library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ 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 errors
library(datasets)
#Memanggil Data Titanic
data(Titanic)
Titanic <-tibble::as_tibble(Titanic)
#Mendapatkan atau menetapkan kelas objek
class(Titanic)
## [1] "tbl_df" "tbl" "data.frame"
#Memberikan ringkasan atau tampilan yang lebih lengkap tentang struktur suatu dataset
glimpse(Titanic)
## Rows: 32
## Columns: 5
## $ Class <chr> "1st", "2nd", "3rd", "Crew", "1st", "2nd", "3rd", "Crew", "1s…
## $ Sex <chr> "Male", "Male", "Male", "Male", "Female", "Female", "Female",…
## $ Age <chr> "Child", "Child", "Child", "Child", "Child", "Child", "Child"…
## $ Survived <chr> "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "…
## $ n <dbl> 0, 0, 35, 0, 0, 0, 17, 0, 118, 154, 387, 670, 4, 13, 89, 3, 5…
#Menampilkan beberapa baris pertama dari suatu objek
head(Titanic)
## # A tibble: 6 × 5
## Class Sex Age Survived n
## <chr> <chr> <chr> <chr> <dbl>
## 1 1st Male Child No 0
## 2 2nd Male Child No 0
## 3 3rd Male Child No 35
## 4 Crew Male Child No 0
## 5 1st Female Child No 0
## 6 2nd Female Child No 0
#Menghitung berapa yang Selamat dan Tidak Selamat
SurviveOrNo <- Titanic %>% group_by(Survived) %>% summarize (NumOfSurvived=sum(n))
head(SurviveOrNo)
## # A tibble: 2 × 2
## Survived NumOfSurvived
## <chr> <dbl>
## 1 No 1490
## 2 Yes 711
#Arrange
#mengurutkan berdasarkan yang paling dikit selamat
Titanic%>%arrange(n)%>%print(n=32)
## # A tibble: 32 × 5
## Class Sex Age Survived n
## <chr> <chr> <chr> <chr> <dbl>
## 1 1st Male Child No 0
## 2 2nd Male Child No 0
## 3 Crew Male Child No 0
## 4 1st Female Child No 0
## 5 2nd Female Child No 0
## 6 Crew Female Child No 0
## 7 Crew Male Child Yes 0
## 8 Crew Female Child Yes 0
## 9 1st Female Child Yes 1
## 10 Crew Female Adult No 3
## 11 1st Female Adult No 4
## 12 1st Male Child Yes 5
## 13 2nd Male Child Yes 11
## 14 2nd Female Adult No 13
## 15 3rd Male Child Yes 13
## 16 2nd Female Child Yes 13
## 17 3rd Female Child Yes 14
## 18 2nd Male Adult Yes 14
## 19 3rd Female Child No 17
## 20 Crew Female Adult Yes 20
## 21 3rd Male Child No 35
## 22 1st Male Adult Yes 57
## 23 3rd Male Adult Yes 75
## 24 3rd Female Adult Yes 76
## 25 2nd Female Adult Yes 80
## 26 3rd Female Adult No 89
## 27 1st Male Adult No 118
## 28 1st Female Adult Yes 140
## 29 2nd Male Adult No 154
## 30 Crew Male Adult Yes 192
## 31 3rd Male Adult No 387
## 32 Crew Male Adult No 670
#Menghitung berapa yang Selamat berdasarkan usia
SurvivedByAge <- Titanic %>% filter(Survived=="Yes") %>% group_by(Age) %>% summarize (Survive=sum(n))
head(SurvivedByAge)
## # A tibble: 2 × 2
## Age Survive
## <chr> <dbl>
## 1 Adult 654
## 2 Child 57