library(sf)
## Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE
library(tmap)
## Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
## remotes::install_github('r-tmap/tmap')
library(tidycensus)
library(tigris)
## To enable caching of data, set `options(tigris_use_cache = TRUE)`
## in your R script or .Rprofile.
##Q1
bexar_ct <-tracts(state = "TX", county = "Bexar",cb=T)
## Retrieving data for the year 2022
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bond_program_line <- st_read("D:/Documents/Academics/UTSA/2_Urban Planning Methods I/Misc/Download Pile/111224/BondProjectLines2017/BondProjectLines2017.shp")
## Reading layer `BondProjectLines2017' from data source
## `D:\Documents\Academics\UTSA\2_Urban Planning Methods I\Misc\Download Pile\111224\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_ct)+
tm_borders()+
tm_shape(bond_program_line)+
tm_lines(col='green')
##Q2
libraries <- st_read("D:/Documents/Academics/UTSA/2_Urban Planning Methods I/Misc/Download Pile/111224/Libraries/Libraries.shp")
## Reading layer `Libraries' from data source
## `D:\Documents\Academics\UTSA\2_Urban Planning Methods I\Misc\Download Pile\111224\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 viewing
tm_shape(bexar_ct)+
tm_borders()+
tm_shape(libraries)+
tm_dots(col='red')
##Q3
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
## 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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cbg$poverty_rate <- cbg$poverty/cbg$poptotal2
tm_shape(cbg)+
tm_polygons(col = "poverty_rate",
palette = "RdYlGn")
##Q4
bexar_ct<-st_transform(bexar_ct,crs = 4326)
libraries<-st_transform(libraries,crs = 4326)
library_ct <- st_intersection(libraries, bexar_ct)
## Warning: attribute variables are assumed to be spatially constant throughout
## all geometries