Downloads and plots data on mass shootings from Mother Jones (http://www.motherjones.com/politics/2012/12/mass-shootings-mother-jones-full-data)

mass-shootings.R

# load packages
library(magrittr)
library(googlesheets)
library(lubridate)
library(dplyr)
library(stringr)
library(tidyr)
library(ggplot2)
library(maps)
library(scales)

# load data from google sheets
u <- "https://docs.google.com/spreadsheets/d/1XV4mZi3gYDgwx5PrLwqqHTUlHkwkV-6uy_yeJh3X46o/edit?usp=sharing"
guns_raw <- gs_url(u) %>% 
	gs_read()

# clean data
guns <- data.frame(
	date = mdy(guns_raw$Date),
	year = year(mdy(guns_raw$Date)),
	fatalities = guns_raw$Fatalities,
	injuries = guns_raw$Injured,
	case = str_to_title(guns_raw$Case),
	long = guns_raw$longitude,
	lat = guns_raw$latitude
)

# calculate cumulative fatalities and injuries
guns <- guns %>%
	mutate(total_fatalities = order_by(date, cumsum(fatalities))) %>%
	mutate(total_injuries = order_by(date, cumsum(injuries))) %>%
	mutate(case = reorder(case, fatalities)) %>%
	mutate(decade = cut(year, breaks = c(1980, 1990, 2000, 2010, 2015),
											labels = c("1980s", "1990s", "2000s", "2011-2015")))



# plot shootings per year
guns_year <- summarize(group_by(guns, year), 
											 mass_shootings = length(fatalities),
											 fatalities = sum(fatalities))
ggplot(guns_year, aes(x = year, y = mass_shootings)) + 
	geom_smooth() + 
	geom_point() + 
	theme_bw() + 
	labs(title = "Mass Shootings Per Year",
		   x = "Year",
		   y = "Number of Mass Shootings")
ggsave("shootings_per_year.png", height = 4, width = 6)

# plot fatalities per year
ggplot(guns_year, aes(x = year, y = fatalities)) + 
	geom_smooth() + 
	geom_point() + 
	theme_bw() + 
	labs(title = "Number of Fatalities from Mass Shootings Per Year",
		x = "Year",
			 y = "Number of Fatalities")
ggsave("fatalities_per_year.png", height = 4, width = 6)

# plot cumulative fatalities and injuries over time
gather(guns, type, total_count, total_injuries, total_fatalities) %>%
	mutate(type = plyr::revalue(type, c("total_fatalities" = "fatalities",
																			"total_injuries" = "injuries"))) %>%
	ggplot(aes(x = date, y = total_count, color = type)) +
	geom_line() + 
	scale_color_brewer(type = "qual", palette = 2) + 
	theme_bw() + 
	labs(title = "Cumulative Fatalities and Injuries from Mass Shootings Since 1980", 
			 x = "Date",
			 y = "Cumulative Count",
			 color = "Type")
ggsave("cumulative.png", height = 4, width = 7)

# plot fatalities and injuries for each shooting
gather(guns, type, count, injuries, fatalities) %>%
ggplot(aes(x = count, y = case, color = type)) + 
	geom_point() + 
	scale_color_brewer(type = "qual", palette = 2) + 
	theme_bw() + 
	labs(title = "Mass Shooting Events Since 1980",
			 x = "Count",
			 y = "Cases",
			 color = "Type")
ggsave("cases.png", height = 10, width = 8)

# map of shootings
usa <- map_data("state")
gg <- ggplot() + 
	geom_polygon(data = usa, aes(x = long, y = lat, group = group),
							 color = "white", fill = "grey95") + 
	coord_fixed(1.3) + 
	geom_point(data = subset(guns, long > -140), 
						 aes(x = long, y = lat, size = fatalities, color = injuries),
						 alpha = 0.7) + 
	scale_color_gradient(low = "#1b9e77", high = "#d95f02") + 
	scale_size(range = c(2, 10)) + 
	labs(title = "Locations of Mass Shootings Since 1980",
			 color = "Injuries",
			 size = "Fatalities") + 
	theme_bw() + theme(axis.line = element_blank(),
										 axis.text.x = element_blank(),
										 axis.text.y = element_blank(),
										 axis.ticks = element_blank(),
										 axis.title.x = element_blank(),
										 axis.title.y = element_blank(),
										 panel.background = element_blank(),
										 panel.border = element_blank(),
										 panel.grid.major = element_blank(),
										 panel.grid.minor = element_blank(),
										 plot.background = element_blank())
print(gg)
ggsave("map.png", height = 4, width = 7)

# map by decade
gg + facet_wrap(~decade) + 
	labs(title = "Locations of Mass Shootings Since 1980 by Decade")
ggsave("map_by_decade.png", height = 6, width = 10)