R Week 07 Assignment

Author

Caitlin Cacciatore

Published

March 12, 2026

install.packages(‘knitr’)

library(knitr)

Explanation of the template

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Check out the Source Code from the top-right corner </>Code menu.

In the following R code chunk, load_packages is the code chunk name. include=FALSE suggests that the code chunk will run, but the code itself and its outputs will not be included in the rendered HTML. echo=TRUE in the following code chunk suggests that the code and results from running the code will be included in the rendered HTML.

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require(tidyverse);
Loading required package: tidyverse
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.2.0     ✔ readr     2.1.6
✔ forcats   1.0.1     ✔ stringr   1.6.0
✔ ggplot2   4.0.2     ✔ tibble    3.3.1
✔ lubridate 1.9.5     ✔ tidyr     1.3.2
✔ purrr     1.2.1     
── 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
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require(sf); 
Loading required package: sf
Linking to GEOS 3.13.0, GDAL 3.8.5, PROJ 9.5.1; sf_use_s2() is TRUE
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require(mapview); 
Loading required package: mapview
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require(magrittr)
Loading required package: magrittr

Attaching package: 'magrittr'

The following object is masked from 'package:purrr':

    set_names

The following object is masked from 'package:tidyr':

    extract

R Spatial Lab Assignment # 1

#Load the Packages

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#Loading the Packages

options(repos = c(CRAN = "https://cloud.r-project.org"))

# Load a list of packages. Install them first if they are not available.
# The list of packages to be installed
list.of.packages <- c("sf", "sp", "spatial", "maptools", "rgeos","rgdal",
                      "raster", "grid", "rasterVis",
                      "tidyverse", "magrittr", "ggpubr", "lubridate",
                      "devtools", "htmlwidgets", "mapview",
                      "classInt", "RColorBrewer", "ggmap", "tmap", "leaflet", "mapview",
                      "ggrepel", "ggsn",
                      "spdep","spatialreg","GWmodel");

# Check out the packages that have not been installed yet.
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]

# Install those missing packages first. It could take a long time for the first time.
if(length(new.packages)>0) install.packages(new.packages)
Warning: packages 'maptools', 'rgeos', 'rgdal', 'ggsn' are not available for this version of R

Versions of these packages for your version of R might be available elsewhere,
see the ideas at
https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
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# Load all packages.

lapply(list.of.packages,function(x) {
  require(x,character.only = TRUE,quietly = TRUE)
})

Attaching package: 'raster'
The following object is masked from 'package:dplyr':

    select

Attaching package: 'ggpubr'
The following object is masked from 'package:raster':

    rotate
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.

Attaching package: 'ggmap'


The following object is masked from 'package:magrittr':

    inset


To access larger datasets in this package, install the spDataLarge
package with: `install.packages('spDataLarge',
repos='https://nowosad.github.io/drat/', type='source')`


Attaching package: 'Matrix'


The following objects are masked from 'package:tidyr':

    expand, pack, unpack



Attaching package: 'spatialreg'


The following objects are masked from 'package:spdep':

    get.ClusterOption, get.coresOption, get.mcOption,
    get.VerboseOption, get.ZeroPolicyOption, set.ClusterOption,
    set.coresOption, set.mcOption, set.VerboseOption,
    set.ZeroPolicyOption
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install.packages("sf")     # run once if not installed

The downloaded binary packages are in
    /var/folders/dm/sj7012g577qdnv76gj2_szd80000gp/T//Rtmpt2Ly0E/downloaded_packages
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install.packages("tidyverse")

The downloaded binary packages are in
    /var/folders/dm/sj7012g577qdnv76gj2_szd80000gp/T//Rtmpt2Ly0E/downloaded_packages
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library(sf)
library(tidyverse)

ZIP CODE DATA CODE

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# read the file 

zip_sf <- st_read("Zip_Code_040114.shp")
Reading layer `ZIP_CODE_040114' from data source 
  `/Users/heliosselene/Desktop/Hunter/R-Spatial/ZIP_CODE_040114.shp' 
  using driver `ESRI Shapefile'
Simple feature collection with 263 features and 12 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 913129 ymin: 120020.9 xmax: 1067494 ymax: 272710.9
Projected CRS: NAD83 / New York Long Island (ftUS)
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#clean the data

zip_nyc <- zip_sf %>%
  filter(!is.na("Zip Code"))

nyc_zip_sf <- st_as_sf(zip_nyc,crs = 4326)

# create  fancy plots

plot(nyc_zip_sf)
Warning: plotting the first 9 out of 12 attributes; use max.plot = 12 to plot
all

Health Facilities Code

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# read the file


NY_Health_df <- read_csv("NYS_Health_Facility.csv", 
                               show_col_types = FALSE, 
                               lazy = FALSE) 

# checking structure
                               
str(NY_Health_df)
spc_tbl_ [3,990 × 36] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ Facility ID                 : num [1:3990] 204 620 654 1156 2589 ...
 $ Facility Name               : chr [1:3990] "Hospice at Lourdes" "Charles T Sitrin Health Care Center Inc" "Central Park Rehabilitation and Nursing Center" "East Side Nursing Home" ...
 $ Short Description           : chr [1:3990] "HSPC" "NH" "NH" "NH" ...
 $ Description                 : chr [1:3990] "Hospice" "Residential Health Care Facility - SNF" "Residential Health Care Facility - SNF" "Residential Health Care Facility - SNF" ...
 $ Facility Open Date          : chr [1:3990] "06/01/1985" "02/01/1989" "02/01/1989" "08/01/1979" ...
 $ Facility Address 1          : chr [1:3990] "4102 Old Vestal Road" "2050 Tilden Avenue" "116 Martin Luther King East" "62 Prospect St" ...
 $ Facility Address 2          : chr [1:3990] NA NA NA NA ...
 $ Facility City               : chr [1:3990] "Vestal" "New Hartford" "Syracuse" "Warsaw" ...
 $ Facility State              : chr [1:3990] "New York" "New York" "New York" "New York" ...
 $ Facility Zip Code           : chr [1:3990] "13850" "13413" "13205" "14569" ...
 $ Facility Phone Number       : num [1:3990] 6.08e+09 3.16e+09 3.15e+09 5.86e+09 5.86e+09 ...
 $ Facility Fax Number         : num [1:3990] NA NA NA NA NA ...
 $ Facility Website            : chr [1:3990] NA NA NA NA ...
 $ Facility County Code        : num [1:3990] 3 32 33 60 2 ...
 $ Facility County             : chr [1:3990] "Broome" "Oneida" "Onondaga" "Wyoming" ...
 $ Regional Office ID          : num [1:3990] 3 3 3 1 1 1 7 1 7 5 ...
 $ Regional Office             : chr [1:3990] "Central New York Regional Office" "Central New York Regional Office" "Central New York Regional Office" "Western Regional Office - Buffalo" ...
 $ Main Site Name              : chr [1:3990] NA NA NA NA ...
 $ Main Site Facility ID       : num [1:3990] NA NA NA NA NA ...
 $ Operating Certificate Number: chr [1:3990] "0301501F" "3227304N" "3301326N" "6027303N" ...
 $ Operator Name               : chr [1:3990] "Our Lady of Lourdes Memorial Hospital Inc" "Charles T Sitrin Health Care Center, Inc" "CPRNC, LLC" "East Side Nursing Home Inc" ...
 $ Operator Address 1          : chr [1:3990] "169 Riverside Drive" "Box 1000 Tilden Avenue" "116 Martin Luther King East" "62 Prospect Street" ...
 $ Operator Address 2          : chr [1:3990] NA NA NA NA ...
 $ Operator City               : chr [1:3990] "Binghamton" "New Hartford" "Syracuse" "Warsaw" ...
 $ Operator State              : chr [1:3990] "New York" "New York" "New York" "New York" ...
 $ Operator Zip Code           : chr [1:3990] "13905" "13413" "13205" "14569" ...
 $ Cooperator Name             : chr [1:3990] NA NA NA NA ...
 $ Cooperator Address          : chr [1:3990] NA NA NA NA ...
 $ Cooperator Address 2        : chr [1:3990] NA NA NA NA ...
 $ Cooperator City             : chr [1:3990] NA NA NA NA ...
 $ Cooperator State            : chr [1:3990] "New York" "New York" "New York" "New York" ...
 $ Cooperator Zip Code         : chr [1:3990] NA NA NA NA ...
 $ Ownership Type              : chr [1:3990] "Not for Profit Corporation" "Not for Profit Corporation" "LLC" "Business Corporation" ...
 $ Facility Latitude           : num [1:3990] 42.1 43.1 NA 42.7 42.1 ...
 $ Facility Longitude          : num [1:3990] -76 -75.2 NA -78.1 -78 ...
 $ Facility Location           : chr [1:3990] "(42.097095, -75.975243)" "(43.05497, -75.228828)" NA "(42.738979, -78.12867)" ...
 - attr(*, "spec")=
  .. cols(
  ..   `Facility ID` = col_double(),
  ..   `Facility Name` = col_character(),
  ..   `Short Description` = col_character(),
  ..   Description = col_character(),
  ..   `Facility Open Date` = col_character(),
  ..   `Facility Address 1` = col_character(),
  ..   `Facility Address 2` = col_character(),
  ..   `Facility City` = col_character(),
  ..   `Facility State` = col_character(),
  ..   `Facility Zip Code` = col_character(),
  ..   `Facility Phone Number` = col_double(),
  ..   `Facility Fax Number` = col_double(),
  ..   `Facility Website` = col_character(),
  ..   `Facility County Code` = col_double(),
  ..   `Facility County` = col_character(),
  ..   `Regional Office ID` = col_double(),
  ..   `Regional Office` = col_character(),
  ..   `Main Site Name` = col_character(),
  ..   `Main Site Facility ID` = col_double(),
  ..   `Operating Certificate Number` = col_character(),
  ..   `Operator Name` = col_character(),
  ..   `Operator Address 1` = col_character(),
  ..   `Operator Address 2` = col_character(),
  ..   `Operator City` = col_character(),
  ..   `Operator State` = col_character(),
  ..   `Operator Zip Code` = col_character(),
  ..   `Cooperator Name` = col_character(),
  ..   `Cooperator Address` = col_character(),
  ..   `Cooperator Address 2` = col_character(),
  ..   `Cooperator City` = col_character(),
  ..   `Cooperator State` = col_character(),
  ..   `Cooperator Zip Code` = col_character(),
  ..   `Ownership Type` = col_character(),
  ..   `Facility Latitude` = col_double(),
  ..   `Facility Longitude` = col_double(),
  ..   `Facility Location` = col_character()
  .. )
 - attr(*, "problems")=<externalptr>
Show the code 
#clean the data


NY_Health_df_clean <- NY_Health_df %>%
  filter(!is.na(`Facility Longitude`) & !is.na(`Facility Latitude`))

# Convert to sf


library(sf)

NY_Health_sf <- st_as_sf(
  NY_Health_df_clean,
  coords = c("Facility Longitude", "Facility Latitude"),
  crs = 4326
)

# create a nice little (simple) plot

plot(st_geometry(NY_Health_sf),xlim=c(-70,-80),ylim=c(40,45))

Show the code 
plot(st_geometry(NY_Health_sf["Facility Zip Code"]),
     xlim = c(-80, -71),
     ylim = c(40, 46))

RETAIL FOOD STORES CODE

I could not get this part to render despite an hour of attempts. Please forgive

that this is not in code format; and please advise on how I could render it

in the future. Many thanks.

install.packages(“janitor”) library(janitor)

nys_retail_food_store_xy_df <- read_csv(“nys_retail_food_store_xy.csv”, show_col_types = FALSE, lazy = FALSE) %>%

str(nys_retail_food_store_xy_df)

Remove rows with those missing coordinates

nys_clean_data <- nys_retail_food_store_xy_df %>% filter(!is.na(“x”) & !is.na(“y”))

Convert to sf object (longitude first, latitude second)

nys_retail_food_store_xy_sf <- st_as_sf( nys_clean_data, coords = c(“x”, “y”), # X = longitude, Y = latitude crs = 4326 )

#check structure

str(nys_retail_food_store_xy_sf)

make a plot

plot(st_geometry(nys_retail_food_store_xy_sf))

Don’t use a single chunk for the entire assignment. Break it into multiple chunks.

You can name the code chunk and also set options.

task 1:

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smpCode <- "hello, R markdown and RPubs!"

cat(smpCode)
hello, R markdown and RPubs!

task 2:

Quarto markdown is different from R markdown in terms of chunk options. See chunk options at Quarto website.

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print("This is the new code chunk options available in Quarto Markdown")
[1] "This is the new code chunk options available in Quarto Markdown"