Global terrorism, 2000 - 2014 (Version 1)

Daily Graph Series

Economist-Style Plot using R

Origin of the plot can be found here. This plot can be replicated by using R as follows:

R Codes for Data Cleaning and Visualization

Data can be downloaded here.

# Load data: 
library(tidyverse)
dfRaw <- read_csv("/home/khanhan/Downloads/globalterrorismdb_0718dist.csv")

# Western Countries: 

library(rvest)

read_html("http://worldpopulationreview.com/countries/western-countries/") %>% 
  html_nodes(xpath = '//*[@id="dataTable"]/div[1]/div/div/div/div/div[2]/table') %>% 
  html_table(fill = TRUE) %>% 
  .[[1]] %>% 
  slice(-1) %>% 
  rename(Country = X1, Pop = X2) -> western_df


# Add Greece and Israel: 

westCountries <- c(western_df$Country, "Greece", "Israel")

# Select some columns and create a new column: 

dfRaw %>%  
  select(iyear, country_txt, nkill, nkillter) %>% 
  filter(iyear %in% c(2000:2014)) %>% 
  mutate(nkill = replace_na(nkill, 0)) %>% 
  mutate(nkillter = replace_na(nkillter, 0)) %>% 
  mutate(totalDeath = nkill + nkillter) %>% 
  mutate(region = case_when(country_txt %in% c("Syria","Afghanistan","Pakistan") ~ "Syria, Afghanistan & Pakistan", 
                            country_txt %in% westCountries ~ "Western Countries", 
                            country_txt == "Iraq" ~ "Iraq",
                            country_txt == "Nigeria" ~ "Nigeria",
                            TRUE ~ "Others")) %>% 
  group_by(iyear, region) %>% 
  summarise(deaths = sum(totalDeath) / 1000) %>%  
  ungroup() -> dfPlot

# Total Deaths: 

dfPlot %>% 
  mutate(region = "Rest of the World") %>% 
  group_by(iyear, region) %>% 
  summarise(deaths = sum(deaths)) %>% 
  ungroup() -> totalDeaths 

# Remove Others: 
dfPlot %>% filter(region != "Others") -> df_remaining

# Joint the two data sets: 
df_for_ploting <- bind_rows(df_remaining, totalDeaths)


# Make a draft version: 

ggplot() + 
  geom_line(data = totalDeaths, aes(x = iyear, y = deaths), size = 1.2) +
  geom_area(data = totalDeaths, aes(x = iyear, y = deaths, fill = region)) +
  geom_area(data = df_remaining, aes(x = iyear, y = deaths, fill = region), color = "white") + 
  labs(title = "The number of deaths from global terrorism, 2000-2014", 
       subtitle = "Deaths from global terrorism have increased dramatically over the last 15 years.\nThe number of deaths has increased elevenfold sine the year 2000", 
       caption = "Source: START, IEP") -> p


# Finalize our plot: 

economistColors <- c("#7b2713", "#eb9e84", "#00a4dc", "#f15a40", "#00526d")
my_font <- "Ubuntu Condensed"
label_x <- c("2000", paste0("0", 1:9), 10:13, "2014")
label_y <- c(seq(0, 50, 10), "60K")

p + 
  theme_minimal(base_family = my_font) + 
  scale_fill_manual(values = economistColors) + 
  scale_y_continuous(breaks = seq(0, 60, 10), limits = c(0, 60), labels = label_y, expand = c(0, 0), position = "right") + 
  scale_x_continuous(breaks = seq(2000, 2014, 1), labels = label_x, expand = c(0, 0.3)) + 
  theme(panel.grid.major.x = element_blank()) + 
  theme(panel.grid.minor.x = element_blank()) + 
  theme(panel.grid.minor.y = element_blank()) + 
  theme(panel.grid.major.y = element_line(color = "darkgrey")) + 
  theme(legend.position = c(0.13, 0.71), legend.title = element_blank()) + 
  theme(legend.key.width = unit(25, "pt"), legend.key.height = unit(15, "pt")) + 
  theme(legend.text = element_text(margin = margin(l = 1), size = 13, color = "grey20")) + 
  theme(plot.margin = unit(rep(1, 4), "cm")) + 
  theme(axis.title = element_blank()) + 
  theme(axis.text = element_text(size = 13)) + 
  theme(plot.title = element_text(size = 26, color = "grey20")) + 
  theme(plot.subtitle = element_text(size = 15, color = "grey30")) + 
  theme(plot.caption = element_text(size = 12, colour = "grey30")) + 
  theme(legend.background = element_rect(fill = "white", size = 0))

library(grid)
grid.rect(x = 0.015, y = 0.91, hjust = 1, vjust = 0, gp = gpar(fill = "#e5001c", lwd = 0))  
grid.rect(x = 1, y = 1 - 0.005, hjust = 1, vjust = 0,  gp = gpar(fill = "#e5001c", lwd = 0))