Tugas Individu Praktikum Mandarel
Elke Frida Rahmawati
2023-12-16
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.3.2## Warning: package 'dplyr' was built under R version 4.3.2## Warning: package 'lubridate' was built under R version 4.3.2## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ 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 errorslibrary(dplyr)
library(datasets)
data(Orange)
Orange <- tibble::as_tibble(Orange)
##Menampilkan kelas (tipe data) dari Orange
class(Orange)## [1] "tbl_df" "tbl" "data.frame"##Menampilkan data frame atau dataset Orange
View(Orange)
##Menampilkan ringkasan dari struktur dataset Orange
##Head menampilkan 6 baris data awal dan glimpse menampilkan informasi lebih terperinci termasuk informasi tiap kolom, tipe data serta beberapa baris awal
head(Orange)## # A tibble: 6 × 3
## Tree age circumference
## <ord> <dbl> <dbl>
## 1 1 118 30
## 2 1 484 58
## 3 1 664 87
## 4 1 1004 115
## 5 1 1231 120
## 6 1 1372 142glimpse(Orange)## Rows: 35
## Columns: 3
## $ Tree <ord> 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3,…
## $ age <dbl> 118, 484, 664, 1004, 1231, 1372, 1582, 118, 484, 664, 10…
## $ circumference <dbl> 30, 58, 87, 115, 120, 142, 145, 33, 69, 111, 156, 172, 2…##Menghitung rata-rata umur (age) pohon
mean(Orange$age)## [1] 922.1429##Memeriksa apakah rata-rata umur (age) pohon dari dataset Orange sama ketika dihitung langsung dengan mean(Orange$age) dan ketika menggunakan (%>%) dari paket dplyr
mean(Orange$age) == Orange$age %>% mean()## [1] TRUE##Memasukkan data
x <- c(109, 359, 163, 896, 515, 142, 117, 329, 407)
x## [1] 109 359 163 896 515 142 117 329 407##Melogaritmakan, mendiferensialkan, mengeksponensialkan kemudian membulatkan 1 angka dibelakang koma
round(exp(diff(log(x))),1)## [1] 3.3 0.5 5.5 0.6 0.3 0.8 2.8 1.2x %>% log () %>%
diff () %>%
exp () %>%
round (1)## [1] 3.3 0.5 5.5 0.6 0.3 0.8 2.8 1.2#Summarize
##Menghitung rata-rata umur (age) dari setiap pohon
Orange %>% group_by(Tree) %>% summarize (mean=mean(age))## # A tibble: 5 × 2
## Tree mean
## <ord> <dbl>
## 1 3 922.
## 2 1 922.
## 3 5 922.
## 4 2 922.
## 5 4 922.##Mengurutkkan berdasarkan peubah age dengan ascending
Orange %>% arrange(age)## # A tibble: 35 × 3
## Tree age circumference
## <ord> <dbl> <dbl>
## 1 1 118 30
## 2 2 118 33
## 3 3 118 30
## 4 4 118 32
## 5 5 118 30
## 6 1 484 58
## 7 2 484 69
## 8 3 484 51
## 9 4 484 62
## 10 5 484 49
## # ℹ 25 more rows##Mengurutkkan berdasarkan peubah age dengan descending
Orange %>% arrange(desc(age))## # A tibble: 35 × 3
## Tree age circumference
## <ord> <dbl> <dbl>
## 1 1 1582 145
## 2 2 1582 203
## 3 3 1582 140
## 4 4 1582 214
## 5 5 1582 177
## 6 1 1372 142
## 7 2 1372 203
## 8 3 1372 139
## 9 4 1372 209
## 10 5 1372 174
## # ℹ 25 more rows#Filter
##Menampilkan data pohon 5
Orange %>% filter(Tree=="5")## # A tibble: 7 × 3
## Tree age circumference
## <ord> <dbl> <dbl>
## 1 5 118 30
## 2 5 484 49
## 3 5 664 81
## 4 5 1004 125
## 5 5 1231 142
## 6 5 1372 174
## 7 5 1582 177##Menampilkan data pohon dan lingkar batang (circumference)
Orange %>% select(Tree,circumference)## # A tibble: 35 × 2
## Tree circumference
## <ord> <dbl>
## 1 1 30
## 2 1 58
## 3 1 87
## 4 1 115
## 5 1 120
## 6 1 142
## 7 1 145
## 8 2 33
## 9 2 69
## 10 2 111
## # ℹ 25 more rows##Menampilkan data yang bukan lingkar batang (circumference)
Orange %>% select(-circumference)## # A tibble: 35 × 2
## Tree age
## <ord> <dbl>
## 1 1 118
## 2 1 484
## 3 1 664
## 4 1 1004
## 5 1 1231
## 6 1 1372
## 7 1 1582
## 8 2 118
## 9 2 484
## 10 2 664
## # ℹ 25 more rows#Mutate (Menambah Peubah Baru)
##Menghitung rasio lingkar batang (circumference) dan age
Orange %>% mutate(Ratio=Orange$circumference / Orange$age)## # A tibble: 35 × 4
## Tree age circumference Ratio
## <ord> <dbl> <dbl> <dbl>
## 1 1 118 30 0.254
## 2 1 484 58 0.120
## 3 1 664 87 0.131
## 4 1 1004 115 0.115
## 5 1 1231 120 0.0975
## 6 1 1372 142 0.103
## 7 1 1582 145 0.0917
## 8 2 118 33 0.280
## 9 2 484 69 0.143
## 10 2 664 111 0.167
## # ℹ 25 more rows##Menghilangkan peubah Tree, kemudian memasukkan peubah ratio
Orange <- Orange %>% select(-Tree) %>% mutate(Ratio=Orange$circumference / Orange$age)
Orange## # A tibble: 35 × 3
## age circumference Ratio
## <dbl> <dbl> <dbl>
## 1 118 30 0.254
## 2 484 58 0.120
## 3 664 87 0.131
## 4 1004 115 0.115
## 5 1231 120 0.0975
## 6 1372 142 0.103
## 7 1582 145 0.0917
## 8 118 33 0.280
## 9 484 69 0.143
## 10 664 111 0.167
## # ℹ 25 more rowsR Markdown
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