Exploratory with Titanic Dataset

#baca data set lalu assignt ke dalam variable titanic 
Titanic <- read.csv("kapal_titanic.csv")
Titanic

Variable Notes

pclass: A proxy for socio-economic status (SES) 1st = Upper 2nd = Middle 3rd = Lower

age: Age is fractional if less than 1. If the age is estimated, is it in the form of xx.5

sibsp: The dataset defines family relations in this way… Sibling = brother, sister, stepbrother, stepsister Spouse = husband, wife (mistresses and fiancés were ignored)

parch: The dataset defines family relations in this way… Parent = mother, father Child = daughter, son, stepdaughter, stepson Some children travelled only with a nanny, therefore parch=0 for them. Variable Definition Key survival Survival 0 = No, 1 = Yes pclass Ticket class 1 = 1st, 2 = 2nd, 3 = 3rd embarked Port of Embarkation C = Cherbourg, Q = Queenstown, S = Southampton

#cek data teratas menggunakan fungsi head()
head(Titanic)

#cek data terbawah menggunakan fungsi head()
tail(Titanic)

#cek jumlah baris dan kolom pada data frame
dim(Titanic)

## [1] 891   9

#cek tipe data
str(Titanic)

## 'data.frame':    891 obs. of  9 variables:
##  $ survived: int  0 1 1 1 0 0 0 0 1 1 ...
##  $ pclass  : int  3 1 3 1 3 3 1 3 3 2 ...
##  $ sex     : Factor w/ 2 levels "female","male": 2 1 1 1 2 2 2 2 1 1 ...
##  $ age     : num  22 38 26 35 35 NA 54 2 27 14 ...
##  $ sibsp   : int  1 1 0 1 0 0 0 3 0 1 ...
##  $ parch   : int  0 0 0 0 0 0 0 1 2 0 ...
##  $ fare    : num  7.25 71.28 7.92 53.1 8.05 ...
##  $ embarked: Factor w/ 4 levels "","C","Q","S": 4 2 4 4 4 3 4 4 4 2 ...
##  $ deck    : Factor w/ 8 levels "","A","B","C",..: 1 4 1 4 1 1 6 1 1 1 ...

#rubah tipe data 
Titanic <- Titanic %>%
                mutate(survived = as.factor(survived)) %>% 
                mutate(pclass = as.factor(pclass))

#cek missing value per kolom
colSums(is.na(Titanic)) 

## survived   pclass      sex      age    sibsp    parch     fare embarked 
##        0        0        0      177        0        0        0        0 
##     deck 
##        0

Karna yang memiliki nilai NA adalah baris pada kolom age maka tidak dilakukan Drop missing value dikarnakan dapat menghilangkan informasi yang lain

Exploratory Data Analysis

p1 <- ggplot(Titanic[!is.na(Titanic$survived),], aes(x = survived, fill = survived)) +
      geom_bar(stat='count') +
      labs(x = 'How many people died and survived on the Titanic?') +
      geom_label(stat='count',aes(label=..count..), size=7) +
      theme_grey()
p1

Terlihat pada plot diatas bahwa penumpang kapal yang berhasil selamat sebanyak 342 orang dan yang tidak selamat 549

Total Survived Based On Sex

s1 <- ggplot(Titanic, aes(x = sex, fill = sex)) +
  geom_bar(stat='count', position='dodge') + theme_grey() +
  labs(x = 'Number of Humans by Sex') +
        geom_label(stat='count', aes(label=..count..)) +
        scale_fill_manual("legend", values = c("female" = "chocolate", "male" = "green"))

s2 <- ggplot(Titanic[!is.na(Titanic$survived),], aes(x = sex, fill = survived)) +
  geom_bar(stat='count', position='dodge') + theme_grey() +
  labs(x = 'Survived or Not Based on Sex') +
        geom_label(stat='count', aes(label=..count..))

grid.arrange(s1,s2, nrow=1)

dari plot diatas terlihat bahwa penumpang perempuan lebih banyak yang selamat ketimbang penumpang pria.

Total Survived Based On pclass

pcls <- ggplot(data = Titanic, mapping = aes(x = sex)) + 
             geom_bar(mapping = aes(fill = survived)) + theme_linedraw() + 
             ggtitle("Pclass Survived Distribution Based on pclass") +
             xlab("Pclass") + ylab("Number of Customers") + facet_wrap(Titanic$pclass) + 
             scale_y_continuous(breaks = c(0, 50, 100, 200 , 300, 400, 500)) 
ggplotly(pcls)

## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

Terlihat bahwa penumpang yang memesan tiket di kelas 1 lebih banyak yag selamat dan sedikit yang tidak selamat dibanding 2 kelas yang lain,

Survival Density Age

sd1 <- ggplot(Titanic[(!is.na(Titanic$survived) & !is.na(Titanic$age)),], aes(x = age, fill = survived)) +
       geom_density(alpha=0.5, aes(fill=factor(survived))) + labs(title="Survival density and Age") +
       scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) + theme_grey()
sd1

Dari plot diatas kebanyakan penumpang yang tidak selamat ada di rentang usia antara 20 - 40 tahun dan yang selamat ada di rentang usia sekitar <=10 - 40 tahun.