Midterm.Rmd

crime_and_incarceration_by_state = read_csv("crime_and_incarceration_by_state.csv")

## Rows: 816 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): jurisdiction
## dbl (13): year, prisoner_count, state_population, violent_crime_total, murde...
## lgl  (3): includes_jails, crime_reporting_change, crimes_estimated
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

shapefile <- "tl_2023_us_state.shp"

map_data <- st_read(shapefile)

## Reading layer `tl_2023_us_state' from data source 
##   `/Users/lorenzogurrola/Desktop/COMP 112/Midterm/tl_2023_us_state.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 56 features and 15 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -179.2311 ymin: -14.60181 xmax: 179.8597 ymax: 71.43979
## Geodetic CRS:  NAD83

myData <- crime_and_incarceration_by_state %>% 
  select(jurisdiction, year, violent_crime_total, state_population) %>% 
  filter(!jurisdiction == "FEDERAL") %>% 
  filter(!jurisdiction == "HAWAII") %>%  
  filter(!jurisdiction== "ALASKA") %>% 
  filter(!is.na(violent_crime_total)) %>% 
  filter(year == 2016) %>% 
  mutate(hundred_thousand_population = state_population/100000) %>%
  mutate(v = violent_crime_total/hundred_thousand_population) %>% 
  mutate(v = round(v, digits = 0)) %>% 
  mutate(mean_v = mean(v))

newMapData <- map_data %>% 
  filter(!NAME == "United States Virgin Islands") %>% 
  filter(!NAME == "Puerto Rico") %>% 
  filter(!NAME == "Guam") %>% 
  filter(!NAME == "District of Columbia") %>% 
  filter(!NAME == "Commonwealth of the Northern Mariana Islands") %>% 
  filter(!NAME == "American Samoa") %>%
  filter(!NAME == "Hawaii") %>%  
  filter(!NAME == "Alaska") %>% 
  mutate(NAMECAPITAL = toupper(NAME))

allData <- newMapData %>% 
  left_join(myData, by = c("NAMECAPITAL" = "jurisdiction"))

leaflet_map <- leaflet(allData) %>%
  addTiles() %>%
  addPolygons(fillColor = ~colorNumeric("viridis", v)(v),
              weight = 1,
              color = "white",
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.7,
              highlightOptions = highlightOptions(weight = 2,
                                                  color = "white",
                                                  fillOpacity = 0.7,
                                                  bringToFront = TRUE),
              label = ~paste("Violent crimes per 100,000 inhabitants:", v),
              labelOptions = labelOptions(style = list("font-weight" = "normal"),
                                          textsize = "13px",
                                          direction = "auto"))

## Warning: sf layer has inconsistent datum (+proj=longlat +datum=NAD83 +no_defs).
## Need '+proj=longlat +datum=WGS84'

leaflet_map