Library yang digunakan dan yang perlu diinstal
library(tidyverse)
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?tidyverse
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install.packages("dplyr")
## Warning: package 'dplyr' is in use and will not be installed
library(dplyr)
1. Mencari Dataset selain iris
Dataset ini menggunakan dataset bawaan yang sudah ada di R
library(datasets)
data(mtcars)
mtcars <- tibble::as.tibble(mtcars)
## Warning: `as.tibble()` was deprecated in tibble 2.0.0.
## ℹ Please use `as_tibble()` instead.
## ℹ The signature and semantics have changed, see `?as_tibble`.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
2. Praktikkan penggunaan fungsi summarise(), arrange(), filter(),
mutate(), select(), minimal 1 kali setiap fungsi pada datasets yang
dipilih
Summarise()
mtcars %>% group_by(gear) %>% summarize (mean=mean(hp))
## # A tibble: 3 × 2
## gear mean
## <dbl> <dbl>
## 1 3 176.
## 2 4 89.5
## 3 5 196.
Arrange()
mtcars %>% arrange (qsec)
## # A tibble: 32 × 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
## 2 15 8 301 335 3.54 3.57 14.6 0 1 5 8
## 3 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4
## 4 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
## 5 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 6 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 7 26 4 120. 91 4.43 2.14 16.7 0 1 5 2
## 8 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2
## 9 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2
## 10 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## # ℹ 22 more rows
mtcars %>% arrange(desc(qsec))
## # A tibble: 32 × 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 2 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 3 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1
## 4 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 5 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1
## 6 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1
## 7 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 8 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## 9 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1
## 10 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## # ℹ 22 more rows
Filter()
filtered_mtcars <- filter(mtcars, drat > 3.5)
filtered_mtcars
## # A tibble: 19 × 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 5 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 6 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## 7 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## 8 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1
## 9 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2
## 10 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1
## 11 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1
## 12 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4
## 13 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1
## 14 26 4 120. 91 4.43 2.14 16.7 0 1 5 2
## 15 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2
## 16 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
## 17 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
## 18 15 8 301 335 3.54 3.57 14.6 0 1 5 8
## 19 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2
mtcars %>% filter(vs==0)
## # A tibble: 18 × 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 4 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 5 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3
## 6 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3
## 7 15.2 8 276. 180 3.07 3.78 18 0 0 3 3
## 8 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4
## 9 10.4 8 460 215 3 5.42 17.8 0 0 3 4
## 10 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4
## 11 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2
## 12 15.2 8 304 150 3.15 3.44 17.3 0 0 3 2
## 13 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4
## 14 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2
## 15 26 4 120. 91 4.43 2.14 16.7 0 1 5 2
## 16 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
## 17 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
## 18 15 8 301 335 3.54 3.57 14.6 0 1 5 8
Mutate()
mtcarsbaru <- mtcars %>% select(-cyl, -hp,) %>% mutate(New.Data=drat+wt)
mtcarsbaru
## # A tibble: 32 × 10
## mpg disp drat wt qsec vs am gear carb New.Data
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 160 3.9 2.62 16.5 0 1 4 4 6.52
## 2 21 160 3.9 2.88 17.0 0 1 4 4 6.78
## 3 22.8 108 3.85 2.32 18.6 1 1 4 1 6.17
## 4 21.4 258 3.08 3.22 19.4 1 0 3 1 6.30
## 5 18.7 360 3.15 3.44 17.0 0 0 3 2 6.59
## 6 18.1 225 2.76 3.46 20.2 1 0 3 1 6.22
## 7 14.3 360 3.21 3.57 15.8 0 0 3 4 6.78
## 8 24.4 147. 3.69 3.19 20 1 0 4 2 6.88
## 9 22.8 141. 3.92 3.15 22.9 1 0 4 2 7.07
## 10 19.2 168. 3.92 3.44 18.3 1 0 4 4 7.36
## # ℹ 22 more rows
Select()
mtcars %>% select(cyl,hp,vs,am,gear)
## # A tibble: 32 × 5
## cyl hp vs am gear
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 6 110 0 1 4
## 2 6 110 0 1 4
## 3 4 93 1 1 4
## 4 6 110 1 0 3
## 5 8 175 0 0 3
## 6 6 105 1 0 3
## 7 8 245 0 0 3
## 8 4 62 1 0 4
## 9 4 95 1 0 4
## 10 6 123 1 0 4
## # ℹ 22 more rows
mtcars %>% select(-cyl,-hp,-drat)
## # A tibble: 32 × 8
## mpg disp wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 160 2.62 16.5 0 1 4 4
## 2 21 160 2.88 17.0 0 1 4 4
## 3 22.8 108 2.32 18.6 1 1 4 1
## 4 21.4 258 3.22 19.4 1 0 3 1
## 5 18.7 360 3.44 17.0 0 0 3 2
## 6 18.1 225 3.46 20.2 1 0 3 1
## 7 14.3 360 3.57 15.8 0 0 3 4
## 8 24.4 147. 3.19 20 1 0 4 2
## 9 22.8 141. 3.15 22.9 1 0 4 2
## 10 19.2 168. 3.44 18.3 1 0 4 4
## # ℹ 22 more rows
3. Praktikkan penggunaan 2 fungsi secara bersama
result1 <- mtcars %>%
filter(drat > 3.5) %>%
arrange(desc(drat))
result1
## # A tibble: 19 × 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2
## 2 26 4 120. 91 4.43 2.14 16.7 0 1 5 2
## 3 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1
## 4 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
## 5 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2
## 6 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1
## 7 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1
## 8 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 9 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## 10 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## 11 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 12 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 13 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 14 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2
## 15 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4
## 16 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1
## 17 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 18 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
## 19 15 8 301 335 3.54 3.57 14.6 0 1 5 8
result2 <- mtcars %>%
mutate(New.Data = (drat * wt)/qsec) %>%
select(drat, wt, qsec, New.Data)
result2
## # A tibble: 32 × 4
## drat wt qsec New.Data
## <dbl> <dbl> <dbl> <dbl>
## 1 3.9 2.62 16.5 0.621
## 2 3.9 2.88 17.0 0.659
## 3 3.85 2.32 18.6 0.480
## 4 3.08 3.22 19.4 0.509
## 5 3.15 3.44 17.0 0.637
## 6 2.76 3.46 20.2 0.472
## 7 3.21 3.57 15.8 0.723
## 8 3.69 3.19 20 0.589
## 9 3.92 3.15 22.9 0.539
## 10 3.92 3.44 18.3 0.737
## # ℹ 22 more rows