TugasVDE_althaf_020

library(tidyr)
library(stringr)
library(forcats)
library(tidyr)
library(modelr)


netflix = read.csv("netflix_titles.csv")
library(ggplot2)
pie <- ggplot(netflix, aes(x = "", fill = factor(type))) +
  geom_bar(width = 1) +
  theme(axis.line = element_blank(),
        plot.title = element_text(hjust = 0.5, size = 22)) +
  labs(fill = "class", 
       x = NULL,
       y = NULL,
       title = "Pie chart nyoba") +
  coord_polar (theta = "y", start = 0)

ggplot(netflix, aes(x = "", fill = factor(type))) +
  geom_bar() +
  coord_polar(theta = 'y')

setwd("/Users/althafsm/18Mar_OP")
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

custom_col = c("#E4C59E", "#AF8F6F", "#74512D", "#543310")
p_age = ggplot(train) +
  geom_freqpoly(mapping = aes(x = Age, color = Survived), binwidth = 1) +
  scale_color_manual(values = custom_col)
  theme(legend.position = "right")

## List of 1
##  $ legend.position: chr "right"
##  - attr(*, "class")= chr [1:2] "theme" "gg"
##  - attr(*, "complete")= logi FALSE
##  - attr(*, "validate")= logi TRUE

p_sex = ggplot(train, mapping = aes(x = Sex, fill = Survived)) +
  geom_bar(stat='count', position='fill') +
  labs(x = 'Sex') +
  scale_fill_manual(values = custom_col, name = "Survived") +
  scale_fill_discrete(name="Surv")

## Scale for fill is already present.
## Adding another scale for fill, which will replace the existing scale.

p_class = ggplot(train, mapping = aes(x = Pclass, fill = Survived, colour = Survived)) +
  geom_bar(stat='count', position='fill') +
  labs(x = 'Pclass') +
  scale_fill_manual(values = custom_col, name = "Survived") +
  theme(legend.position = "none")

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

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

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

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

p_age

Fig. 2

p_sex

Fig. 2

p_fare

Fig. 2

p_class

Fig. 2

p_emb

Fig. 2

p_sib

Fig. 2

p_par

Fig. 2