WEEK 9 VDE TITANIC
George Edison
2025-04-25
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tally(titanic)## n
## 1 891titanic %>%
select(1:9) %>%
sample_n(size = 10)## PassengerId Survived Pclass
## 1 526 0 3
## 2 186 0 1
## 3 99 1 2
## 4 128 1 3
## 5 203 0 3
## 6 410 0 3
## 7 799 0 3
## 8 863 1 1
## 9 40 1 3
## 10 652 1 2
## Name Sex Age SibSp Parch
## 1 Farrell, Mr. James male 40.5 0 0
## 2 Rood, Mr. Hugh Roscoe male NA 0 0
## 3 Doling, Mrs. John T (Ada Julia Bone) female 34.0 0 1
## 4 Madsen, Mr. Fridtjof Arne male 24.0 0 0
## 5 Johanson, Mr. Jakob Alfred male 34.0 0 0
## 6 Lefebre, Miss. Ida female NA 3 1
## 7 Ibrahim Shawah, Mr. Yousseff male 30.0 0 0
## 8 Swift, Mrs. Frederick Joel (Margaret Welles Barron) female 48.0 0 0
## 9 Nicola-Yarred, Miss. Jamila female 14.0 1 0
## 10 Doling, Miss. Elsie female 18.0 0 1
## Ticket
## 1 367232
## 2 113767
## 3 231919
## 4 C 17369
## 5 3101264
## 6 4133
## 7 2685
## 8 17466
## 9 2651
## 10 231919glimpse(titanic)## Rows: 891
## Columns: 12
## $ PassengerId <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,…
## $ Survived <int> 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1…
## $ Pclass <int> 3, 1, 3, 1, 3, 3, 1, 3, 3, 2, 3, 1, 3, 3, 3, 2, 3, 2, 3, 3…
## $ Name <chr> "Braund, Mr. Owen Harris", "Cumings, Mrs. John Bradley (Fl…
## $ Sex <chr> "male", "female", "female", "female", "male", "male", "mal…
## $ Age <dbl> 22, 38, 26, 35, 35, NA, 54, 2, 27, 14, 4, 58, 20, 39, 14, …
## $ SibSp <int> 1, 1, 0, 1, 0, 0, 0, 3, 0, 1, 1, 0, 0, 1, 0, 0, 4, 0, 1, 0…
## $ Parch <int> 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 0, 0, 5, 0, 0, 1, 0, 0, 0…
## $ Ticket <chr> "A/5 21171", "PC 17599", "STON/O2. 3101282", "113803", "37…
## $ Fare <dbl> 7.2500, 71.2833, 7.9250, 53.1000, 8.0500, 8.4583, 51.8625,…
## $ Cabin <chr> "", "C85", "", "C123", "", "", "E46", "", "", "", "G6", "C…
## $ Embarked <chr> "S", "C", "S", "S", "S", "Q", "S", "S", "S", "C", "S", "S"…str(titanic)## 'data.frame': 891 obs. of 12 variables:
## $ PassengerId: int 1 2 3 4 5 6 7 8 9 10 ...
## $ Survived : int 0 1 1 1 0 0 0 0 1 1 ...
## $ Pclass : int 3 1 3 1 3 3 1 3 3 2 ...
## $ Name : chr "Braund, Mr. Owen Harris" "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Heikkinen, Miss. Laina" "Futrelle, Mrs. Jacques Heath (Lily May Peel)" ...
## $ Sex : chr "male" "female" "female" "female" ...
## $ 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 ...
## $ Ticket : chr "A/5 21171" "PC 17599" "STON/O2. 3101282" "113803" ...
## $ Fare : num 7.25 71.28 7.92 53.1 8.05 ...
## $ Cabin : chr "" "C85" "" "C123" ...
## $ Embarked : chr "S" "C" "S" "S" ...summary(titanic)## PassengerId Survived Pclass Name
## Min. : 1.0 Min. :0.0000 Min. :1.000 Length:891
## 1st Qu.:223.5 1st Qu.:0.0000 1st Qu.:2.000 Class :character
## Median :446.0 Median :0.0000 Median :3.000 Mode :character
## Mean :446.0 Mean :0.3838 Mean :2.309
## 3rd Qu.:668.5 3rd Qu.:1.0000 3rd Qu.:3.000
## Max. :891.0 Max. :1.0000 Max. :3.000
##
## Sex Age SibSp Parch
## Length:891 Min. : 0.42 Min. :0.000 Min. :0.0000
## Class :character 1st Qu.:20.12 1st Qu.:0.000 1st Qu.:0.0000
## Mode :character Median :28.00 Median :0.000 Median :0.0000
## Mean :29.70 Mean :0.523 Mean :0.3816
## 3rd Qu.:38.00 3rd Qu.:1.000 3rd Qu.:0.0000
## Max. :80.00 Max. :8.000 Max. :6.0000
## NA's :177
## Ticket Fare Cabin Embarked
## Length:891 Min. : 0.00 Length:891 Length:891
## Class :character 1st Qu.: 7.91 Class :character Class :character
## Mode :character Median : 14.45 Mode :character Mode :character
## Mean : 32.20
## 3rd Qu.: 31.00
## Max. :512.33
## Including Plots
# Plot 1: Gender distribution
print(
ggplot(titanic, aes(x = Sex)) +
geom_bar(fill = 'pink') +
labs(title = "Perbandingan Jenis Kelamin di Titanic")
)
# Plot 2: Survival proportion by class
print(
ggplot(titanic, aes(x = factor(Pclass), fill = factor(Survived))) +
geom_bar(position = "fill") +
labs(title = "Proporsi Survival berdasarkan kelas")
)
# Plot 3: Age distribution
print(
ggplot(titanic, aes(x = Age)) +
geom_histogram(bins = 20, fill = 'purple') +
labs(title = "Distribusi umur penumpang")
)## Warning: Removed 177 rows containing non-finite outside the scale range
## (`stat_bin()`).
# Plot 4: Boxplot by survival
print(
ggplot(titanic, aes(x = factor(Survived), y = Age, fill = factor(Survived))) +
geom_boxplot() +
labs(title = "Boxplot")
)## Warning: Removed 177 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
# Plot 5: Age vs Fare with trend line
print(
ggplot(titanic, aes(x = Age, y = Fare)) +
geom_point() +
geom_smooth(method = "lm", color = 'blue') +
labs(title = "Pengaruh umur terhadap harga tiket")
)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 177 rows containing non-finite outside the scale range
## (`stat_smooth()`).## Warning: Removed 177 rows containing missing values or values outside the scale range
## (`geom_point()`).