library(ggplot2)
library(ggthemes)
library(socviz)
library(maps)
library(mapproj)
library(viridis)DVLab7
Subway and Population Overlay
library(tidyverse)
library(tidycensus)
library(leaflet)
library(stringr)
census_api_key("2b86d958f8aa678b59489cf543adc5f1264ce053", overwrite = TRUE)
TX_pop <-
get_acs(geography = "county",
variables = "B01003_001",
state = "TX",
geometry = TRUE)
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|======================================================================| 100%head(as_tibble(TX_pop))# A tibble: 6 × 6
GEOID NAME variable estimate moe geometry
<chr> <chr> <chr> <dbl> <dbl> <MULTIPOLYGON [°]>
1 48273 Kleberg County, Texas B01003_… 30860 NA (((-97.3178 27.49456, -9…
2 48391 Refugio County, Texas B01003_… 6718 NA (((-97.54085 28.16496, -…
3 48201 Harris County, Texas B01003_… 4726177 NA (((-94.97839 29.68365, -…
4 48443 Terrell County, Texas B01003_… 862 252 (((-102.5669 30.28327, -…
5 48229 Hudspeth County, Texas B01003_… 3329 NA (((-105.998 32.00233, -1…
6 48205 Hartley County, Texas B01003_… 5369 NA (((-103.0422 35.82522, -…Create a Cholopleth Using Leaflet for Arkansas Counties
MapPalette <- colorQuantile(palette = "viridis", domain = TX_pop$estimate, n = 20)
library(sf)
TX_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) In Texas there are some highly populated counties in the east side. These counties appear to be the Dallas and Austin areas where there are large cities. The western half of texas has a lower population proably due to the fact that that area is mainly farm land or desert.
Plotting Subway Locations
subway <- read.csv("subway_locations_in_us.csv")
head(subway) X title address_1 address_2
1 0 Tikahtnu Commons S/C 1118 N Muldoon Rd Suite 115
2 1 1307 W Northern Lights 1307 W Northern Lights
3 2 1330 Huffman Rd 1330 Huffman Rd
4 3 2715 E. Tudor Road 2715 E. Tudor Road
5 4 Alaska Regional Hospital 2801 Debarr Rd
6 5 3104 Seward Hwy 3104 Seward Hwy
open_hours
1 Closed Today 10:30 AM - 7:00 PM 10:30 AM - 7:00 PM 10:30 AM - 7:00 PM 10:30 AM - 8:00 PM 10:30 AM - 8:00 PM 10:30 AM - 7:00 PM
2 9:00 AM - 9:00 PM 9:00 AM - 9:00 PM 9:00 AM - 9:00 PM 9:00 AM - 9:00 PM 9:00 AM - 9:00 PM 10:00 AM - 9:00 PM 11:00 AM - 8:00 PM
3 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 9:00 AM - 9:00 PM 10:00 AM - 8:00 PM
4 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 10:00 AM - 10:00 PM 11:00 AM - 10:00 PM
5 Closed Today Closed Today Closed Today Closed Today Closed Today Closed Today Closed Today
6 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 8:00 AM - 10:00 PM 10:00 AM - 10:00 PM 11:00 AM - 9:00 PM
city state postal_code latitude longitude
1 Anchorage AK 99504 61.2037 -149.7447
2 Anchorage AK 99503 61.1900 -149.8938
3 Anchorage AK 99515 61.1194 -149.8974
4 Anchorage AK 99507 61.1535 -149.8289
5 Anchorage AK 99508 61.2060 -149.8101
6 Anchorage AK 99503 61.1900 -149.8938tbar <- subway %>% filter(state=="TX")
tbar %>% leaflet(width = "100%") %>%
addTiles() %>%
setView(-99.0, 31.0, zoom = 3.5) %>%
addMarkers(lat = ~latitude,
lng = ~longitude,
popup = tbar$name)Again we can see that the majority of Subways are in the eastern half of the state where the large cities are located. There are also a large number of Subway’s located in the state of Texas.
Combine Choropleth and Locations
MapPalette <- colorQuantile(palette = "viridis", domain = TX_pop$estimate, n = 20)
TX_pop %>%
st_transform(crs = "+proj=longlat +datum=WGS84") %>%
leaflet(width = "100%", height = 500) %>%
addProviderTiles(provider = "Esri.WorldPhysical") %>%
addPolygons(popup = ~NAME,
stroke = FALSE,
smoothFactor = 0,
fillOpacity = 0.7,
color = ~ MapPalette(estimate)) %>%
addLegend("bottomright",
pal = MapPalette,
values = ~ estimate,
title = "Population Percentiles",
opacity = 1) %>%
addCircleMarkers(data = tbar,
lat = tbar$latitude,
lng = tbar$longitude,
popup = tbar$name,
weight = 1,
radius=4,
color = "white",
opacity = 1)In those yellow highly populated areas there are a lot of dots representing Subway’s located in that county.These (coming from the top down) are the Dallas Fort-Worth Area, the Austin area, the Houston area and the Rio Grand area. There is also a yellow county on the far west handle of Texas where the city of El Paso resides. Overall Texas is a large state with a lot of Subway locations especially in counties that have a population percentage of 90-100%