Data Visualization with R: Final Test

This is my product for final test in the courses.

rm(list = ls()) # remove list before script

# Load packages
library(readr)
library(dplyr)
library(ggplot2)
library(ggthemes)
library(showtext)
library(hrbrthemes)

# Path directory
path1 <- c("C:/Users/Phong Vu/Dropbox/PC/Downloads/r_cased/R15_exam1/globalterrorismdb_0718dist.csv")

# Read data
read.csv(path1) -> terrorism_data

# Note
# - Chart type: 
# - Idea:
# - Insight: 
# - Data required: x: numeric var.; y: numeric var. and group
# - Function: geom_area()
# # Create data
# time <- as.numeric(rep(seq(1, 7), each =7)) # x axis
# value <- runif(49, 10, 100) # y axis
# group <- rep(LETTERS[1:7], times = 7)
# data <- data.frame(time, value, group)
# 
# # Stacked area chart
# ggplot(data, aes(x=time, y=value, fill=group)) +
#   geom_area()

# Wrangling and Cleaning
terrorism_data %>%
  filter(iyear >= 2000, iyear <= 2014)  %>%
  select(iyear,
         country,
         country_txt,
         region,
         region_txt,
         nkill,
         nkillter)-> terrorism_data # Select years, from 2000 to 2014 and vars. of interests

coalesce(terrorism_data$nkill, 0) -> nkill_1
coalesce(terrorism_data$nkillter, 0) -> nkillter_1

terrorism_data %>% 
  mutate(total_kill = nkill_1 + nkillter_1) -> terrorism_data

west_countries <- c("North America", "Western Europe", "Australasia & Oceania")

terrorism_data %>% 
  filter(region_txt == west_countries) -> west_countries

west_countries %>% 
  pull(country_txt) -> west_countries_names

terrorism_data %>% 
  mutate(country_group = case_when(country_txt == "Iraq" ~ "Iraq",
                                   country_txt == "Nigeria" ~ "Nigeria",
                                   country_txt %in% c("Syria","Afghanistan","Pakistan") ~ "Syria, Afghanistan & Pakistan",
                                   country_txt %in% west_countries_names ~ "Western countries",
                                   TRUE ~ "Rest of the world")) -> terrorism_data

terrorism_data %>% 
  group_by(iyear, country_group) %>% 
  summarise(death = sum(total_kill/1000)) %>% 
  ungroup() -> terrorism_data

region_names <- c("Rest of the world","Western countries","Syria, Afghanistan & Pakistan",
                  "Nigeria","Iraq")

c("2000", "01","02","03","04","05","06","07","08","09","10","11","12","13","14") -> label_on_x

terrorism_data$country_group <- factor(terrorism_data$country_group, levels = region_names)

font_main <- "Ubuntu"

font_add_google(name = font_main, family = font_main)

showtext_auto()

# Visualization
ggplot(terrorism_data, aes(x = iyear, y = death, fill = country_group)) +
  geom_area() +
  scale_fill_manual(values = c("Rest of the world" = "#00a4dc",
                               "Western countries" = "#00526d",
                               "Syria, Afghanistan & Pakistan" = "#7b2713",
                               "Nigeria" = "#eca288",
                               "Iraq" = "#f15a40"))+
  labs(title = " Global deaths from terrorism",
       subtitle = "  '000",
       caption = "Source: START, IEP",
       x = NULL, y = NULL) +
  theme(axis.title = element_blank(),
        axis.ticks = element_blank(),
        axis.text.x = element_text(hjust = c(0, 0.5, 0.5, 0.5, 1), size = 20),
        axis.text.y = element_text(size = 20),
        legend.position = c(0.18, 0.8),
        legend.title = element_blank(),
        legend.text = element_text(size = 20),
        legend.key.height = unit(10, "pt"),
        legend.key.width = unit(20, "pt"),
        panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.major.y = element_line(color = "grey", size = 1),
        panel.background = element_rect(fill = "white"),
        plot.background = element_rect(fill = "white")) +
  scale_x_continuous(breaks = 2000:2014, labels = label_on_x, expand = c(0, 1)) +
  scale_y_continuous(breaks = seq(0, 50, 5), expand = c(0, 0), position = "right") +
  guides(fill = guide_legend(reverse = TRUE))+
  theme(plot.title = element_text(size = 40, face = "bold"))+
  theme(plot.subtitle  = element_text(colour = "grey30",size = 20, hjust = 0))+
  theme(plot.caption  = element_text(color = "grey30",size = 20,hjust = 0))