library(ipumsr)
## Warning: package 'ipumsr' was built under R version 4.0.5
ddi <- read_ipums_ddi("C:/Users/adolp/Desktop/GIS/usa_00001 (DDI).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 "labeled" data
library(survey)
library(dplyr)
library(car)
library(ggplot2)
library(tigris)
library(classInt)
library(tmap)
library(mapview)
names(data)<-tolower(names(data))
data$pwt <- data$perwt/100
data$hwt <- data$hhwt/100
data$mig <- recode(data$migrate1, recodes = "0=NA; 9=NA; 1= 1; 2:4=0")
des<-svydesign(ids = ~cluster,
strata = ~ strata,
weights = ~pwt,
data = data)
summary(data$mig)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 1.000 1.000 0.874 1.000 1.000 17752
puma_est_sameHH<-svyby(formula = ~mig,
by = ~puma,
design = des,
FUN=svymean,
na.rm = TRUE )
head(puma_est_sameHH)
## puma mig se
## 101 101 0.7442398 0.009366589
## 102 102 0.8259565 0.006778309
## 103 103 0.8749223 0.006679989
## 104 104 0.8904980 0.008340314
## 105 105 0.8888690 0.006785526
## 106 106 0.9227006 0.006058942
pumas$puma<-as.numeric(pumas$PUMACE10)
geo1<-geo_join(pumas, puma_est_sameHH, by_sp="puma",by_df= "puma")
## Warning: `group_by_()` was deprecated in dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
head(geo1)
## Simple feature collection with 6 features and 12 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -124.4096 ymin: 33.46296 xmax: -116.8412 ymax: 41.46584
## geographic CRS: NAD83
## STATEFP10 PUMACE10 AFFGEOID10 GEOID10
## 1 06 09702 7950000US0609702 0609702
## 2 06 02300 7950000US0602300 0602300
## 3 06 08506 7950000US0608506 0608506
## 4 06 06506 7950000US0606506 0606506
## 5 06 08900 7950000US0608900 0608900
## 6 06 06103 7950000US0606103 0606103
## NAME10
## 1 Sonoma County (South)--Petaluma, Rohnert Park & Cotati Cities
## 2 Humboldt County
## 3 Santa Clara County (East)--Gilroy, Morgan Hill & San Jose (South) Cities
## 4 Riverside County (Southwest)--Hemet City & East Hemet
## 5 Shasta County--Redding City
## 6 Placer County (East/High Country Region)--Auburn & Colfax Cities
## LSAD10 ALAND10 AWATER10 puma mig se rank
## 1 P0 344472696 7555813 9702 0.8532523 0.009686046 1
## 2 P0 9241426488 1253864712 2300 0.8019943 0.009648508 1
## 3 P0 2152449674 13432167 8506 0.8776152 0.009286238 1
## 4 P0 645481741 4500965 6506 0.8328268 0.010520474 1
## 5 P0 9778407493 186302040 8900 0.8575320 0.007507578 1
## 6 P0 3094034997 246117939 6103 0.8741276 0.009498078 1
## geometry
## 1 MULTIPOLYGON (((-122.7418 3...
## 2 MULTIPOLYGON (((-124.4086 4...
## 3 MULTIPOLYGON (((-121.8558 3...
## 4 MULTIPOLYGON (((-117.1456 3...
## 5 MULTIPOLYGON (((-123.0688 4...
## 6 MULTIPOLYGON (((-121.4104 3...
tmap_mode("view")
## tmap mode set to interactive viewing
tm_basemap("OpenStreetMap.Mapnik")+
tm_shape(geo1)+
tm_polygons("mig",
style="kmeans",
n=8,
legend.hist = TRUE) +
tm_layout(legend.outside = TRUE,
title = "% of the population that lived in the same house last year in California PUMAs \n 2014-2019")
## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1