install library

library(ggplot2)
library(dplyr) # data manipulation
library(tidyr) # data manipulation
library(modelr) #factor manipulation
library(stringr) #string manipulation

Visualisasi Data Pie

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=15),panel.background = element_blank()) + 
        labs(fill="class", x=NULL, y=NULL, title="Pie Chart of Netflix") +
        coord_polar(theta="y",start=0) + scale_fill_manual(values=c("#8B322C","#322C2B"))
pie

EXERCISE

import data

train <- read.csv("C:/Users/User/OneDrive - Institut Teknologi Sepuluh Nopember/Dokumen/MATKUL SMSTR 2/Visualisasi Data/R/workinf directory/train.csv")

mengubah data menjadi 

train <- train %>% mutate(
  Survived = factor(Survived),
  Pclass = factor(Pclass),
  Embarked = factor(Embarked),
  Sex = factor(Sex)
)

membuat pie

Mengetahui proporsi penumpang berdasarkan survived

Mengetahui proporsi penumpang berdasarkan tiket kelas

Line Chart

p_age <- ggplot(train, aes(x = Age, color = Survived)) +
  geom_freqpoly(binwidth = 1) +
  scale_color_manual(values = c("#FFC94A", "#DD5746")) +
  theme(plot.title=element_text(hjust=0.5),panel.background = element_blank())+ 
  labs(title="Line Chart for Age Who Survived")
p_age

Mengetahui banyak survived antar umur

Bar Chart

p_sex = ggplot(train, mapping = aes(x = Sex, fill = Survived)) +
  geom_bar(stat='count', position='fill') + scale_fill_manual(values = c("#BED7DC","#F1EEDC")) + 
  theme(plot.title=element_text(hjust=0.5),panel.background = element_blank())+
  labs(title="Bar Chart of Survivor between Sex") 
p_sex

Mengetahui proporsi survived diantara kedua gender