Assignment 4
Anne Bransford
2024-11-13
library(sf)## Warning: package 'sf' was built under R version 4.4.2## Linking to GEOS 3.12.2, GDAL 3.9.3, PROJ 9.4.1; sf_use_s2() is TRUElibrary(tmap)## Warning: package 'tmap' was built under R version 4.4.2## Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
## remotes::install_github('r-tmap/tmap')library(tidycensus)## Warning: package 'tidycensus' was built under R version 4.4.2library(mapview)
library(tigris)## Warning: package 'tigris' was built under R version 4.4.2## To enable caching of data, set `options(tigris_use_cache = TRUE)`
## in your R script or .Rprofile.#1. Download the "2017 BOND PROGRAM LINE " shapefile data from https://www.sanantonio.gov/GIS/GISDataLinks to an external site. to an external site. and visualize the lines (in green) with bexar county census tracts as the background. (2')
bexar<-tracts(state="Texas", county="Bexar", cb=T)## 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% | |========== | 15% | |=========== | 15% | |=========== | 16% | |============ | 17% | |============= | 18% | |============= | 19% | |============== | 19% | |============== | 20% | |=============== | 21% | |=============== | 22% | |================ | 22% | |================ | 23% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |=================== | 28% | |==================== | 28% | |==================== | 29% | |===================== | 30% | |====================== | 31% | |====================== | 32% | 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100%bondlines<-st_read("C:/Users/vmq938/Downloads/BondProjectLines2017/BondProjectLines2017/BondProjectLines2017.shp")## Reading layer `BondProjectLines2017' from data source
## `C:\Users\vmq938\Downloads\BondProjectLines2017\BondProjectLines2017\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)tm_shape(bexar)+
tm_borders()+
tm_shape(bondlines)+
tm_lines(col='green')
#Download the "LIBRARIES " shapefile data from https://www.sanantonio.gov/GIS/GISDataLinks to an external site. to an external site. and visualize the library point (in red) with Bexar county census tracts as the background. Make the map interactive using tmap_mode("view") (2').
libraries<-st_read("C:/Users/vmq938/Downloads/Libraries/Libraries/Libraries.shp")## Reading layer `Libraries' from data source
## `C:\Users\vmq938\Downloads\Libraries\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)tmap_mode("view")## tmap mode set to interactive viewingtm_shape(bexar)+
tm_borders()+
tm_shape(libraries)+
tm_dots()#3. Retrieve the census block group data for Travis County, TX using get_acs(), including variables like total population and poverty level. Calculate the ratio of poverty level to total population (poverty/total), and visualize this variable using polygons on a map, applying a custom color palette with a gradient of green to red (e.g., palette = "RdYlGn"). (3')
var<-c(poptotal2='B17017_001E',
poverty='B17017_002E')
st<-"TX"
ct<-"Travis"
cbg<-get_acs(geography="block group", variables=var, count=ct,
state=st, output="wide", year=2021, geometry=TRUE)## Getting data from the 2017-2021 5-year ACS## Warning: • You have not set a Census API key. Users without a key are limited to 500
## queries per day and may experience performance limitations.
## ℹ For best results, get a Census API key at
## http://api.census.gov/data/key_signup.html and then supply the key to the
## `census_api_key()` function to use it throughout your tidycensus session.
## This warning is displayed once per session.## Downloading feature geometry from the Census website. 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|=================================================================== | 96% | |==================================================================== | 97% | |==================================================================== | 98% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 99% | |======================================================================| 100%cbg$poverty_rate<-cbg$poverty/cbg$poptotal2
tm_shape(cbg)+
tm_polygons(col="poverty_rate",
palette="RdYlGn")#4. Make the coordinate systems of Bexar Couny census tract and LIBRARY the same, then use overlay analysis to find the census tract for each library. (3')
bexar<-st_transform(bexar, crs=4326)
libraries<-st_transform(libraries,crs = 4326)
lib_tract<-st_intersection(libraries, bexar)## Warning: attribute variables are assumed to be spatially constant throughout
## all geometriesknitr::opts_chunk$set(echo = TRUE)