Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

title: “Homework 4” author: “Lydia Okabe” format: html editor: visual —

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##load libraries
library(censusxy)
library(readr)
library(data.table)

MAPPING WIC STORES

##LOADING WIC STORE DATA
wicstores <- read_csv("C:/Users/okabe/OneDrive/Pictures/Stats 2/GIS/wic_west_side.csv")
## New names:
## Rows: 103 Columns: 227
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (113): Source...1, Date, Obsolescence Date, Business Name, Legal Name, P... dbl
## (42): Physical Address Number, Physical ZIP, Physical ZIP 4, Mailing Ad... lgl
## (70): Physical Post Direction, Mailing Post Direction, Importer or Expo...
## 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.
## • `Source` -> `Source...1`
## • `Source` -> `Source...227`
head(wicstores)
## # A tibble: 6 × 227
##   Source…¹ Date  Obsol…² Busin…³ Legal…⁴ Physi…⁵ Physi…⁶ Physi…⁷ Physi…⁸ Physi…⁹
##   <chr>    <chr> <chr>   <chr>   <chr>   <chr>     <dbl> <chr>   <chr>   <chr>  
## 1 AtoZDat… 2/23… 8/23/2… Coalit… <NA>    1013 S…    1013 S       San Ja… St     
## 2 AtoZDat… 2/23… 8/23/2… San An… <NA>    1102 D…    1102 <NA>    Delgado St     
## 3 AtoZDat… 2/23… 8/23/2… Center… <NA>    1115 W…    1115 W       Martin  St     
## 4 AtoZDat… 2/23… 8/23/2… Profes… <NA>    1115 W…    1115 W       Martin  St     
## 5 AtoZDat… 2/23… 8/23/2… Linda … <NA>    1115 W…    1115 W       Martin  St     
## 6 AtoZDat… 2/23… 8/23/2… Adrian… Center… 1115 W…    1115 W       Martin  St     
## # … with 217 more variables: `Physical Post Direction` <lgl>,
## #   `Physical City` <chr>, `Physical State` <chr>, `Physical ZIP` <dbl>,
## #   `Physical ZIP 4` <dbl>, `Key Executive Name` <chr>, `First Name` <chr>,
## #   `Middle Initial` <chr>, `Last Name` <chr>, Title <chr>, Gender <chr>,
## #   `Location Employee Size` <dbl>, `Corporate Employee Size` <dbl>,
## #   `Revenue / Yr` <chr>, `Mailing Address` <chr>,
## #   `Mailing Address Number` <dbl>, `Mailing Pre Direction` <chr>, …
wic<-wicstores[c(6, 12:14)]
names(wic)<-c("street", "city", "st", "zip" )
head(wic)
## # A tibble: 6 × 4
##   street                city        st      zip
##   <chr>                 <chr>       <chr> <dbl>
## 1 1013 S San Jacinto St San Antonio TX    78207
## 2 1102 Delgado St       San Antonio TX    78207
## 3 1115 W Martin St      San Antonio TX    78207
## 4 1115 W Martin St      San Antonio TX    78207
## 5 1115 W Martin St      San Antonio TX    78207
## 6 1115 W Martin St      San Antonio TX    78207
library(censusxy)
wicresults<-cxy_geocode(wic,
                     street = "street",
                     city = "city",
                     state ="st",
                     zip = "zip",
                     class="sf",
                     output = "simple")
## 5 rows removed to create an sf object. These were addresses that the geocoder could not match.

Basic interactive maps of the points for WIC Service stores

Lydia Okabe

Source: https://www-atozdatabases-com.libweb.lib.utsa.edu/usbusiness/result

library(mapview)
mapview(wicresults, layer.name="WIC Services",col.regions = "green")

WIC Stores Longitude and Latitude

library(sf)
## Linking to GEOS 3.9.1, GDAL 3.4.3, PROJ 7.2.1; sf_use_s2() is TRUE
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:data.table':
## 
##     between, first, last
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
addrLL<-read.csv ("C:/Users/okabe/OneDrive/Pictures/Stats 2/GIS/wic_west_side.csv")
resultsWIC <- st_as_sf(addrLL, coords=c("Longitude", "Latitude"), crs=4269,agr="constant")
resultsWIC.proj<-st_transform(resultsWIC,
                           crs = 2278)

WIC Stores Longitude and Latitude map

Lydia Okabe

Source: https://www-atozdatabases-com.libweb.lib.utsa.edu/usbusiness/result

mapview(resultsWIC.proj,col.regions = "darkgreen")

MAPPING GROCERY STORES

##load data for grocery stores
grocerystores <- read_csv("C:/Users/okabe/OneDrive/Pictures/Stats 2/GIS/grocery_stores.csv")
## New names:
## Rows: 58 Columns: 228
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (170): Source...1, Date, Obsolescence Date, Business Name, Legal Name, P... dbl
## (45): Physical Address Number, Physical ZIP, Physical ZIP 4, Location E... lgl
## (12): Physical Post Direction, Mailing Post Direction, EIN, Importer or...
## 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.
## • `Source` -> `Source...1`
## • `Source` -> `Source...227`
## • `` -> `...228`
head(grocerystores)
## # A tibble: 6 × 228
##   Source…¹ Date  Obsol…² Busin…³ Legal…⁴ Physi…⁵ Physi…⁶ Physi…⁷ Physi…⁸ Physi…⁹
##   <chr>    <chr> <chr>   <chr>   <chr>   <chr>     <dbl> <chr>   <chr>   <chr>  
## 1 AtoZDat… 02/2… 08/23/… Surlea… <NA>    1545 S…    1545 S       San Ma… <NA>   
## 2 AtoZDat… 02/2… 08/23/… Super … <NA>    4522 F…    4522 <NA>    Freder… Rd     
## 3 AtoZDat… 02/2… 08/23/… Pico D… <NA>    111 S …     111 S       Leona   St     
## 4 AtoZDat… 02/2… 08/23/… Target  Target… 4522 F…    4522 <NA>    Freder… Rd     
## 5 AtoZDat… 02/2… 08/23/… H-E-B … <NA>    3485 F…    3485 <NA>    Freder… Rd     
## 6 AtoZDat… 02/2… 08/23/… Balcon… <NA>    3309 H…    3309 <NA>    Hillcr… Dr     
## # … with 218 more variables: `Physical Post Direction` <lgl>,
## #   `Physical City` <chr>, `Physical State` <chr>, `Physical ZIP` <dbl>,
## #   `Physical ZIP 4` <dbl>, `Key Executive Name` <chr>, `First Name` <chr>,
## #   `Middle Initial` <chr>, `Last Name` <chr>, Title <chr>, Gender <chr>,
## #   `Location Employee Size` <dbl>, `Corporate Employee Size` <dbl>,
## #   `Revenue / Yr` <chr>, `Mailing Address` <chr>,
## #   `Mailing Address Number` <dbl>, `Mailing Pre Direction` <chr>, …
grocery<-grocerystores[c(4,6, 12:14)]
names(grocery)<-c("business name","street", "city", "st", "zip" )
head(grocery)
## # A tibble: 6 × 5
##   `business name`     street                 city        st      zip
##   <chr>               <chr>                  <chr>       <chr> <dbl>
## 1 Surlean Foods       1545 S San Marcos      San Antonio TX    78207
## 2 Super Target        4522 Fredericksburg Rd San Antonio TX    78201
## 3 Pico De Gallo       111 S Leona St         San Antonio TX    78207
## 4 Target              4522 Fredericksburg Rd San Antonio TX    78201
## 5 H-E-B LP            3485 Fredericksburg Rd San Antonio TX    78201
## 6 Balcones Food Store 3309 Hillcrest Dr      San Antonio TX    78201
library(censusxy)
results<-cxy_geocode(grocery,
                     street = "street",
                     city = "city",
                     state ="st",
                     zip = "zip",
                     class="sf",
                     output = "simple")
## 4 rows removed to create an sf object. These were addresses that the geocoder could not match.

Basic interactive map of the points for grocery stores in West side San Antonio

Lydia Okabe

Source: https://www-atozdatabases-com.libweb.lib.utsa.edu/usbusiness/result

###basic map
library(mapview)
mapview(results, layer.name="Grocery Stores",col.regions = "purple")
##longitude and latitude for grocery stores

library(sf)
library(dplyr)
addrLL<-read.csv("C:/Users/okabe/OneDrive/Pictures/Stats 2/GIS/grocery_stores.csv")
resultsgrocery <- st_as_sf(addrLL, coords=c("Longitude", "Latitude"), crs=4269,agr="constant")
resultsgrocery.proj<-st_transform(resultsgrocery,
                           crs = 2278)

Longitude and latitude interactive map of the points for grocery stores in West side San Antonio

Lydia Okabe

Source: https://www-atozdatabases-com.libweb.lib.utsa.edu/usbusiness/result

mapview(resultsgrocery.proj)

Extra credit

Interactive map of the points for grocery stores in West side San Antonio with all four elements

Lydia Okabe

Source: https://www-atozdatabases-com.libweb.lib.utsa.edu/usbusiness/result

mapview(list(wicresults, resultsWIC.proj,results,resultsgrocery.proj),
        layer.name = c("WIC Locations", "WIC LL", "Grocery Stores", "Grocery StoresLL"), col.regions=list("blue","black", "green", "brown"),col=list("blue","black", "green", "brown"))