Final Project

knitr::opts_chunk$set(echo = TRUE)
## Initializing Libraries
setwd('C:/Users/ogalagedara/Documents/data for r project')
require(tidyverse)

## Loading required package: tidyverse

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

require(ggplot2)
require(mapview)

## Loading required package: mapview

require(sf)

## Loading required package: sf
## Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; sf_use_s2() is TRUE

require(dplyr)
require(devtools)

## Loading required package: devtools
## Loading required package: usethis

require(leaflet)

## Loading required package: leaflet

require(ggmap); require(ggsn); require(RColorBrewer); require(htmlwidgets); require(classInt); require(sp); require(magrittr)

## Loading required package: ggmap
## ℹ Google's Terms of Service: <https://mapsplatform.google.com>
##   Stadia Maps' Terms of Service: <https://stadiamaps.com/terms-of-service/>
##   OpenStreetMap's Tile Usage Policy: <https://operations.osmfoundation.org/policies/tiles/>
## ℹ Please cite ggmap if you use it! Use `citation("ggmap")` for details.Loading required package: ggsn

## Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
## logical.return = TRUE, : there is no package called 'ggsn'

## Loading required package: RColorBrewer
## Loading required package: htmlwidgets
## Loading required package: classInt
## Loading required package: sp
## Loading required package: magrittr
## 
## Attaching package: 'magrittr'
## 
## The following object is masked from 'package:ggmap':
## 
##     inset
## 
## The following object is masked from 'package:purrr':
## 
##     set_names
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## The following object is masked from 'package:tidyr':
## 
##     extract

require(gganimate)

## Loading required package: gganimate

## Cleaning NTA
basemap <- st_read("C:/Users/ogalagedara/Documents/data for r project/2020 Neighborhood Tabulation Areas (NTAs)_20250512.geojson")

## Reading layer `2020 Neighborhood Tabulation Areas (NTAs)_20250512' from data source `C:\Users\ogalagedara\Documents\data for r project\2020 Neighborhood Tabulation Areas (NTAs)_20250512.geojson' 
##   using driver `GeoJSON'
## Simple feature collection with 262 features and 11 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -74.25559 ymin: 40.49613 xmax: -73.70001 ymax: 40.91553
## Geodetic CRS:  WGS 84

basemap <- basemap%>%filter(grepl('Brooklyn',boroname,ignore.case=TRUE))
## Winter 2024 Data Loading and Cleaning
Winter2024 <- read.csv('Winter2024.csv')
Winter2024$CMPLNT_NUM <- NULL
Winter2024$LOC_OF_OCCUR_DESC <- NULL
Winter2024$VIC_AGE_GROUP <- NULL
Winter2024$KY_CD <- NULL
Winter2024$ADDR_PCT_CD <- NULL
Winter2024$OFNS_DESC <- NULL
Winter2024$PD_CD <- NULL
Winter2024$PREM_TYP_DESC  <- NULL
Winter2024$PD_DESC <- NULL
Winter2024$CRM_ATPT_CPTD_CD <- NULL
Winter2024$JURIS_DESC <- NULL
Winter2024$STATION_NAME <- NULL
Winter2024$VIC_RACE <- NULL
Winter2024$VIC_SEX <- NULL
Winter2024 <- Winter2024%>%filter(grepl('Brooklyn',BORO_NM,ignore.case=TRUE))
Winter2024 <- Winter2024%>%filter(LAW_CAT_CD%in%c('FELONY','MISDEMEANOR'))
## Filtered for Brooklyn, Felony and Misdemeanor
## Converting to and sf object
Winter2024 <- Winter2024%>%filter(!(Latitude==0 & Longitude==0))
Winter2024 <- st_as_sf(Winter2024,
                     coords = c("Longitude","Latitude"),
                     crs = 4326,
                     remove = FALSE)
winter2024MAP <- ggplot()+ geom_sf(data = basemap, fill = 'white', color ='black', size = 0.3)+
  stat_density2d(data=Winter2024, aes(x = Longitude, y = Latitude, fill = ..level..),
                 geom = "polygon", alpha = 0.5, color = NA) +
  scale_fill_viridis_c(option = "rocket") +
  labs(title = "Density of Felony and Misdemeanor NYPD Incidents in Brooklyn, December - Feburary (2023-2024)",
       fill = "Felony and Misdemeanor Incidents") +
  coord_sf() +
  theme_classic()+theme(panel.grid = 
                          element_blank(),
                        axis.title = element_blank(),
                        axis.text = element_blank(),
                        axis.line = element_blank())

## Spring 2024 Data Loading and Clean
setwd('C:/Users/ogalagedara/Documents/data for r project')
Spring2024 <- read.csv('Spring2024.csv')
Spring2024 <- Spring2024%>%filter(LAW_CAT_CD%in%c('FELONY','MISDEMEANOR'))
Spring2024$CMPLNT_NUM <- NULL
Spring2024$LOC_OF_OCCUR_DESC <- NULL
Spring2024$VIC_AGE_GROUP <- NULL
Spring2024$KY_CD <- NULL
Spring2024$ADDR_PCT_CD <- NULL
Spring2024$OFNS_DESC <- NULL
Spring2024$PD_CD <- NULL
Spring2024$PREM_TYP_DESC  <- NULL
Spring2024$PD_DESC <- NULL
Spring2024$CRM_ATPT_CPTD_CD <- NULL
Spring2024$JURIS_DESC <- NULL
Spring2024$STATION_NAME <- NULL
Spring2024$VIC_RACE <- NULL
Spring2024$VIC_SEX <- NULL
Spring2024$CMPLNT_FR_TM <- NULL
Spring2024$PATROL_BORO <- NULL
Spring2024 <- Spring2024%>%filter(grepl('Brooklyn',BORO_NM,ignore.case=TRUE))
Spring2024 <- Spring2024%>%filter(!(Latitude==0 & Longitude==0))
Spring2024 <- st_as_sf(Spring2024,
                       coords = c("Longitude","Latitude"),
                       crs = 4326,
                       remove = FALSE)
Spring2024MAP <- ggplot()+ geom_sf(data = basemap, fill = 'white', color ='black', size = 0.3)+
  stat_density2d(data=Spring2024, aes(x = Longitude, y = Latitude, fill = ..level..),
                 geom = "polygon", alpha = 0.5, color = NA) +
  scale_fill_viridis_c(option = "rocket") +
  labs(title = "Density of Felony and Misdemeanor NYPD Incidents in Brooklyn, March - May (2024)",
       fill = "Felony and Misdemeanor Incidents") +
  coord_sf() +
  theme_classic()+theme(panel.grid = 
                          element_blank(),
                        axis.title = element_blank(),
                        axis.text = element_blank(),
                        axis.line = element_blank())

## Summer 2024 Data Loading and Cleaning
setwd('C:/Users/ogalagedara/Documents/data for r project')
Summer2024 <- read.csv('Summer2024.csv')
Summer2024 <- Summer2024%>%filter(LAW_CAT_CD%in%c('FELONY','MISDEMEANOR'))
Summer2024$CMPLNT_NUM <- NULL
Summer2024$LOC_OF_OCCUR_DESC <- NULL
Summer2024$VIC_AGE_GROUP <- NULL
Summer2024$KY_CD <- NULL
Summer2024$ADDR_PCT_CD <- NULL
Summer2024$OFNS_DESC <- NULL
Summer2024$PD_CD <- NULL
Summer2024$PREM_TYP_DESC  <- NULL
Summer2024$PD_DESC <- NULL
Summer2024$CRM_ATPT_CPTD_CD <- NULL
Summer2024$JURIS_DESC <- NULL
Summer2024$STATION_NAME <- NULL
Summer2024$VIC_RACE <- NULL
Summer2024$VIC_SEX <- NULL
Summer2024$CMPLNT_FR_TM <- NULL
Summer2024$PATROL_BORO <- NULL
Summer2024 <- Summer2024%>%filter(!(Latitude==0 & Longitude==0))
Summer2024 <- Summer2024%>%filter(grepl('Brooklyn',BORO_NM,ignore.case=TRUE))
Summer2024 <- st_as_sf(Summer2024,
                       coords = c("Longitude","Latitude"),
                       crs = 4326,
                       remove = FALSE)
Summer2024MAP <- ggplot()+ geom_sf(data = basemap, fill = 'white', color ='black', size = 0.3)+
  stat_density2d(data=Summer2024, aes(x = Longitude, y = Latitude, fill = ..level..),
                 geom = "polygon", alpha = 0.5, color = NA) +
  scale_fill_viridis_c(option = "rocket") +
  labs(title = "Density of Felony and Misdemeanor NYPD Incidents in Brooklyn, June - August (2024)",
       fill = "Felony and Misdemeanor Incidents") +
  coord_sf() +
  theme_classic()+theme(panel.grid = 
                          element_blank(),
                        axis.title = element_blank(),
                        axis.text = element_blank(),
                        axis.line = element_blank())

## Fall 2024 Data Loading and Cleaning 
setwd('C:/Users/ogalagedara/Documents/data for r project')
Fall2024 <- read.csv('Fall2024.csv')
Fall2024 <- Fall2024%>%filter(LAW_CAT_CD%in%c('FELONY','MISDEMEANOR'))
Fall2024$CMPLNT_NUM <- NULL
Fall2024$LOC_OF_OCCUR_DESC <- NULL
Fall2024$VIC_AGE_GROUP <- NULL
Fall2024$KY_CD <- NULL
Fall2024$ADDR_PCT_CD <- NULL
Fall2024$OFNS_DESC <- NULL
Fall2024$PD_CD <- NULL
Fall2024$PREM_TYP_DESC  <- NULL
Fall2024$PD_DESC <- NULL
Fall2024$CRM_ATPT_CPTD_CD <- NULL
Fall2024$JURIS_DESC <- NULL
Fall2024$STATION_NAME <- NULL
Fall2024$VIC_RACE <- NULL
Fall2024$VIC_SEX <- NULL
Fall2024$CMPLNT_FR_TM <- NULL
Fall2024$PATROL_BORO <- NULL
Fall2024 <- Fall2024%>%filter(!(Latitude==0 & Longitude==0))
Fall2024 <- Fall2024%>%filter(grepl('Brooklyn',BORO_NM,ignore.case=TRUE))
Fall2024 <- st_as_sf(Fall2024,
                       coords = c("Longitude","Latitude"),
                       crs = 4326,
                       remove = FALSE)
Fall2024MAP <- ggplot()+ geom_sf(data = basemap, fill = 'white', color ='black', size = 0.3)+
  stat_density2d(data=Fall2024, aes(x = Longitude, y = Latitude, fill = ..level..),
                 geom = "polygon", alpha = 0.5, color = NA) +
  scale_fill_viridis_c(option = "rocket") +
  labs(title = "Density of Felony and Misdemeanor NYPD Incidents in Brooklyn, September - November (2024)",
       fill = "Felony and Misdemeanor Incidents") +
  coord_sf() +
  theme_classic()+theme(panel.grid = 
                          element_blank(),
                        axis.title = element_blank(),
                        axis.text = element_blank(),
                        axis.line = element_blank())

Final Comments:

I attempted to web-map kernel density, via the Leaflet-Heatmap plugin; this did not work out no matter what I did. My data types are correctly converted into SF objects, with the correct coordinate systems; I looked through the R textbook as well as rpub forums to find a solution for this; found no luck below is the code i attempted to do; i tried creating a raster function, please let me know what my errors are:

kernalplot <- function(points_sf, color = ‘blue’){

coords <- st_coordinates(points_sf)

kde <- kde2d(coords[,1], coords[,2], n=100)

r <- raster(kde)

extent(r) <- extent(bbox(points_sf))

pal <- colorNumeric(c(“transparent”, color), values(r), na.color = “transparent”)

leaflet()%>%

##addTiles()%>% ## addRasterImage(r, colors=pal, opacity = 0.3)%>% ## addLegend(pal = pal, values = values(r), title = ‘Density’, opacity = 0.3) ##}