Lab 7

Author

Katlyn Collins

library(ggplot2)
library(ggthemes)
Warning: package 'ggthemes' was built under R version 4.3.2
library(socviz)
Warning: package 'socviz' was built under R version 4.3.2
library(maps)
Warning: package 'maps' was built under R version 4.3.2
library(mapproj)
Warning: package 'mapproj' was built under R version 4.3.2
library(viridis)
Warning: package 'viridis' was built under R version 4.3.2
Loading required package: viridisLite
Warning: package 'viridisLite' was built under R version 4.3.2

Attaching package: 'viridis'
The following object is masked from 'package:maps':

    unemp
library(tidyverse)
Warning: package 'tidyverse' was built under R version 4.3.2
Warning: package 'readr' was built under R version 4.3.2
Warning: package 'dplyr' was built under R version 4.3.2
Warning: package 'stringr' was built under R version 4.3.2
Warning: package 'forcats' was built under R version 4.3.2
Warning: package 'lubridate' was built under R version 4.3.2
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ lubridate 1.9.3     ✔ tibble    3.2.1
✔ purrr     1.0.2     ✔ tidyr     1.3.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
✖ purrr::map()    masks maps::map()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(tidycensus)
Warning: package 'tidycensus' was built under R version 4.3.3
library(leaflet)
Warning: package 'leaflet' was built under R version 4.3.3
library(stringr)

census_api_key("91d75f2026ef71780c02dbff95f245e8c42f2f15")
To install your API key for use in future sessions, run this function with `install = TRUE`.
AR_pop <- 
  get_acs(geography = "county",
          variables = "B01003_001",
          state = "AR",
          geometry = TRUE)
Getting data from the 2018-2022 5-year ACS
Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

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head(as_tibble(AR_pop))
# A tibble: 6 × 6
  GEOID NAME                   variable estimate   moe                  geometry
  <chr> <chr>                  <chr>       <dbl> <dbl>        <MULTIPOLYGON [°]>
1 05081 Little River County, … B01003_…    12024    NA (((-94.48558 33.65331, -…
2 05121 Randolph County, Arka… B01003_…    18619    NA (((-91.40687 36.49712, -…
3 05013 Calhoun County, Arkan… B01003_…     4773    NA (((-92.77672 33.53926, -…
4 05061 Howard County, Arkans… B01003_…    12779    NA (((-94.2549 34.3462, -94…
5 05099 Nevada County, Arkans… B01003_…     8292    NA (((-93.48322 33.47617, -…
6 05103 Ouachita County, Arka… B01003_…    22606    NA (((-93.11638 33.45245, -…
MapPalette <- colorQuantile(palette = "magma", domain = AR_pop$estimate, n = 20)

library(sf)
Warning: package 'sf' was built under R version 4.3.3
Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; sf_use_s2() is TRUE
AR_pop %>% 
  st_transform(crs = "+proj=longlat +datum=WGS84") %>% 
  leaflet(width = "100%", height = 500) %>% 
  addProviderTiles(provider = "Esri.WorldPhysical") %>% 
  addPolygons(popup = ~NAME,
              stroke = FALSE,
              smoothFactor = 0,
              fillOpacity = 0.7,
              color = ~ MapPalette(estimate)) %>% 
  addLegend("bottomright", 
            pal = MapPalette,
            values = ~ estimate,
            title = "Population Percentiles",
            opacity = 1) 
  AR_pop %>% 
    st_transform(crs = "+proj=longlat +datum=WGS84") %>% 
    leaflet(width = "100%", height = 500) %>% 
    addProviderTiles(provider = "Esri.WorldPhysical") %>% 
    addPolygons(popup = ~NAME,
                stroke = FALSE,
                smoothFactor = 0,
                fillOpacity = 0.7,
                color = ~ MapPalette(estimate)) %>% 
    addLegend("bottomright", 
              pal = MapPalette,
              values = ~ estimate,
              title = "Population Percentiles",
              opacity = 1)

Northwest Arkansas and Central Arkansas have the biggiest population percentiles. It seems the outer right hand portion of Arkansas also has a high population percentile. As you move down the map, the population percentiles get lower and lower.

subway_locations_in_us <- read.csv("subway_locations_in_us.csv")
View(subway_locations_in_us)

subbar <- subway_locations_in_us %>% filter(state=="AR")

subbar %>% leaflet(width = "100%") %>% 
             addTiles() %>% 
             setView(-94.0, 36.0, zoom = 8) %>% 
             addMarkers(lat = ~latitude, 
                                 lng = ~longitude, 
                                 popup = subbar$name)
Warning in validateCoords(lng, lat, funcName): Data contains 1 rows with either
missing or invalid lat/lon values and will be ignored
Northwest Arkansas, FortSmith Area, and Central Arkansas have the biggest cluster of subways. The other subways are spread out and mainly on big highways. Overall, a lot of subways are found throughout Arkansas.
MapPalette <- colorQuantile(palette = "viridis", domain = AR_pop$estimate, n = 20)


AR_pop %>% 
  st_transform(crs = "+proj=longlat +datum=WGS84") %>% 
  leaflet(width = "100%", height = 500) %>% 
  addProviderTiles(provider = "Esri.WorldPhysical") %>% 
  addPolygons(popup = ~NAME,
              stroke = FALSE,
              smoothFactor = 0,
              fillOpacity = 0.7,
              color = ~ MapPalette(estimate)) %>% 
  addLegend("bottomright", 
            pal = MapPalette,
            values = ~ estimate,
            title = "Population Percentiles",
            opacity = 1) %>% 
addCircleMarkers(data = subbar, 
                   lat = subbar$latitude,
                   lng = subbar$longitude,
                   popup = subbar$name,
                   weight = 1,
                   radius=3,
                   color = "white", 
                   opacity = 9)
Warning in validateCoords(lng, lat, funcName): Data contains 1 rows with either
missing or invalid lat/lon values and will be ignored

Areas in Arkansas with the highest population percentiles also have the highest number of subways in that area. Areas that don’t have as big of a population percentile, have very little subways in their area. The majority of subways in Arkansas are found in the northern region.