Distribution of stikes per day by Coalition aircraft in Iraq and Syria (Aug. 2014 - June 2017 included)

1.png

2.png

R.R

library(readr)
library(dplyr)
library(tidyr)
library(ggplot2)
library(ggridges)

# import and simplify before we manipulate
dataset <- read_csv('~/Downloads/Coalition bombing timeline & geolocate - Sheet1.csv')
d <- dataset %>%
  select(Date, `Strike Iraq`, `Strike Syria`) %>%
  replace(is.na(.), 0)

# parse dates
d$Date <- as.Date(d$Date, format = '%d/%m/%Y')

# group by month and calculate daily tally
d.sum <- d %>% 
  group_by(Date) %>% 
  summarise(tally = sum(`Strike Iraq`, `Strike Syria`)) %>%
  na.omit()
d.sum$month <- cut(d.sum$Date, breaks = 'month')

ggplot(d.sum, aes(x=tally, y=month)) +
  geom_density_ridges(scale = 5, size = 0.25, rel_min_height = 0.03) +
  theme_ridges()

# group by year and calculate monthly tally
d.month <- d.sum %>%
  group_by(month) %>%
  summarise(tally=sum(tally)) %>%
  na.omit()
d.month$month <- as.Date(d.month$month, format = '%Y-%m-%d')
d.month$year <- cut(d.month$month, breaks = 'year')

ggplot(d.month, aes(x=tally, y=year)) +
  geom_density_ridges(scale = 3, size = 0.25, rel_min_height = 0.03) +
  theme_ridges()