automatic 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 V automatic 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 V automatic 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 V automatic 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 V automatic 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 S manual 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 V manual 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 S manual 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 V manual 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 V manual 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 V manual 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 S manual 4 2
## weight_kg
## Mazda RX4 1179.00
## Mazda RX4 Wag 1293.75
## Datsun 710 1044.00
## Hornet 4 Drive 1446.75
## Hornet Sportabout 1548.00
## Valiant 1557.00
## Duster 360 1606.50
## Merc 240D 1435.50
## Merc 230 1417.50
## Merc 280 1548.00
## Merc 280C 1548.00
## Merc 450SE 1831.50
## Merc 450SL 1678.50
## Merc 450SLC 1701.00
## Cadillac Fleetwood 2362.50
## Lincoln Continental 2440.80
## Chrysler Imperial 2405.25
## Fiat 128 990.00
## Honda Civic 726.75
## Toyota Corolla 825.75
## Toyota Corona 1109.25
## Dodge Challenger 1584.00
## AMC Javelin 1545.75
## Camaro Z28 1728.00
## Pontiac Firebird 1730.25
## Fiat X1-9 870.75
## Porsche 914-2 963.00
## Lotus Europa 680.85
## Ford Pantera L 1426.50
## Ferrari Dino 1246.50
## Maserati Bora 1606.50
## Volvo 142E 1251.00
mtcars2 %>%
summarise(avg_weight = mean(wt))
## avg_weight
## 1 3.21725
mtcars2 %>%
summarise(avg_weight = mean(wt, na.rm = TRUE))
## avg_weight
## 1 3.21725
mtcars2 %>%
group_by(cyl)%>%
summarise(avg_weight = mean(wt))
## # A tibble: 3 × 2
## cyl avg_weight
## <ord> <dbl>
## 1 4 2.29
## 2 6 3.12
## 3 8 4.00
ggplot(data = mtcars, aes(x =wt, y = mpg)) + geom_point()+
labs(title = "Hubungan Berat Mobil dengan Efisiensi Bahan Bakar", x = "Berat(1000 lbs)", y = "Miles per Gallon")
ggplot(data = mtcars, aes(x =wt, y = mpg, color =factor(cyl))) + geom_point() + labs(title = "berat vs efisiensi bahan bakar berdasarkan silinder", x = "berat (1000 lbs)", y = "miles per gallon", color = "jumlah silinder")
ggplot(data = mtcars, aes(x = wt, y = mpg, color = factor(cyl)))+
geom_point()+
geom_smooth(method = "lm", se = FALSE, color ="blue") +
labs(title = "berat vs efisiensi bahan bakar dengan garis regresi", color = "jumlah silinder", x = "berat(1000 lbs)",y = "miles per gallon")
## `geom_smooth()` using formula = 'y ~ x'
mtcars_summary = mtcars %>%
group_by(cyl)%>%
summarise(count=n())
ggplot(data = mtcars_summary, aes(x = factor(cyl), y = count)) +
geom_bar(stat = "identity", fill = "steelblue") +
labs(
title = "Distribusi mobil berdasarkan jumlah silinder",
x = "Jumlah Silinder",
y = "Jumlah Mobil"
)
ggplot(data = mtcars, aes(x=wt,y = mpg))+
geom_point()+
facet_wrap(~cyl) +
labs(title = "berat vs efisiensi bb per jumlah silinder", x = "berat(1000 lbs)", y = "miles per galon")
ggplot(data = mtcars, aes(x = wt,y=mpg))+
geom_point()+
labs(title="scatter plot berat vs mpg")
