Assignment 4 new
Joseph
2024-11-13
# Set repository for package installations
options(repos = c(CRAN = "https://cloud.r-project.org"))
# Load required libraries
library(sf)## Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUElibrary(tmap)## Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
## remotes::install_github('r-tmap/tmap')library(tidycensus)
library(tigris) # Required for using tracts() function## To enable caching of data, set `options(tigris_use_cache = TRUE)`
## in your R script or .Rprofile.# Download census tracts for Bexar County, Texas, using tigris
# Note: cb = TRUE to get cartographic boundaries for better visualization
bexar_ct <- tracts(state = "TX", county = "Bexar", cb = TRUE)## Retrieving data for the year 2022## | | | 0% | |= | 1% | |= | 2% | |== | 2% | |== | 3% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 9% | |======= | 10% | |======= | 11% | |======== | 11% | |======== | 12% | |========= | 12% | |========= | 13% | |========= | 14% | |========== | 14% | |========== | 15% | |=========== | 15% | |=========== | 16% | |============ | 17% | |============ | 18% | |============= | 18% | |============= | 19% | |============== | 19% | |============== | 20% | |=============== | 21% | |=============== | 22% | |================ | 22% | |================ | 23% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |=================== | 28% | |==================== | 28% | |==================== | 29% | |===================== | 29% | |===================== | 30% | |===================== | 31% | |====================== | 31% | |====================== | 32% | |======================= | 32% | |======================= | 33% | |======================= | 34% | |======================== | 34% | |======================== | 35% | |========================= | 35% | |========================= | 36% | |========================== | 36% | |========================== | 37% | |========================== | 38% | |=========================== | 38% | |=========================== | 39% | |============================ | 39% | |============================ | 40% | |============================ | 41% | |============================= | 41% | |============================= | 42% | |============================== | 42% | |============================== | 43% | |=============================== | 44% | |=============================== | 45% | |================================ | 46% | |================================= | 47% | |================================= | 48% | |================================== | 48% | |================================== | 49% | |=================================== | 49% | |=================================== | 50% | |==================================== | 51% | |==================================== | 52% | |===================================== | 52% | |===================================== | 53% | |====================================== | 54% | |====================================== | 55% | |======================================= | 55% | |======================================= | 56% | |======================================== | 57% | |======================================== | 58% | |========================================= | 58% | |========================================= | 59% | |========================================== | 60% | |========================================== | 61% | |=========================================== | 61% | |=========================================== | 62% | |============================================ | 62% | |============================================ | 63% | |============================================= | 64% | |============================================= | 65% | |============================================== | 65% | |============================================== | 66% | |=============================================== | 67% | |=============================================== | 68% | |================================================ | 68% | |================================================ | 69% | |================================================= | 69% | |================================================= | 70% | |================================================= | 71% | |================================================== | 71% | |================================================== | 72% | |=================================================== | 72% | |=================================================== | 73% | |=================================================== | 74% | |==================================================== | 74% | |==================================================== | 75% | |===================================================== | 75% | |===================================================== | 76% | |====================================================== | 77% | |====================================================== | 78% | |======================================================= | 78% | |======================================================= | 79% | |======================================================== | 79% | |======================================================== | 80% | |========================================================= | 81% | |========================================================= | 82% | |========================================================== | 82% | |========================================================== | 83% | |=========================================================== | 84% | |=========================================================== | 85% | |============================================================ | 85% | |============================================================ | 86% | |============================================================= | 87% | |============================================================= | 88% | |============================================================== | 88% | |============================================================== | 89% | |=============================================================== | 90% | |=============================================================== | 91% | |================================================================ | 91% | |================================================================ | 92% | |================================================================= | 93% | |================================================================== | 94% | |================================================================== | 95% | |=================================================================== | 95% | |=================================================================== | 96% | |==================================================================== | 97% | |==================================================================== | 98% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 99% | |======================================================================| 100%# Read Bond Project Lines shapefile
bond_program_line <- st_read("/Users/jayjay/Desktop/BondProjectLines20172/BondProjectLines2017.shp")## Reading layer `BondProjectLines2017' from data source
## `/Users/jayjay/Desktop/BondProjectLines20172/BondProjectLines2017.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 69 features and 24 fields
## Geometry type: MULTILINESTRING
## Dimension: XY
## Bounding box: xmin: 2078269 ymin: 13665110 xmax: 2168346 ymax: 13783530
## Projected CRS: NAD83 / Texas South Central (ftUS)# Plot Bexar County tracts and Bond Project Lines
tmap_mode("plot") # Switch to plot mode## tmap mode set to plottingtm_shape(bexar_ct) +
tm_borders() +
tm_shape(bond_program_line) +
tm_lines(col = "orange")
## Q2: Plot Libraries
# Read Libraries shapefile
libraries <- st_read("/Users/jayjay/Downloads/Libraries/Libraries.shp")## Reading layer `Libraries' from data source
## `/Users/jayjay/Downloads/Libraries/Libraries.shp' using driver `ESRI Shapefile'
## Simple feature collection with 30 features and 9 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: 2075828 ymin: 13669570 xmax: 2170361 ymax: 13779280
## Projected CRS: NAD83 / Texas South Central (ftUS)# Plot Bexar County tracts and Libraries as points
tm_shape(bexar_ct) +
tm_borders() +
tm_shape(libraries) +
tm_dots(col = "violet")
## Q3: Retrieve ACS Data and Calculate Poverty Rate
# Define variables for total population and poverty counts
var <- c(poptotal2 = 'B17017_001E', poverty = 'B17017_002E')
# Specify state and county
st <- "TX"
ct <- "Travis"
# Retrieve block group-level ACS data for Travis County, Texas
cbg <- get_acs(geography = "block group", variables = var, county = ct,
state = st, output = "wide", year = 2021, geometry = TRUE)## Getting data from the 2017-2021 5-year ACS## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.## | | | 0% | | | 1% | |= | 1% | |= | 2% | |== | 2% | |== | 3% | |== | 4% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 9% | |======= | 10% | |======= | 11% | |======== | 11% | |======== | 12% | |========= | 12% | |========= | 13% | |========= | 14% | |========== | 14% | |========== | 15% | |=========== | 15% | |=========== | 16% | |============ | 17% | |============ | 18% | |============= | 18% | |============= | 19% | |============== | 19% | |============== | 20% | |============== | 21% | |=============== | 21% | |=============== | 22% | |================ | 22% | |================ | 23% | |================ | 24% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |=================== | 28% | |==================== | 28% | |==================== | 29% | |===================== | 29% | |===================== | 30% | |====================== | 31% | |====================== | 32% | |======================= | 32% | |======================= | 33% | |======================= | 34% | |======================== | 34% | |======================== | 35% | |========================= | 35% | |========================= | 36% | |========================== | 37% | |========================== | 38% | |=========================== | 38% | |=========================== | 39% | |============================ | 39% | |============================ | 40% | |============================ | 41% | |============================= | 41% | |============================= | 42% | |============================== | 42% | |============================== | 43% | |=============================== | 44% | |=============================== | 45% | |================================ | 45% | |================================ | 46% | |================================= | 46% | |================================= | 47% | |================================= | 48% | |================================== | 48% | |================================== | 49% | |=================================== | 49% | |=================================== | 50% | |=================================== | 51% | |==================================== | 51% | |==================================== | 52% | |===================================== | 52% | |===================================== | 53% | |====================================== | 54% | |====================================== | 55% | |======================================= | 55% | |======================================= | 56% | |======================================== | 57% | |======================================== | 58% | |========================================= | 58% | |========================================= | 59% | |========================================== | 59% | |========================================== | 60% | |========================================== | 61% | |=========================================== | 61% | |=========================================== | 62% | |============================================ | 62% | |============================================ | 63% | |============================================ | 64% | |============================================= | 64% | |============================================= | 65% | |============================================== | 65% | |============================================== | 66% | |=============================================== | 67% | |=============================================== | 68% | |================================================ | 68% | |================================================ | 69% | |================================================= | 69% | |================================================= | 70% | |================================================== | 71% | |================================================== | 72% | |=================================================== | 72% | |=================================================== | 73% | |=================================================== | 74% | |==================================================== | 74% | |==================================================== | 75% | |===================================================== | 75% | |===================================================== | 76% | |====================================================== | 77% | |======================================================= | 78% | |======================================================= | 79% | |======================================================== | 79% | |======================================================== | 80% | |======================================================== | 81% | |========================================================= | 81% | |========================================================= | 82% | |========================================================== | 82% | |========================================================== | 83% | |=========================================================== | 84% | |=========================================================== | 85% | |============================================================ | 85% | |============================================================ | 86% | |============================================================= | 86% | |============================================================= | 87% | |============================================================= | 88% | |============================================================== | 88% | |============================================================== | 89% | |=============================================================== | 89% | |=============================================================== | 90% | |=============================================================== | 91% | |================================================================ | 91% | |================================================================ | 92% | |================================================================= | 92% | |================================================================= | 93% | |================================================================== | 94% | |================================================================== | 95% | |=================================================================== | 95% | |=================================================================== | 96% | |==================================================================== | 96% | |==================================================================== | 97% | |==================================================================== | 98% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 99% | |======================================================================| 100%# Calculate poverty rate
cbg$poverty_rate <- cbg$poverty / cbg$poptotal2
# Plot poverty rate in Travis County
tm_shape(cbg) +
tm_polygons(col = "poverty_rate", palette = "RdYlGn")
## Q4: Spatial Transformation and Intersection
# Ensure both spatial objects are in the same coordinate reference system (CRS)
bexar_ct <- st_transform(bexar_ct, crs = 4326)
libraries <- st_transform(libraries, crs = 4326)
# Perform spatial intersection to find libraries within Bexar County tracts
library_ct <- st_intersection(libraries, bexar_ct)## Warning: attribute variables are assumed to be spatially constant throughout
## all geometries# Display intersection result
print(library_ct)## Simple feature collection with 30 features and 22 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -98.66264 ymin: 29.33487 xmax: -98.36605 ymax: 29.63648
## Geodetic CRS: WGS 84
## First 10 features:
## Name Address Phone
## 10 Potranco Branch 8765 State Hwy 151 (Access Rd) <NA>
## 25 Maury Maverick Jr Branch 8700 Mystic Park 210.680.9346
## 11 Henry A. Guerra Jr Branch 7978 W. Military Dr 210.673.1492
## 18 Bazan Branch 2200 W Commerce St 210.225.1614
## 2 Collins Garden Branch 200 N Park Blvd 210.225.0331
## 30 Roosevelt Branch 5110 Walzem Rd 210.650.1122
## 27 Las Palmas Branch 515 Castroville Rd 210.434.6394
## 20 Kampmann Portal 210 W Market St 210.207.2500
## 22 Central Library 600 Soledad 210.207.2500
## 8 Parman Branch 20735 Wilderness Oak 210.207.2703
## Zipcode Number PrefixDire StreetName StreetType
## 10 78250 8765 <NA> StTATE HWY 151 HWY
## 25 78254 8700 <NA> MYSTIC PARK <NA>
## 11 78227 7978 W MILITARY DR
## 18 78207 2200 W COMMERCE ST
## 2 78204 200 N PARK BLVD
## 30 78218 5110 <NA> WALZEM RD
## 27 78237 515 <NA> CASTROVILLE RD
## 20 78205 210 W MARKET ST ST
## 22 78205 600 <NA> SOLEDAD <NA>
## 8 78258 <NA> <NA> WILDERNESS OAK <NA>
## Website STATEFP COUNTYFP TRACTCE
## 10 <NA> 48 029 171926
## 25 www.sanantonio.gov/library/branch/maverick.asp 48 029 181703
## 11 www.sanantonio.gov/library/branch/guerra.asp 48 029 171700
## 18 www.sat.lib.tx.us/branches/bazan.htm 48 029 170200
## 2 www.sat.lib.tx.us/branches/collinsgarden.htm 48 029 160200
## 30 <NA> 48 029 121403
## 27 www.sat.lib.tx.us/branches/laspalmas.htm 48 029 170900
## 20 <NA> 48 029 110100
## 22 www.sat.lib.tx.us/html/centralphotos.htm 48 029 110100
## 8 <NA> 48 029 191811
## AFFGEOID GEOID NAME NAMELSAD STUSPS
## 10 1400000US48029171926 48029171926 1719.26 Census Tract 1719.26 TX
## 25 1400000US48029181703 48029181703 1817.03 Census Tract 1817.03 TX
## 11 1400000US48029171700 48029171700 1717 Census Tract 1717 TX
## 18 1400000US48029170200 48029170200 1702 Census Tract 1702 TX
## 2 1400000US48029160200 48029160200 1602 Census Tract 1602 TX
## 30 1400000US48029121403 48029121403 1214.03 Census Tract 1214.03 TX
## 27 1400000US48029170900 48029170900 1709 Census Tract 1709 TX
## 20 1400000US48029110100 48029110100 1101 Census Tract 1101 TX
## 22 1400000US48029110100 48029110100 1101 Census Tract 1101 TX
## 8 1400000US48029191811 48029191811 1918.11 Census Tract 1918.11 TX
## NAMELSADCO STATE_NAME LSAD ALAND AWATER geometry
## 10 Bexar County Texas CT 3301430 1475 POINT (-98.66067 29.44238)
## 25 Bexar County Texas CT 3764552 2533 POINT (-98.64214 29.52431)
## 11 Bexar County Texas CT 10635977 31619 POINT (-98.62553 29.42446)
## 18 Bexar County Texas CT 1730790 0 POINT (-98.51954 29.42716)
## 2 Bexar County Texas CT 1088272 0 POINT (-98.51508 29.39835)
## 30 Bexar County Texas CT 4504203 8119 POINT (-98.38969 29.5094)
## 27 Bexar County Texas CT 1844410 13947 POINT (-98.54955 29.41818)
## 20 Bexar County Texas CT 3428908 13720 POINT (-98.48894 29.42293)
## 22 Bexar County Texas CT 3428908 13720 POINT (-98.49251 29.43203)
## 8 Bexar County Texas CT 6092837 2297 POINT (-98.51492 29.63648)