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@ -134,7 +134,7 @@ county_populations <- get_estimates(geography = "county", year = 2022, product =
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county_populations <- st_transform(county_populations, crs = 4326)
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County_Crash_geom <- left_join(county_populations, County_Crash_Data, join_by("County"))
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County_Crash_geom <- County_Crash_geom %>%
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mutate(CrashesPerPopulation = MeanCrashes/value*100000)
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mutate(CrashesPerPopulation = MeanCrashes/(value/100000))
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County_Crash_geom$CrashesPerPopulation[is.na(County_Crash_geom$CrashesPerPopulation)] <- 0
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county_pal <- colorNumeric(palette = "YlOrRd", domain = c(min(County_Crash_geom$CrashesPerPopulation, na.rm = TRUE), max(County_Crash_geom$CrashesPerPopulation, na.rm = TRUE)))
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@ -217,7 +217,7 @@ wisconsin_crash_map <-
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fillColor=county_pal(County_Crash_geom$CrashesPerPopulation),
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fillOpacity = 0.6,
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label = lapply(paste0("<b>", str_to_title(County_Crash_geom$County), " County</b></br>",
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"population: ", County_Crash_geom$value, "<br>",
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"population: ", format(County_Crash_geom$value, nsmall=0, big.mark=","), "<br>",
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"average crashes per year: ", round(County_Crash_geom$MeanCrashes,0), "</br>",
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"average crashes/year per 100k residents: ", round(County_Crash_geom$CrashesPerPopulation,0)), htmltools::HTML),
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group = "Counties") %>%
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