netflix = read.csv("C:/Users/asus4/OneDrive/Desktop/TUGAS/VDE/netflix_titles.csv")
library(ggplot2)
custom_col <- c("red", "green", "orange")
ggplot(netflix, aes(x = "", fill = factor(type))) + geom_bar(width = 1) + 
  theme(axis.line = element_blank(), plot.title = element_text(hjust=0.5, size=2)) +
  labs(fill="class", x=NULL, y=NULL, title="Pie Chart of Netflix Shows") + coord_polar(theta="y", start=0) + scale_fill_manual(values=custom_col)

par(c(2,1))
## Warning in par(c(2, 1)): argument 1 does not name a graphical parameter
## NULL
ggplot(netflix, aes(x="", fill=factor(type))) + geom_bar()

ggplot(netflix, aes(y="", fill=factor(type))) + geom_bar()

train = read.csv('train.csv')
head(train)
##   PassengerId Survived Pclass
## 1           1        0      3
## 2           2        1      1
## 3           3        1      3
## 4           4        1      1
## 5           5        0      3
## 6           6        0      3
##                                                  Name    Sex Age SibSp Parch
## 1                             Braund, Mr. Owen Harris   male  22     1     0
## 2 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female  38     1     0
## 3                              Heikkinen, Miss. Laina female  26     0     0
## 4        Futrelle, Mrs. Jacques Heath (Lily May Peel) female  35     1     0
## 5                            Allen, Mr. William Henry   male  35     0     0
## 6                                    Moran, Mr. James   male  NA     0     0
##             Ticket    Fare Cabin Embarked
## 1        A/5 21171  7.2500              S
## 2         PC 17599 71.2833   C85        C
## 3 STON/O2. 3101282  7.9250              S
## 4           113803 53.1000  C123        S
## 5           373450  8.0500              S
## 6           330877  8.4583              Q
summary(train)
##   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                                        
## 
p_age = ggplot(train) +
  geom_freqpoly(mapping = aes(x = Age, fill = Age), binwidth = 1) +
  theme(legend.position = "right") + labs(title = "Average Age of Passangers", y = "Age Count")
p_age
Fig. 2

Fig. 2 

color = c("orange","purple")
p_sex = ggplot(train, aes(x = "", fill = factor(Sex))) + geom_bar(width = 1) + 
  theme(axis.line = element_blank(), plot.title = element_text(hjust=0.5, size=2)) +
  labs(fill="Sex", x=NULL, y=NULL, title="Number of Male and Female Passangers") + coord_polar(theta="y", start=0) + scale_fill_manual(values=color)
p_sex
Fig. 2

Fig. 2 

p_class = ggplot(train, aes(Pclass, fill=Survived)) + scale_color_viridis_b() +
  geom_bar(stat='count') + labs(title="Type Of Ticket Class",x = 'Pclass')
  
p_class
Fig. 2

Fig. 2 

p_emb = ggplot(train, aes(Embarked, fill = Survived)) +
  geom_bar(stat='count', position='fill') +
  labs(x = 'Embarked') +
  theme(legend.position = "none")
p_emb
Fig. 2

Fig. 2 

p_sib = ggplot(train, aes(SibSp, fill = Survived)) +
  geom_bar(stat='count', position='fill') +
  labs(x = 'SibSp') +
  theme(legend.position = "none")
p_sib
Fig. 2

Fig. 2 

p_par = ggplot(train, aes(Parch, fill = Survived)) +
  geom_bar(stat='count', position='fill') +
  labs(x = 'Parch') +
  theme(legend.position = "none")
p_par
Fig. 2

Fig. 2 

p_fare = ggplot(train) +
  geom_freqpoly(mapping = aes(Fare, color = Survived), binwidth = 0.05) +
  scale_x_log10() +
  theme(legend.position = "none")
p_fare
Fig. 2

Fig. 2