Let’s use some of the skills we put into practice to examine the subnational relationship between development and conflict in Nigeria.
In this breakout, we’ll:
We’ll use the following spatial datasets for this project:
The data can be downloaded from the following Dropbox data transfer link.
Read in the Nigeria country shape file, prio grid shape file, and the acled conflict (
In addition, do the following:
1(that is, events where we are confident about where the location of the event took place).
latitude) for the Nigeria Acled data into a simple features geometry.
Parsed with column specification: cols( .default = col_character(), data_id = col_double(), iso = col_double(), event_id_no_cnty = col_double(), year = col_double(), time_precision = col_double(), inter1 = col_double(), inter2 = col_double(), interaction = col_double(), latitude = col_double(), longitude = col_double(), geo_precision = col_double(), fatalities = col_double(), timestamp = col_double() ) See spec(...) for full column specifications.
Plot the three spatial data objects as separate plots. Combine the three separate plots into a single plot using
# Generate the plot of Nigeria plot_nig <- ggplot(nig) + geom_sf() + theme_map() # Generate the plot of the prio grid data plot_grid <- ggplot(afr) + geom_sf() + theme_map() # Generate a plot of the acled-nigeria events plot_conflict <- ggplot(acled_nig) + geom_sf(alpha=.1) + theme_map() # Use patchwork to bring all three plots together plot_nig + plot_grid + plot_conflict + plot_layout(ncol=1)