library(tidycensus)
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.0.5 v dplyr 1.0.4
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.0
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(sf)
## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
library(tmap)
v11_Profile <- load_variables(2011, "acs5/profile", cache = TRUE)
v19_Profile <- load_variables(2019 , "acs5/profile", cache = TRUE)
v11_Profile[grep(x = v11_Profile$label, "Vacant housing units", ignore.case = TRUE), c("name", "label")]
## # A tibble: 2 x 2
## name label
## <chr> <chr>
## 1 DP04_0003 Estimate!!HOUSING OCCUPANCY!!Vacant housing units
## 2 DP04_0003P Percent!!HOUSING OCCUPANCY!!Vacant housing units
v19_Profile[grep(x = v19_Profile$label, "Percent Vacant housing units", ignore.case = TRUE), c("name", "label")]
## # A tibble: 0 x 2
## # ... with 2 variables: name <chr>, label <chr>
vac11sa<-get_acs(geography = "tract",
state="TX",
county = "Bexar",
year = 2011,
variables="DP04_0003P" ,
geometry = T,
output = "wide")
## Getting data from the 2007-2011 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## Using the ACS Data Profile
vac11sa <- vac11sa%>%
mutate(pvac11 = DP04_0003PE,
pvac_er11 = DP04_0003PM/1.645,
pvac_cv11 =100* (pvac_er11/pvac11)) %>%
filter(complete.cases(pvac11), is.finite(pvac_cv11)==T)
head(vac11sa)
summary(vac11sa)
vac11d<-get_acs(geography = "tract",
state="TX",
county = "Dallas",
year = 2011,
variables="DP04_0003P" ,
geometry = T,
output = "wide")
## Getting data from the 2007-2011 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## Using the ACS Data Profile
vac11d <- vac11d%>%
mutate(pvac11 = DP04_0003PE,
pvac_er11 = DP04_0003PM/1.645,
pvac_cv11 =100* (pvac_er11/pvac11)) %>%
filter(complete.cases(pvac11), is.finite(pvac_cv11)==T)
head(vac11d)
summary(vac11d)
vac19sa<-get_acs(geography = "tract",
state="TX",
county = "Bexar",
year = 2019,
variables="DP04_0003P" ,
geometry = T,
output = "wide")
## Getting data from the 2015-2019 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## Using the ACS Data Profile
vac19sa <- vac19sa%>%
mutate(pvac19 = DP04_0003PE,
pvac_er19 = DP04_0003PM/1.645,
pvac_cv19 =100* (pvac_er19/pvac19)) %>%
filter(complete.cases(pvac19), is.finite(pvac_cv19)==T)
head(vac19sa)
summary(vac19sa)
vac19d<-get_acs(geography = "tract",
state="TX",
county = "Dallas",
year = 2019,
variables="DP04_0003P" ,
geometry = T,
output = "wide")
## Getting data from the 2015-2019 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## Using the ACS Data Profile
vac19d <- vac19d%>%
mutate(pvac19 = DP04_0003PE,
pvac_er19 = DP04_0003PM/1.645,
pvac_cv19 =100* (pvac_er19/pvac19)) %>%
filter(complete.cases(pvac19), is.finite(pvac_cv19)==T)
head(vac19d)
summary(vac19d)
tm_shape(vac11sa)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Quantile Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac11d)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Quantile Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19sa)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Quantile Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19d)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Quantile Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac11sa)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="pretty", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Pretty Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac11d)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="pretty", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Pretty Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19sa)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="pretty", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Pretty Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19d)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="pretty", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Pretty Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac11sa)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="jenks", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Jenks Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac11d)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="pretty", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Pretty Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19sa)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="jenks", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates - Jenks Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
tm_shape(vac19d)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="jenks", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates - Jenks Breaks", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p1<-tm_shape(vac11sa)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p2<-tm_shape(vac11sa)+
tm_polygons(c("pvac_cv11"), title=c("CV Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Bexar County Vacant housing units Rate CV", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p1, p2)
p3<-tm_shape(vac11d)+
tm_polygons(c("pvac11"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p4<-tm_shape(vac11d)+
tm_polygons(c("pvac_cv11"), title=c("CV Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Dallas County Vacant housing units Rate CV", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p3, p4)
p5<-tm_shape(vac19sa)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant housing units Rate Estimates", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p6<-tm_shape(vac19sa)+
tm_polygons(c("pvac_cv19"), title=c("CV Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Bexar County Vacant housing units Rate CV", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p5, p6)
p7<-tm_shape(vac19d)+
tm_polygons(c("pvac19"), title=c("% Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant housing units Rate Estimates", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p8<-tm_shape(vac19d)+
tm_polygons(c("pvac_cv19"), title=c("CV Vacant housing units"), palette="Blues", style="quantile", n=5)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Dallas County Vacant housing units Rate CV", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p7, p8)
plot(vac11sa$pvac11, vac11sa$pvac_cv11)
plot(vac11d$pvac11, vac11d$pvac_cv11)
plot(vac19sa$pvac19, vac19sa$pvac_cv19)
plot(vac19d$pvac19, vac19d$pvac_cv19)
mdatsa<-tigris::geo_join(vac11sa, as.data.frame(vac19sa), by_sp="GEOID", by_df="GEOID")
## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
head(mdatsa)
## Simple feature collection with 6 features and 14 fields
## Active geometry column: geometry.x
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: -98.56778 ymin: 29.35415 xmax: -98.39488 ymax: 29.44661
## geographic CRS: NAD83
## GEOID NAME.x DP04_0003PE.x
## 1 48029170401 Census Tract 1704.01, Bexar County, Texas 17.3
## 2 48029170402 Census Tract 1704.02, Bexar County, Texas 16.0
## 3 48029160702 Census Tract 1607.02, Bexar County, Texas 11.1
## 4 48029160200 Census Tract 1602, Bexar County, Texas 8.3
## 5 48029141200 Census Tract 1412, Bexar County, Texas 10.8
## 6 48029141300 Census Tract 1413, Bexar County, Texas 15.5
## DP04_0003PM.x pvac11 pvac_er11 pvac_cv11
## 1 5.6 17.3 3.404255 19.67778
## 2 6.7 16.0 4.072948 25.45593
## 3 4.8 11.1 2.917933 26.28769
## 4 7.4 8.3 4.498480 54.19856
## 5 6.3 10.8 3.829787 35.46099
## 6 6.6 15.5 4.012158 25.88489
## NAME.y DP04_0003PE.y DP04_0003PM.y pvac19
## 1 Census Tract 1704.01, Bexar County, Texas 22.1 7.2 22.1
## 2 Census Tract 1704.02, Bexar County, Texas 10.3 4.5 10.3
## 3 Census Tract 1607.02, Bexar County, Texas 13.3 4.7 13.3
## 4 Census Tract 1602, Bexar County, Texas 4.9 3.1 4.9
## 5 Census Tract 1412, Bexar County, Texas 5.3 4.8 5.3
## 6 Census Tract 1413, Bexar County, Texas 11.5 4.9 11.5
## pvac_er19 pvac_cv19 rank geometry.x
## 1 4.376900 19.80498 1 POLYGON ((-98.5251 29.44358...
## 2 2.735562 26.55886 1 POLYGON ((-98.53594 29.4405...
## 3 2.857143 21.48228 1 POLYGON ((-98.55955 29.3849...
## 4 1.884498 38.45915 1 POLYGON ((-98.51153 29.3992...
## 5 2.917933 55.05534 1 POLYGON ((-98.44832 29.3826...
## 6 2.978723 25.90194 1 POLYGON ((-98.41921 29.3684...
## geometry.y
## 1 MULTIPOLYGON (((-98.54106 2...
## 2 MULTIPOLYGON (((-98.54196 2...
## 3 MULTIPOLYGON (((-98.56773 2...
## 4 MULTIPOLYGON (((-98.52883 2...
## 5 MULTIPOLYGON (((-98.44833 2...
## 6 MULTIPOLYGON (((-98.43312 2...
mdatd<-tigris::geo_join(vac11d, as.data.frame(vac19d), by_sp="GEOID", by_df="GEOID")
head(mdatd)
## Simple feature collection with 6 features and 14 fields
## Active geometry column: geometry.x
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: -96.80067 ymin: 32.83427 xmax: -96.57525 ymax: 32.94708
## geographic CRS: NAD83
## GEOID NAME.x DP04_0003PE.x
## 1 48113018120 Census Tract 181.20, Dallas County, Texas 10.2
## 2 48113012702 Census Tract 127.02, Dallas County, Texas 5.2
## 3 48113012800 Census Tract 128, Dallas County, Texas 2.9
## 4 48113012900 Census Tract 129, Dallas County, Texas 7.4
## 5 48113013004 Census Tract 130.04, Dallas County, Texas 5.7
## 6 48113019400 Census Tract 194, Dallas County, Texas 6.5
## DP04_0003PM.x pvac11 pvac_er11 pvac_cv11
## 1 6.4 10.2 3.890578 38.14292
## 2 5.7 5.2 3.465046 66.63549
## 3 3.0 2.9 1.823708 62.88649
## 4 4.9 7.4 2.978723 40.25302
## 5 4.6 5.7 2.796353 49.05882
## 6 4.8 6.5 2.917933 44.89128
## NAME.y DP04_0003PE.y DP04_0003PM.y pvac19
## 1 Census Tract 181.20, Dallas County, Texas 4.6 4.2 4.6
## 2 Census Tract 127.02, Dallas County, Texas 3.8 3.6 3.8
## 3 Census Tract 128, Dallas County, Texas 1.1 1.4 1.1
## 4 Census Tract 129, Dallas County, Texas 6.4 5.5 6.4
## 5 Census Tract 130.04, Dallas County, Texas 3.2 3.6 3.2
## 6 Census Tract 194, Dallas County, Texas 7.8 5.4 7.8
## pvac_er19 pvac_cv19 rank geometry.x
## 1 2.5531915 55.50416 1 POLYGON ((-96.57525 32.9365...
## 2 2.1884498 57.59079 1 POLYGON ((-96.68648 32.8400...
## 3 0.8510638 77.36944 1 POLYGON ((-96.68664 32.8402...
## 4 3.3434650 52.24164 1 POLYGON ((-96.71915 32.8612...
## 5 2.1884498 68.38906 1 POLYGON ((-96.73348 32.8677...
## 6 3.2826748 42.08557 1 POLYGON ((-96.78691 32.8507...
## geometry.y
## 1 MULTIPOLYGON (((-96.61445 3...
## 2 MULTIPOLYGON (((-96.68511 3...
## 3 MULTIPOLYGON (((-96.70107 3...
## 4 MULTIPOLYGON (((-96.7251 32...
## 5 MULTIPOLYGON (((-96.73332 3...
## 6 MULTIPOLYGON (((-96.80067 3...
acstest<-function(names,geoid, est1, err1, est2, err2, alpha, yr1, yr2, span){
se1<-err1/qnorm(.90)
se2<-err2/qnorm(.90)
yrs1<-seq(yr1, to=yr1-span)
yrs2<-seq(yr2, to=yr2-span)
C<-mean(yrs2%in%yrs1)
diff<- (est1-est2)
test<-(est1-est2) / (sqrt(1-C)*sqrt((se1^2+se2^2)))
crit<-qnorm(1-alpha/2)
pval<-2*pnorm(abs(test),lower.tail=F)
result<-NULL
result[pval > alpha]<-"insignificant change"
result[pval < alpha & test < 0]<- "significant increase"
result[pval < alpha & test > 0]<-"significant decrease"
data.frame(name=names,geoid=geoid, est1=est1, est2=est2, se1=se1, se2=se2,difference=diff, test=test, result=result, pval=pval)
}
diff1119sa<-acstest(names = mdatsa$NAME.x, geoid = mdatsa$GEOID, est1 = mdatsa$pvac11, est2 = mdatsa$pvac19, err1 = mdatsa$pvac_er11, err2=mdatsa$pvac_er19,alpha = .1, yr1 = 2011, yr2=2019, span = 5)
head(diff1119sa)
## name geoid est1 est2 se1
## 1 Census Tract 1704.01, Bexar County, Texas 48029170401 17.3 22.1 2.656355
## 2 Census Tract 1704.02, Bexar County, Texas 48029170402 16.0 10.3 3.178138
## 3 Census Tract 1607.02, Bexar County, Texas 48029160702 11.1 13.3 2.276875
## 4 Census Tract 1602, Bexar County, Texas 48029160200 8.3 4.9 3.510183
## 5 Census Tract 1412, Bexar County, Texas 48029141200 10.8 5.3 2.988399
## 6 Census Tract 1413, Bexar County, Texas 48029141300 15.5 11.5 3.130704
## se2 difference test result pval
## 1 3.415313 -4.8 -1.109383 insignificant change 0.2672649
## 2 2.134571 5.7 1.488857 insignificant change 0.1365250
## 3 2.229440 -2.2 -0.690386 insignificant change 0.4899515
## 4 1.470482 3.4 0.893386 insignificant change 0.3716505
## 5 2.276875 5.5 1.463953 insignificant change 0.1432069
## 6 2.324310 4.0 1.025853 insignificant change 0.3049610
table(diff1119sa$result)
##
## insignificant change significant decrease significant increase
## 251 65 24
diff1119d<-acstest(names = mdatd$NAME.x, geoid = mdatd$GEOID, est1 = mdatd$pvac11, est2 = mdatd$pvac19, err1 = mdatd$pvac_er11, err2=mdatd$pvac_er19,alpha = .1, yr1 = 2011, yr2=2019, span = 5)
head(diff1119d)
## name geoid est1 est2 se1
## 1 Census Tract 181.20, Dallas County, Texas 48113018120 10.2 4.6 3.035834
## 2 Census Tract 127.02, Dallas County, Texas 48113012702 5.2 3.8 2.703789
## 3 Census Tract 128, Dallas County, Texas 48113012800 2.9 1.1 1.423047
## 4 Census Tract 129, Dallas County, Texas 48113012900 7.4 6.4 2.324310
## 5 Census Tract 130.04, Dallas County, Texas 48113013004 5.7 3.2 2.182006
## 6 Census Tract 194, Dallas County, Texas 48113019400 6.5 7.8 2.276875
## se2 difference test result pval
## 1 1.9922659 5.6 1.5422018 insignificant change 0.1230246
## 2 1.7076565 1.4 0.4377872 insignificant change 0.6615405
## 3 0.6640886 1.8 1.1462233 insignificant change 0.2517028
## 4 2.6089196 1.0 0.2861950 insignificant change 0.7747287
## 5 1.7076565 2.5 0.9022720 insignificant change 0.3669124
## 6 2.5614847 -1.3 -0.3793238 insignificant change 0.7044474
table(diff1119d$result)
##
## insignificant change significant decrease significant increase
## 342 117 43
acs_mergesa<-left_join(mdatsa, diff1119sa, by=c("GEOID"="geoid"))
tmap_mode("plot")
## tmap mode set to plotting
p1sa<-tm_shape(acs_mergesa)+
tm_polygons(c("pvac11"), title=c("% Vacant Housing Units 2011"), palette="Blues", style="quantile", n=6)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Bexar County Vacant Housing Units Rate Estimates 2011", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p2sa<-tm_shape(acs_mergesa)+
tm_polygons(c("pvac19"), title=c("% Vacant Housing Units 2019"), palette="Blues", style="quantile", n=6)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Bexar County Vacant Housing Units Rate Estimate 2019", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
p3sa <- tm_shape(acs_mergesa)+
tm_polygons(c("result"), title=c("Changes"), palette = "Dark2")+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Bexar County Vacant Housing Units Rate Estimate Changes", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p1sa, p2sa, p3sa)
diff1119d<-acstest(names = mdatd$NAME.x, geoid = mdatd$GEOID, est1 = mdatd$pvac11, est2 = mdatd$pvac19, err1 = mdatd$pvac_er11, err2=mdatd$pvac_er19,alpha = .1, yr1 = 2011, yr2=2019, span = 5)
head(diff1119d)
## name geoid est1 est2 se1
## 1 Census Tract 181.20, Dallas County, Texas 48113018120 10.2 4.6 3.035834
## 2 Census Tract 127.02, Dallas County, Texas 48113012702 5.2 3.8 2.703789
## 3 Census Tract 128, Dallas County, Texas 48113012800 2.9 1.1 1.423047
## 4 Census Tract 129, Dallas County, Texas 48113012900 7.4 6.4 2.324310
## 5 Census Tract 130.04, Dallas County, Texas 48113013004 5.7 3.2 2.182006
## 6 Census Tract 194, Dallas County, Texas 48113019400 6.5 7.8 2.276875
## se2 difference test result pval
## 1 1.9922659 5.6 1.5422018 insignificant change 0.1230246
## 2 1.7076565 1.4 0.4377872 insignificant change 0.6615405
## 3 0.6640886 1.8 1.1462233 insignificant change 0.2517028
## 4 2.6089196 1.0 0.2861950 insignificant change 0.7747287
## 5 1.7076565 2.5 0.9022720 insignificant change 0.3669124
## 6 2.5614847 -1.3 -0.3793238 insignificant change 0.7044474
table(diff1119d$result)
##
## insignificant change significant decrease significant increase
## 342 117 43
acs_merged<-left_join(mdatd, diff1119d, by=c("GEOID"="geoid"))
tmap_mode("plot")
## tmap mode set to plotting
p1d<-tm_shape(acs_merged)+
tm_polygons(c("pvac11"), title=c("% Vacant Housing Units 2011"), palette="Blues", style="quantile", n=6)+
#tm_format("World", legend.outside=T, title.size =4)+
tm_scale_bar()+
tm_layout(title="Dallas County Vacant Housing Units Rate Estimates 2011", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_compass()
p2d<-tm_shape(acs_mergesa)+
tm_polygons(c("pvac19"), title=c("% Vacant Housing Units 2019"), palette="Blues", style="quantile", n=6)+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Dallas County Vacant Housing Units Rate Estimate 2019", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
p3d <- tm_shape(acs_mergesa)+
tm_polygons(c("result"), title=c("Changes"), palette = "Dark2")+
#tm_format("World", title="San Antonio Poverty Rate CV", legend.outside=T)+
tm_layout(title="Dallas County Vacant Housing Units Rate Estimate Changes", title.size =1.5, legend.frame = TRUE, title.position = c('right', 'top'))+
tm_scale_bar()+
tm_compass()
tmap_arrange(p1d, p2d, p3d)
