--- title: "Gaza Genocide" author: "Itamar Johan Rachailovich" date: "2024-11-26" output: html_document --- # Libraries ```{r setup, include=FALSE} library(tidyverse) library(kableExtra) library(gtsummary) library(ggplot2) library(maps) # Get palestinian cities library(sf) # convert it to sf dataframe, assign projection to the coordinates and save it library(leaflet) library(leaflet.providers) library(patchwork) library(htmltools) library(htmlwidgets) ``` # Data ```{r} gaza_geno <- read.csv("D:/R_Gaza/gaza/data/killed-in-gaza.csv") class(gaza_geno) ``` # First data exploration ```{r, warning=FALSE, message=FALSE} gaza_geno <- as_tibble(gaza_geno) class(gaza_geno) gaza_geno death_by_age <- gaza_geno %>% group_by(age = as.integer(age)) %>% summarise(Death = n()) peak_10_ages <- death_by_age %>% top_n(n = 10, Death) %>% pull(age) age_quantiles <- quantile(gaza_geno$age) age_quantiles <- as.matrix(age_quantiles) age_quantiles_rownames <- rownames(age_quantiles) age_quantiles <- as.tibble(cbind(age_quantiles, age_quantiles_rownames)) colnames(age_quantiles) colnames(age_quantiles)<- c("Age", "Quantile") age_quantiles %>% kbl(caption = "Age quantiles of murdered palestinians") %>% kable_classic() %>% kable_styling(full_width = FALSE) peak_10_ages death_by_sex_age <- gaza_geno %>% mutate(sex = factor(sex, levels = c("f", "m"), labels = c("Female", "Male"))) %>% group_by(age, sex, .groups = TRUE) %>% summarise(Death = n()) death_by_sex_age <- death_by_sex_age[-3] tbl_by_sex_age <- gaza_geno %>% select(sex, age) %>% mutate(sex = factor(sex, levels = c("f", "m"), labels = c("Female", "Male"))) %>% tbl_summary(label = list(sex = "Sex", age = "Age")) tbl_by_sex_age ``` # Plots ```{r, message=FALSE, warning=FALSE} theme_set(theme_bw()) A <- gaza_geno %>% ggplot(aes(x = age))+ geom_histogram(fill = "#4D5052", colour = "black", bins = 20, binwidth = 2)+ scale_x_continuous(breaks = seq(0, 100, 20))+ labs(title = "Gaza genocide - Death by Age", x = "Age", y = "Frequency of Deaths")+ theme(plot.title = element_text(face = "bold")) B <- death_by_age %>% ggplot(aes(x = age, y = Death))+ geom_line()+ geom_segment(x = 14, xend= 14, y = 0, yend = 659, linetype = "dashed")+ geom_segment(x = 26, xend= 26, y = 0, yend = 652, linetype = "dashed")+ geom_segment(x = 39, xend= 39, y = 0, yend = 469, linetype = "dashed")+ scale_x_continuous(breaks = seq(0, 100, 20))+ labs(title = "Gaza genocide - Death by Age", x = "Age", y = "Number of Deaths", caption = "The frequency and number of murdered palestinians by age (murdered by the Israelis)")+ theme(plot.title = element_text(face = "bold"), plot.caption = element_text(face = "italic", colour = "#4D5052"), plot.caption.position = "plot") hist_linechart_geno <- A + B pal_hist_linechart <- plotTag({ hist_linechart_geno }, "Gaza genocide - Death by Age", width = 700, height = 400) pal_hist_linechart save_html(html = pal_hist_linechart, file = "pal_hist_linechart.html") ``` # Maps ## Setting the data ```{r, warning=FALSE, message=FALSE} # Get palestinian cities, convert it to sf dataframe, assign projection to the coordinates and save it data(world.cities) palestine_cities <- world.cities %>% filter(country.etc == "Palestine") class(palestine_cities) palestine_cities <- as_tibble(palestine_cities) write_excel_csv(palestine_cities, file = "D:/R_Gaza/IRachailovich.github.io/data/palestinians_cities.csv") names(palestine_cities) #get the names for the coordinate variables palestine_cities_sf <- st_as_sf(palestine_cities, coords = c("lat", "long")) #convert to sf df tibble class(palestine_cities_sf) #check if class has changed to sf dataframe tibble st_crs(palestine_cities_sf) #check for geographic projections st_crs(palestine_cities_sf) <- 4326 #assign geographic projection (4326, i.e., longlat WGS84) st_crs(palestine_cities_sf)$proj4string #check if the geographic projection was assigned names(palestine_cities_sf) #check if "lat" and "long" variables were changed to "geometry" variable. st_write(palestine_cities_sf, "D:/R_Gaza/IRachailovich.github.io/data/palestinian_cities", driver = "ESRI Shapefile", delete_layer = TRUE) # save the sf data frame as shapefile unzip(zipfile = "D:/R_Gaza/gaza/data/localities_palestine_sf.zip" , exdir ="data/localities_palestine") localities_palestine_sf <- st_read("data/localities_palestine") localities_palestine_sf %>% head() class(localities_palestine_sf) st_crs(localities_palestine_sf)$proj4string localities_palestine_WGS84 <- st_transform(localities_palestine_sf, crs = 4326) st_crs(localities_palestine_WGS84)$proj4string st_write(localities_palestine_WGS84, "D:/R_Gaza/IRachailovich.github.io/data/localities_palestine", driver = "ESRI Shapefile", delete_layer = TRUE) st_crs(localities_palestine_WGS84)$proj4string st_crs(palestine_cities_sf)$proj4string ``` ## Creating maps ```{r, warning=FALSE, message=FALSE} simple_polygons <- plotTag({ ggplot(localities_palestine_WGS84)+ geom_sf(colour = "black") }, "simple_polygons", width = 700, height = 400) simple_polygons save_html(html = simple_polygons, file = "simple_polygons.html") col_fun <- colorFactor(c("#337bd7", "#c8143b"), domain = NULL) itamar <- st_point(c(34.82375, 31.89530)) itamarpopup <- c("Where I.J.R was born") pal_popup <- paste0("City Name:", palestine_cities$name) palestine_map <- leaflet(localities_palestine_WGS84) %>% addPolygons(stroke = TRUE, weight = 0.7, color = "black", fillColor = ~col_fun(REGIONCODE), group = "Regions", fillOpacity = 0.8) %>% addCircleMarkers(lng = 34.82375 , lat = 31.89530, group = "Where I Live", popup = itamarpopup) %>% addCircleMarkers(data = palestine_cities, group = "Cities", popup = pal_popup, radius = 0.01, color = "#2c120c") %>% addTiles(group = "OSM") %>% addProviderTiles(provider = "CartoDB", group = "CartoDB") %>% addProviderTiles(provider = "CartoDB.Voyager", group = "CartoDB.Voyager") %>% addProviderTiles(provider = "Esri", group = "Esri") %>% addLayersControl(baseGroups = c("OSM", "CartoDB", "CartoDB.Voyager", "Esri"), overlayGroups = c("Regions", "Where I Live", "Cities")) palestine_map saveWidget(widget = palestine_map, file = "palestine_map.html", selfcontained = TRUE) ``` 