library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)

#import data

titanic = read.csv("/Users/elenamiskafaradisa/Documents 2/titanic2.csv.csv")
tally(titanic)
##     n
## 1 891
titanic %>%
  select(1:9) %>% #kolom 1:9
  sample_n(size= 10)
##    PassengerId Survived Pclass                                          Name
## 1          211        0      3                                Ali, Mr. Ahmed
## 2          843        1      1                       Serepeca, Miss. Augusta
## 3           70        0      3                             Kink, Mr. Vincenz
## 4          319        1      1                      Wick, Miss. Mary Natalie
## 5          486        0      3                        Lefebre, Miss. Jeannie
## 6          572        1      1 Appleton, Mrs. Edward Dale (Charlotte Lamson)
## 7          870        1      3               Johnson, Master. Harold Theodor
## 8          552        0      2                   Sharp, Mr. Percival James R
## 9          144        0      3                           Burke, Mr. Jeremiah
## 10         612        0      3                         Jardin, Mr. Jose Neto
##       Sex Age SibSp Parch             Ticket
## 1    male  24     0     0 SOTON/O.Q. 3101311
## 2  female  30     0     0             113798
## 3    male  26     2     0             315151
## 4  female  31     0     2              36928
## 5  female  NA     3     1               4133
## 6  female  53     2     0              11769
## 7    male   4     1     1             347742
## 8    male  27     0     0             244358
## 9    male  19     0     0             365222
## 10   male  NA     0     0 SOTON/O.Q. 3101305

#summary

glimpse(titanic) #lebiih rapi
## 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                                        
## 

#EDA (exploratori data analysis)

#1. perbandingan jenis kelamin di titanic

ggplot(titanic, aes(x = Sex)) + geom_bar(fill = "pink")+
  labs(title = "perbandingan jenis kelamin penumpang titanic")

#2. perbandingan data selamat atau tdk berdasarkan kelas

ggplot(titanic, aes(factor(Pclass), fill = factor(Survived))) +
  geom_bar(position = "fill") + labs(title = "Proporsi Survival berdasarkan kelas")

#3. Distribusi umur panjang

ggplot(titanic, aes(x=Age)) +
  geom_histogram(bins=30,fill="purple", colors= "white")+
  labs(title = "Distribusi umur penumpang")
## Warning in geom_histogram(bins = 30, fill = "purple", colors = "white"):
## Ignoring unknown parameters: `colours`
## Warning: Removed 177 rows containing non-finite outside the scale range
## (`stat_bin()`).

#4. boxplot

ggplot(titanic, aes(x=factor(Survived), y = Age, fill= factor(Survived)))+
  geom_boxplot(outlier.color="red")+
  labs(title="boxplot")
## Warning: Removed 177 rows containing non-finite outside the scale range
## (`stat_boxplot()`).

#scatterplot

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()`).