R Week 07 Assignment

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R Spatial Lab Assignment # 1

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

task 1: Set up R Project

Code

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

cat(smpCode)

hello, R markdown and RPubs!

task 2: read zip code shapefile

Code

zip_codes <- st_read('R-Spatial_I_Lab/ZIP_CODE_040114/ZIP_CODE_040114.shp')

Reading layer `ZIP_CODE_040114' from data source 
  `C:\Users\wcornejo\Documents\assign7\assign7\R-Spatial_I_Lab\ZIP_CODE_040114\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)

task 3: read and process the nys health facilities spreadsheet data (.csv file)

Code

health_facilities <- read.csv('R-Spatial_I_Lab/NYS_Health_Facility 3(in).csv')
hf_df <- health_facilities[!is.na(health_facilities$Facility.Longitude), ]
hf_df <- hf_df[!is.na(hf_df$Facility.Latitude), ]
hf_df <- hf_df[!is.na(hf_df$Facility.Longitude), ]
hf_df <- hf_df[hf_df$Facility.Latitude != 0, ]
hf_df <- hf_df[hf_df$Facility.Longitude != 0, ]
hf_sf <- st_as_sf(hf_df, coords = c("Facility.Longitude", "Facility.Latitude"))

task 4: read and process the nys retail food stores data

Code

retail_df <- read.csv('R-Spatial_I_Lab/NYS_Retail_Food_Stores.csv')
retail_df_xy <- read.csv('R-Spatial_I_Lab/nys_retail_food_store_xy.csv')
r_sf <- retail_df_xy[!is.na(retail_df_xy$X),]
r_sf <- r_sf[!is.na(r_sf$Y),]
r_sf <- st_as_sf(r_sf, coords = c("X", "Y"))
#had to save with encoding utf-8 in vscode
plot(r_sf)

Warning: plotting the first 9 out of 16 attributes; use max.plot = 16 to plot
all

Warning in min(x): no non-missing arguments to min; returning Inf

Warning in max(x): no non-missing arguments to max; returning -Inf

task 5: Use simple mapping method such as mapview with a basemap to verify the above datasets in terms of their geometry locations.

Health Facilities

Code

#mapview() + mapview(hf_sf)

Retail Stores

Code

#mapview() + mapview(r_sf)

Zip Codes

Code

mapview() + mapview(zip_codes['POPULATION'])

task 6: Save the three sf objects in a RData file or in a single GeoPackage file/database.

Code

save(zip_codes, zip_codes, 
     file = 'zip_codes_sf.RData')
save(hf_sf, health_facilities,
     file = 'health_facilities.RData')
# Now a geopackage
st_write(r_sf,          
         dsn = 'retail_stores.gpkg', 
         layer='',
         delete_layer = TRUE)

writing: substituting ENGCRS["Undefined Cartesian SRS with unknown unit"] for missing CRS

Deleting layer `' failed
Writing layer `' to data source `retail_stores.gpkg' using driver `GPKG'
Writing 23972 features with 16 fields and geometry type Point.