HW7
Drew Schaefer
4/13/2022
library(ipumsr)
library(survey, quietly = T)##
## Attaching package: 'survey'## The following object is masked from 'package:graphics':
##
## dotchartlibrary(tidyverse, quietly = T)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.6 ✓ dplyr 1.0.8
## ✓ tidyr 1.2.0 ✓ stringr 1.4.0
## ✓ readr 2.0.1 ✓ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x tidyr::expand() masks Matrix::expand()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
## x tidyr::pack() masks Matrix::pack()
## x tidyr::unpack() masks Matrix::unpack()library(car, quietly = T)##
## Attaching package: 'car'## The following object is masked from 'package:dplyr':
##
## recode## The following object is masked from 'package:purrr':
##
## somelibrary(ggplot2, quietly = T)
library(tigris, quietly = T)## To enable
## caching of data, set `options(tigris_use_cache = TRUE)` in your R script or .Rprofile.library(classInt, quietly = T)
library(tmap, quietly = T)ddi <- read_ipums_ddi("/Users/drewschaefer/Downloads/GIS-Dem7093/GIS/usa_00005.xml")
data <- read_ipums_micro(ddi)## Use of data from IPUMS USA is subject to conditions including that users should
## cite the data appropriately. Use command `ipums_conditions()` for more details.data<-haven::zap_labels(data) #necessary to avoid problems with "labelled" data class
names(data)<-tolower(names(data))data$pwt <- data$perwt
data$hwt <- data$hhwt
data$samehouse <- Recode(data$migrate1, recodes = "0=NA; 1=1; 2:9=0")options(tigris_class = "sf")
pumas<-pumas(state = "CA",
year = 2018,
cb = T)##
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|======================================================================| 100%plot(pumas["GEOID10"],
main = "Public Use Microdata Areas in California")
mapview::mapview(pumas, zcol= "GEOID10")## Warning: replacing previous import 'terra::extend' by 'raster::extend' when
## loading 'satellite'## Warning: replacing previous import 'terra::crop' by 'raster::crop' when loading
## 'satellite'## Warning: multiple methods tables found for 'crop'## Warning: multiple methods tables found for 'extend'des<-svydesign(ids = ~cluster,
strata = ~ strata,
weights = ~pwt,
data = data)puma_est_house<-svyby(formula = ~samehouse,
by = ~puma,
design = des,
FUN=svymean,
na.rm = TRUE )pumas$puma<-as.numeric(pumas$PUMACE10)
geo1<-left_join(pumas, puma_est_house, by=c("puma"= "puma"))
head(geo1)## Simple feature collection with 6 features and 11 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -123.0688 ymin: 32.56534 xmax: -116.0811 ymax: 41.18493
## Geodetic CRS: NAD83
## STATEFP10 PUMACE10 AFFGEOID10 GEOID10
## 1 06 04101 7950000US0604101 0604101
## 2 06 01309 7950000US0601309 0601309
## 3 06 07104 7950000US0607104 0607104
## 4 06 08900 7950000US0608900 0608900
## 5 06 05905 7950000US0605905 0605905
## 6 06 07302 7950000US0607302 0607302
## NAME10
## 1 Marin County (North & West)--Novato & San Rafael (North) Cities
## 2 Contra Costa County (East)--Brentwood & Oakley Cities
## 3 San Bernardino County (Southwest)--Phelan, Lake Arrowhead & Big Bear City
## 4 Shasta County--Redding City
## 5 Orange County (Northeast)--Lake Forest, Irvine (North) Cities & Silverado
## 6 San Diego County (North & East)--Fallbrook, Alpine & Valley Center
## LSAD10 ALAND10 AWATER10 puma samehouse se
## 1 P0 1218249181 765416684 4101 0.8638056 0.011133363
## 2 P0 365953896 56398672 1309 0.8926442 0.010129984
## 3 P0 2957261879 22807769 7104 0.8857259 0.009408765
## 4 P0 9778230074 186479459 8900 0.8575320 0.007507578
## 5 P0 374559889 2183758 5905 0.8663146 0.007305893
## 6 P0 6961523076 32694855 7302 0.8672727 0.009832366
## geometry
## 1 MULTIPOLYGON (((-123.0241 3...
## 2 MULTIPOLYGON (((-121.7789 3...
## 3 MULTIPOLYGON (((-117.6817 3...
## 4 MULTIPOLYGON (((-123.0688 4...
## 5 MULTIPOLYGON (((-117.8449 3...
## 6 MULTIPOLYGON (((-117.5097 3...tmap_mode("view")## tmap mode set to interactive viewinggeo1%>%
tm_shape()+
tm_polygons("samehouse",
style="kmeans",
n=8,
legend.hist = TRUE) +
tm_layout(legend.outside = TRUE,
title = "Living in same house rate in California PUMAs \n 2015-2019")