library(tidycensus)
library(tidyverse)
library(sf)
library(ggplot2)
library(dplyr)
library(leaflet)
library(flextable)
library(gtable)
library(gt)
library(stringr)

Set up Westend study area by block group

Westend_bg<-c("340390392004","340390393021","340390396002","340390390001","340390396003",
"340390394001", "340390395012", "340390395022","340390393011","340390393012",
"340390395021", "340390389003",  "340390394003", "340390392003", "340390395011", "340390393022",
"340390394002", "340390396001")

Westend_bg_v2<-c("340390394001","340390395012","340390395022","340390395021",
                 "340390394003","340390395011","340390394002")

Create block group maps

Block Group Maps

Section 5 Neighborhood Description and Statement of Need

Describe the neighborhood, including delineation of its boundaries, and list pertinent census tracts and block groups. Include one or more legible maps of the municipality and of the neighborhood that identify features in the neighborhood and surrounding area relevant to the neighborhood revitalization effort. One of these maps must be “plain,” showing the streets and street names within the proposed neighborhood. Indicate neighborhood boundaries, census tracts, and zoning designations on the maps. Please present maps at a reasonable scale (i.e.: 1”=200’ or 1”=100’). Organizations with Geographic Information System (GIS) capabilities are encouraged to submit their maps in both paper and electronic (digital) formats.

Map with Street Views

leaflet(Plainfield_BG) %>%
   addProviderTiles(providers$OpenStreetMap)%>%addPolygons(
    label = ~GEOID, 
    fillColor = "blue", 
    fillOpacity = 0.2,
    weight = 2, 
    color = "darkblue",
    opacity = 1
  )

Section 5 Neighborhood Description and Statement of Need

###Describe conditions to establish the need for neighborhood revitalization. Support this description with statistical information. American FactFinder, at the US Census Bureau, is recommended as a data source and can help determine census tracts and block groups; data from the most recent American Community Survey, 5-year estimate should be obtained. You may access American FactFinder at: http://factfinder.census.gov. At a minimum, the following statistics should be obtained for the involved census tracts and block groups (for partial tracts, interpolation of data will be accepted):

##PEOPLE # Pull population fields

*Total Population

## [1] 30186
## [1] 30186

Table Population by Census Tract

      gt(Census_Tract_Summary)
Tract sum(estimate, na.rm = TRUE)
Census Tract 396 4498
Census Tract 395.02 3653
Census Tract 395.01 3299
Census Tract 394 6039
Census Tract 393.02 3023
Census Tract 393.01 3248
Census Tract 392 3515
Census Tract 390 1917
Census Tract 389 994
 
 gt(Census_studyarea_Summary)
County sum(estimate, na.rm = TRUE)
Union County 30186

Population by Race

## Getting data from the 2019-2023 5-year ACS

Race Catergory by Tract Table

Note: race table do not equal total population as you can select more than on race

Summary for the West End Table

gt(Plainfield_race_summary)%>%
  fmt_percent(columns = Percent, decimals = 1)
Race_Catergory area_total Grand_total Percent
American_Indian_and_Alaska_Native_alone 132 33309 0.4%
Asian_alone 121 33309 0.4%
Black_or_African_American_alone 8020 33309 24.1%
Native_Hawaiian_and_Other_Pacific_Islander_alone 0 33309 0.0%
Some_other_race_alone 16944 33309 50.9%
Two_or_more_races_ 3123 33309 9.4%
Two_races_excluding_Some_other_race__and_three_or_more_races 320 33309 1.0%
Two_races_including_Some_other_race 2803 33309 8.4%
White_alone 1846 33309 5.5%

Hispanic

## Getting data from the 2019-2023 5-year ACS
## `summarise()` has grouped output by 'Tract'. You can override using the
## `.groups` argument.

Hispanc Table

gt(Plainfield_hispanic_summary)
Ethnicity area_total
Census Tract 389
Hispanic 948
Not_Hispanic 46
Census Tract 390
Hispanic 1742
Not_Hispanic 175
Census Tract 392
Hispanic 2307
Not_Hispanic 1208
Census Tract 393.01
Hispanic 2327
Not_Hispanic 921
Census Tract 393.02
Hispanic 2352
Not_Hispanic 671
Census Tract 394
Hispanic 4248
Not_Hispanic 1791
Census Tract 395.01
Hispanic 2069
Not_Hispanic 1230
Census Tract 395.02
Hispanic 2285
Not_Hispanic 1368
Census Tract 396
Hispanic 1631
Not_Hispanic 2867

Median Age

## Getting data from the 2019-2023 5-year ACS

Median Age by Tract

gt(Plainfield_medianage_summary)
Tract area_total
Census Tract 389 30.60
Census Tract 390 31.80
Census Tract 392 30.55
Census Tract 393.01 25.85
Census Tract 393.02 27.90
Census Tract 394 30.00
Census Tract 395.01 26.90
Census Tract 395.02 31.35
Census Tract 396 38.70

Sex Age

## Getting data from the 2019-2023 5-year ACS
## `summarise()` has grouped output by 'Tract', 'Age_Group', 'Sex',
## 'Age_category'. You can override using the `.groups` argument.

Dependency Table

Study age category

Dependency Table

gt(studyarea_dependency)
DependencyGroup Tracttotal
Elderly_dependency 2114
Female_Subtotal 14554
Male_Subtotal 15632
Working_age 19522
Youth_dependency 8550
 
gt(studyarea_age_LifeStage)
LifeStage total
Active_Retirement 6023
Children 9963
Female_Subtotal 14554
Male_Subtotal 15632
Retirement_age 2114
Transitioning 2730
family formation 9356

% of households headed by single womenHousehold Headed by Femal Households

# define variable

HouseholdType<-c(Total  = "B11001_001E",
                Family_households_ = "B11001_002E",
                Marriedcouple_family = "B11001_003E",
                Other_family_ = "B11001_004E",
                Male_householder__no_spouse_present = "B11001_005E",
                Female_householder__no_spouse_present = "B11001_006E",
                Nonfamily_households_ = "B11001_007E",
                Householder_living_alone = "B11001_008E",
                Householder_not_living_alone = "B11001_009E")
                
# Pull census data
                
Plainfield_householdtype<-get_acs(geography = "block group",
                              state = "NJ",
                              county = "Union county",
                              variables = HouseholdType,
                              geometry = FALSE,
                              survey = "acs5",
                              output = "wide",
                              year = 2023)
## Getting data from the 2019-2023 5-year ACS
# Remove Margin of Error & Total



Plainfield_householdtype<- Plainfield_householdtype %>% select (-Total)

# Pivot the variables

Plainfield_householdtype<-Plainfield_householdtype%>%
        pivot_longer(
        cols = -c(GEOID, NAME), names_to = "Type", values_to = "Count")
        
# Filter out the study area - West end Plainfield City
        
Plainfield_householdtype<-filter(Plainfield_householdtype, GEOID %in% Westend_bg)

# Seoerate the NAME Variable

Plainfield_householdtype <-Plainfield_householdtype %>%
    separate(NAME, into = c("Block Group","Tract","County", "State"), sep = ";")
    Plainfield_householdtype<- Plainfield_householdtype %>% select (-ends_with("M"))
# Create  table Block and tracts

Plainfield_householdtype_SA<-Plainfield_householdtype %>%
      group_by(County, Type)%>%
      mutate(grandtotal = sum(Count))%>%
      ungroup()
      
# Create Summary Table   
      

Plainfield_householdtype_SA <- Plainfield_householdtype %>%
  group_by( Type) %>%
  summarise(Total_per_Type = sum(Count)) %>%
  mutate(Percent = Total_per_Type / sum(Total_per_Type)) %>%
  ungroup()
gt(Plainfield_householdtype_SA)%>%
     fmt_percent(columns = Percent, decimals = 1)
Type Total_per_Type Percent
B11001_001M 2696 7.8%
B11001_002M 2304 6.6%
B11001_003M 1720 5.0%
B11001_004M 1728 5.0%
B11001_005M 1044 3.0%
B11001_006M 1386 4.0%
B11001_007M 1668 4.8%
B11001_008M 1338 3.9%
B11001_009M 776 2.2%
Family_households_ 6342 18.3%
Female_householder__no_spouse_present 2153 6.2%
Householder_living_alone 1538 4.4%
Householder_not_living_alone 498 1.4%
Male_householder__no_spouse_present 1123 3.2%
Marriedcouple_family 3066 8.8%
Nonfamily_households_ 2036 5.9%
Other_family_ 3276 9.4%

###Income: median income; % of population with income below poverty level; unemployment rate

# Define variables for Ratio of Income to Poverty Level
poverty_vars <- c(
  total = "C17002_001",
  under_50_Deep_poverty = "C17002_002",
  under_100_below_poverty_line = "C17002_003",
  up_to_124_near_poverty = "C17002_004")
  
# Pull data on poverty

Plainfield_poverty <-get_acs(geography = "block group",
                              state = "NJ",
                              county = "Union county",
                              variables = poverty_vars,
                              geometry = FALSE,
                              survey = "acs5",
                              output = "wide",
                              year = 2023)
## Getting data from the 2019-2023 5-year ACS
Plainfield_poverty<- Plainfield_poverty %>% select (-ends_with("M"))

Plainfield_poverty<-Plainfield_poverty%>%
        pivot_longer(
        cols = -c(GEOID, NAME), names_to = "Type", values_to = "Count")

Plainfield_poverty<-filter(Plainfield_poverty, GEOID %in% Westend_bg)
gt(Plainfield_poverty)
GEOID NAME Type Count
340390389003 Block Group 3; Census Tract 389; Union County; New Jersey totalE 994
340390389003 Block Group 3; Census Tract 389; Union County; New Jersey under_50_Deep_povertyE 29
340390389003 Block Group 3; Census Tract 389; Union County; New Jersey under_100_below_poverty_lineE 22
340390389003 Block Group 3; Census Tract 389; Union County; New Jersey up_to_124_near_povertyE 107
340390390001 Block Group 1; Census Tract 390; Union County; New Jersey totalE 1857
340390390001 Block Group 1; Census Tract 390; Union County; New Jersey under_50_Deep_povertyE 153
340390390001 Block Group 1; Census Tract 390; Union County; New Jersey under_100_below_poverty_lineE 26
340390390001 Block Group 1; Census Tract 390; Union County; New Jersey up_to_124_near_povertyE 154
340390392003 Block Group 3; Census Tract 392; Union County; New Jersey totalE 1607
340390392003 Block Group 3; Census Tract 392; Union County; New Jersey under_50_Deep_povertyE 3
340390392003 Block Group 3; Census Tract 392; Union County; New Jersey under_100_below_poverty_lineE 139
340390392003 Block Group 3; Census Tract 392; Union County; New Jersey up_to_124_near_povertyE 215
340390392004 Block Group 4; Census Tract 392; Union County; New Jersey totalE 1908
340390392004 Block Group 4; Census Tract 392; Union County; New Jersey under_50_Deep_povertyE 103
340390392004 Block Group 4; Census Tract 392; Union County; New Jersey under_100_below_poverty_lineE 654
340390392004 Block Group 4; Census Tract 392; Union County; New Jersey up_to_124_near_povertyE 85
340390393011 Block Group 1; Census Tract 393.01; Union County; New Jersey totalE 1700
340390393011 Block Group 1; Census Tract 393.01; Union County; New Jersey under_50_Deep_povertyE 160
340390393011 Block Group 1; Census Tract 393.01; Union County; New Jersey under_100_below_poverty_lineE 514
340390393011 Block Group 1; Census Tract 393.01; Union County; New Jersey up_to_124_near_povertyE 89
340390393012 Block Group 2; Census Tract 393.01; Union County; New Jersey totalE 1457
340390393012 Block Group 2; Census Tract 393.01; Union County; New Jersey under_50_Deep_povertyE 199
340390393012 Block Group 2; Census Tract 393.01; Union County; New Jersey under_100_below_poverty_lineE 470
340390393012 Block Group 2; Census Tract 393.01; Union County; New Jersey up_to_124_near_povertyE 40
340390393021 Block Group 1; Census Tract 393.02; Union County; New Jersey totalE 1494
340390393021 Block Group 1; Census Tract 393.02; Union County; New Jersey under_50_Deep_povertyE 124
340390393021 Block Group 1; Census Tract 393.02; Union County; New Jersey under_100_below_poverty_lineE 389
340390393021 Block Group 1; Census Tract 393.02; Union County; New Jersey up_to_124_near_povertyE 335
340390393022 Block Group 2; Census Tract 393.02; Union County; New Jersey totalE 1475
340390393022 Block Group 2; Census Tract 393.02; Union County; New Jersey under_50_Deep_povertyE 100
340390393022 Block Group 2; Census Tract 393.02; Union County; New Jersey under_100_below_poverty_lineE 360
340390393022 Block Group 2; Census Tract 393.02; Union County; New Jersey up_to_124_near_povertyE 74
340390394001 Block Group 1; Census Tract 394; Union County; New Jersey totalE 2711
340390394001 Block Group 1; Census Tract 394; Union County; New Jersey under_50_Deep_povertyE 520
340390394001 Block Group 1; Census Tract 394; Union County; New Jersey under_100_below_poverty_lineE 214
340390394001 Block Group 1; Census Tract 394; Union County; New Jersey up_to_124_near_povertyE 156
340390394002 Block Group 2; Census Tract 394; Union County; New Jersey totalE 1687
340390394002 Block Group 2; Census Tract 394; Union County; New Jersey under_50_Deep_povertyE 45
340390394002 Block Group 2; Census Tract 394; Union County; New Jersey under_100_below_poverty_lineE 0
340390394002 Block Group 2; Census Tract 394; Union County; New Jersey up_to_124_near_povertyE 0
340390394003 Block Group 3; Census Tract 394; Union County; New Jersey totalE 1603
340390394003 Block Group 3; Census Tract 394; Union County; New Jersey under_50_Deep_povertyE 125
340390394003 Block Group 3; Census Tract 394; Union County; New Jersey under_100_below_poverty_lineE 144
340390394003 Block Group 3; Census Tract 394; Union County; New Jersey up_to_124_near_povertyE 210
340390395011 Block Group 1; Census Tract 395.01; Union County; New Jersey totalE 1973
340390395011 Block Group 1; Census Tract 395.01; Union County; New Jersey under_50_Deep_povertyE 137
340390395011 Block Group 1; Census Tract 395.01; Union County; New Jersey under_100_below_poverty_lineE 108
340390395011 Block Group 1; Census Tract 395.01; Union County; New Jersey up_to_124_near_povertyE 91
340390395012 Block Group 2; Census Tract 395.01; Union County; New Jersey totalE 1260
340390395012 Block Group 2; Census Tract 395.01; Union County; New Jersey under_50_Deep_povertyE 45
340390395012 Block Group 2; Census Tract 395.01; Union County; New Jersey under_100_below_poverty_lineE 133
340390395012 Block Group 2; Census Tract 395.01; Union County; New Jersey up_to_124_near_povertyE 51
340390395021 Block Group 1; Census Tract 395.02; Union County; New Jersey totalE 2083
340390395021 Block Group 1; Census Tract 395.02; Union County; New Jersey under_50_Deep_povertyE 45
340390395021 Block Group 1; Census Tract 395.02; Union County; New Jersey under_100_below_poverty_lineE 483
340390395021 Block Group 1; Census Tract 395.02; Union County; New Jersey up_to_124_near_povertyE 50
340390395022 Block Group 2; Census Tract 395.02; Union County; New Jersey totalE 1499
340390395022 Block Group 2; Census Tract 395.02; Union County; New Jersey under_50_Deep_povertyE 41
340390395022 Block Group 2; Census Tract 395.02; Union County; New Jersey under_100_below_poverty_lineE 26
340390395022 Block Group 2; Census Tract 395.02; Union County; New Jersey up_to_124_near_povertyE 36
340390396001 Block Group 1; Census Tract 396; Union County; New Jersey totalE 1503
340390396001 Block Group 1; Census Tract 396; Union County; New Jersey under_50_Deep_povertyE 33
340390396001 Block Group 1; Census Tract 396; Union County; New Jersey under_100_below_poverty_lineE 148
340390396001 Block Group 1; Census Tract 396; Union County; New Jersey up_to_124_near_povertyE 40
340390396002 Block Group 2; Census Tract 396; Union County; New Jersey totalE 1035
340390396002 Block Group 2; Census Tract 396; Union County; New Jersey under_50_Deep_povertyE 18
340390396002 Block Group 2; Census Tract 396; Union County; New Jersey under_100_below_poverty_lineE 114
340390396002 Block Group 2; Census Tract 396; Union County; New Jersey up_to_124_near_povertyE 0
340390396003 Block Group 3; Census Tract 396; Union County; New Jersey totalE 1917
340390396003 Block Group 3; Census Tract 396; Union County; New Jersey under_50_Deep_povertyE 357
340390396003 Block Group 3; Census Tract 396; Union County; New Jersey under_100_below_poverty_lineE 303
340390396003 Block Group 3; Census Tract 396; Union County; New Jersey up_to_124_near_povertyE 199
 
##### Househood Income Past 12 months

Plainfield_householdIncome<-c(Total  = "B19001_001E",
A_Less_than__10_000 = "B19001_002E",
B_10_000_to__14_999 = "B19001_003E",
C_15_000_to__19_999 = "B19001_004E",
D_20_000_to__24_999 = "B19001_005E",
E_25_000_to__29_999 = "B19001_006E",
F_30_000_to__34_999 = "B19001_007E",
G_35_000_to__39_999 = "B19001_008E",
H_40_000_to__44_999 = "B19001_009E",
I_45_000_to__49_999 = "B19001_010E",
J_50_000_to__59_999 = "B19001_011E",
K_60_000_to__74_999 = "B19001_012E",
L_75_000_to__99_999 = "B19001_013E",
M_100_000_to__124_999 = "B19001_014E",
N_125_000_to__149_999 = "B19001_015E",
O_150_000_to__199_999 = "B19001_016E",
P_200_000_or_more = "B19001_017E")

Plainfield_houseincome<-  get_acs(geography = "block group",
                              state = "NJ",
                              county = "Union county",
                              variables = Plainfield_householdIncome,
                              geometry = FALSE,
                              survey = "acs5",
                              output = "wide",
                              year = 2023)
## Getting data from the 2019-2023 5-year ACS
Plainfield_houseincome<- Plainfield_houseincome %>% select (-ends_with("M")) 

Plainfield_houseincome<-Plainfield_houseincome %>% select(-Total)
                              
Plainfield_houseincome<-Plainfield_houseincome%>%
        pivot_longer(
        cols = -c(GEOID, NAME), names_to = "Income_Group", values_to = "Count")
        

Plainfield_houseincome<-filter(Plainfield_houseincome, GEOID %in% Westend_bg)


Plainfield_houseincome<-Plainfield_houseincome %>%
        separate(NAME, into = c("Block Group","Tract","County", "State"), sep = ";")
        

        

Plainfield_houseincome_SA<-Plainfield_houseincome%>%
        group_by(County,Income_Group)%>%
        summarise(Population = sum(Count)) %>%
        mutate( Total = sum(Population))%>%
        mutate(Percent = Population/Total)
## `summarise()` has grouped output by 'County'. You can override using the
## `.groups` argument.
 Plainfield_houseincome_SA<- Plainfield_houseincome_SA %>%
        select(-Total)

Table Household Income Study Area

Plainfield_houseincome_SA %>% gt() %>%
     fmt_percent(columns = Percent, decimals = 1)
Income_Group Population Percent
Union County
A_Less_than__10_000 342 4.1%
B_10_000_to__14_999 98 1.2%
C_15_000_to__19_999 361 4.3%
D_20_000_to__24_999 281 3.4%
E_25_000_to__29_999 304 3.6%
F_30_000_to__34_999 284 3.4%
G_35_000_to__39_999 252 3.0%
H_40_000_to__44_999 361 4.3%
I_45_000_to__49_999 706 8.4%
J_50_000_to__59_999 1020 12.2%
K_60_000_to__74_999 691 8.2%
L_75_000_to__99_999 1337 16.0%
M_100_000_to__124_999 665 7.9%
N_125_000_to__149_999 576 6.9%
O_150_000_to__199_999 628 7.5%
P_200_000_or_more 472 5.6%

EDUCATION

## Getting data from the 2019-2023 5-year ACS
## Warning: There was 1 warning in `summarise()`.
## ℹ In argument: `across(where(is.numeric), sum, na.rm = TRUE)`.
## ℹ In group 1: `Tract = " Census Tract 389"`.
## Caused by warning:
## ! The `...` argument of `across()` is deprecated as of dplyr 1.1.0.
## Supply arguments directly to `.fns` through an anonymous function instead.
## 
##   # Previously
##   across(a:b, mean, na.rm = TRUE)
## 
##   # Now
##   across(a:b, \(x) mean(x, na.rm = TRUE))
Metric Census Tract 389 Census Tract 390 Census Tract 392 Census Tract 393.01 Census Tract 393.02 Census Tract 394 Census Tract 395.01 Census Tract 395.02 Census Tract 396
grade_12_no_diplomaE 1.0000000 0.000000 20.000000 67.000000 52.000000 90.000000 49.0000000 0.000000 48.0000000
hs_diplomaE 63.0000000 284.000000 750.000000 442.000000 365.000000 1062.000000 505.0000000 595.000000 658.0000000
GEDE 12.0000000 0.000000 29.000000 83.000000 20.000000 31.000000 61.0000000 86.000000 181.0000000
some_college_lt1yrE 36.0000000 14.000000 63.000000 22.000000 239.000000 178.000000 103.0000000 93.000000 123.0000000
some_college_1plusE 13.0000000 148.000000 110.000000 88.000000 112.000000 314.000000 166.0000000 141.000000 401.0000000
associatesE 5.0000000 43.000000 70.000000 72.000000 7.000000 126.000000 150.0000000 145.000000 122.0000000
bachelorsE 81.0000000 172.000000 155.000000 43.000000 64.000000 265.000000 234.0000000 247.000000 599.0000000
mastersE 0.0000000 0.000000 101.000000 31.000000 0.000000 84.000000 44.0000000 37.000000 254.0000000
professional_degreeE 0.0000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.0000000 24.000000 9.0000000
doctoriateE 0.0000000 0.000000 0.000000 0.000000 24.000000 0.000000 17.0000000 0.000000 21.0000000
Tract_total 211.0000000 661.000000 1298.000000 848.000000 883.000000 2150.000000 1332.0000000 1368.000000 2416.0000000
grade_12_no_diplomaE_pct 0.4739336 0.000000 1.540832 7.900943 5.889015 4.186047 3.6786787 0.000000 1.9867550
hs_diplomaE_pct 29.8578199 42.965204 57.781202 52.122642 41.336353 49.395349 37.9129129 43.494152 27.2350993
GEDE_pct 5.6872038 0.000000 2.234206 9.787736 2.265006 1.441860 4.5795796 6.286550 7.4917219
some_college_lt1yrE_pct 17.0616114 2.118003 4.853621 2.594340 27.066818 8.279070 7.7327327 6.798246 5.0910596
some_college_1plusE_pct 6.1611374 22.390318 8.474576 10.377358 12.684032 14.604651 12.4624625 10.307018 16.5976821
associatesE_pct 2.3696682 6.505295 5.392912 8.490566 0.792752 5.860465 11.2612613 10.599415 5.0496689
bachelorsE_pct 38.3886256 26.021180 11.941448 5.070755 7.248018 12.325581 17.5675676 18.055556 24.7930464
mastersE_pct 0.0000000 0.000000 7.781202 3.655660 0.000000 3.906977 3.3033033 2.704678 10.5132450
professional_degreeE_pct 0.0000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.2252252 1.754386 0.3725166
doctoriateE_pct 0.0000000 0.000000 0.000000 0.000000 2.718007 0.000000 1.2762763 0.000000 0.8692053

Housing

## Getting data from the 2019-2023 5-year ACS
Tract Total_sum Owner_sum Rental_sum rental_per owner_per
Census Tract 389 240 30 210 87.50000 12.500000
Census Tract 390 538 18 520 96.65428 3.345725
Census Tract 392 1011 195 816 80.71217 19.287834
Census Tract 393.01 889 95 794 89.31384 10.686164
Census Tract 393.02 951 0 951 100.00000 0.000000
Census Tract 394 1622 482 1140 70.28360 29.716400
Census Tract 395.01 874 442 432 49.42792 50.572082
Census Tract 395.02 901 448 453 50.27747 49.722531
Census Tract 396 1352 744 608 44.97041 55.029586

### Housing Occupancy Status

## Getting data from the 2019-2023 5-year ACS
Tract Total_sum Occupied_sum Vacant_sum Occupied_per Vacant_per
Census Tract 389 258 240 18 93.02326 6.976744
Census Tract 390 585 538 47 91.96581 8.034188
Census Tract 392 1157 1011 146 87.38116 12.618842
Census Tract 393.01 912 889 23 97.47807 2.521930
Census Tract 393.02 978 951 27 97.23926 2.760736
Census Tract 394 1697 1622 75 95.58044 4.419564
Census Tract 395.01 892 874 18 97.98206 2.017937
Census Tract 395.02 901 901 0 100.00000 0.000000
Census Tract 396 1462 1352 110 92.47606 7.523940

Median Home Value

## Getting data from the 2019-2023 5-year ACS
Tract value_medianE
Census Tract 389 428600
Census Tract 390 NA
Census Tract 392 338000
Census Tract 393.01 418800
Census Tract 393.02 NA
Census Tract 394 373900
Census Tract 395.01 403500
Census Tract 395.02 369350
Census Tract 396 369600

Median Gross Rent

## Getting data from the 2019-2023 5-year ACS
Tract value_medianE
Census Tract 389 1708.0
Census Tract 390 1835.0
Census Tract 392 1457.0
Census Tract 393.01 1537.5
Census Tract 393.02 1447.0
Census Tract 394 1628.0
Census Tract 395.01 1724.5
Census Tract 395.02 1900.5
Census Tract 396 1696.5

###Gross rent as % of household income (renter cost burden

## Getting data from the 2019-2023 5-year ACS
Renter Cost Burden by Block Group
Plainfield NRTC Study Area — ACS 2019–2023
tract Renter HH Burdened (30%+) Severe (50%+) % Burdened % Severe
Census Tract 389 210 110 19 52.4 9.0
Census Tract 390 520 318 121 61.2 23.3
Census Tract 392 816 543 198 66.5 24.3
Census Tract 393.01 794 394 289 49.6 36.4
Census Tract 393.02 951 722 317 75.9 33.3
Census Tract 394 1,140 520 233 45.6 20.4
Census Tract 395.01 432 208 98 48.1 22.7
Census Tract 395.02 453 266 128 58.7 28.3
Census Tract 396 608 433 216 71.2 35.5
Source: U.S. Census Bureau ACS 5-Year Table B25070

###Owner costs as % of income (owner cost burden)

## Getting data from the 2019-2023 5-year ACS
Owner Cost as Percentage of Household Income (Mortgaged Units)
Plainfield NRTC Study Area — ACS 2019–2023
Category Census Tract 389 Census Tract 390 Census Tract 392 Census Tract 393.01 Census Tract 393.02 Census Tract 394 Census Tract 395.01 Census Tract 395.02 Census Tract 396
Less_than_ten 21 0 25 0 0 9 2 7 9
Ten_to_fifteen 0 0 25 0 0 19 9 74 55
Fifteen_to_twenty 0 0 0 0 0 29 29 58 177
Twenty_to_Twentyfive 0 0 0 0 0 63 74 15 137
Twentyfive_to_thirty 0 0 55 7 0 60 52 59 67
Thirty_to_thirtyfive 0 0 5 0 0 0 37 5 21
Thirtyfive_to_forty 0 0 10 0 0 0 26 23 39
Forty_to_Fifty 3 0 10 33 0 59 38 23 22
Fiftyplus 0 0 9 0 0 87 93 71 98
Not_computed 0 0 0 0 0 0 0 0 0
Source: U.S. Census Bureau, ACS 5-Year Estimates, Table B25091
Owner Cost as Percentage of Household Income (No Mortgaged Units)
Plainfield NRTC Study Area — ACS 2019–2023
Category Census Tract 389 Census Tract 390 Census Tract 392 Census Tract 393.01 Census Tract 393.02 Census Tract 394 Census Tract 395.01 Census Tract 395.02 Census Tract 396
Less_than_ten 21 0 25 0 0 9 2 7 9
Ten_to_fifteen 0 0 25 0 0 19 9 74 55
Fifteen_to_twenty 0 0 0 0 0 29 29 58 177
Twenty_to_Twentyfive 0 0 0 0 0 63 74 15 137
Twentyfive_to_thirty 0 0 55 7 0 60 52 59 67
Thirty_to_thirtyfive 0 0 5 0 0 0 37 5 21
Thirtyfive_to_forty 0 0 10 0 0 0 26 23 39
Forty_to_Fifty 3 0 10 33 0 59 38 23 22
Fiftyplus 0 0 9 0 0 87 93 71 98
Not_computed 0 0 0 0 0 0 0 0 0
Source: U.S. Census Bureau, ACS 5-Year Estimates, Table B25091

###Year structure built (age of stock; lead-paint/rehab flags) (Measures of condition & suitiability)

## Getting data from the 2019-2023 5-year ACS
Year Structure Built by Census Tract
Plainfield NRTC / West End Study Area — ACS 5-Year Estimates, Table B25034
Year Built Census Tract 389 Census Tract 390 Census Tract 392 Census Tract 393.01 Census Tract 393.02 Census Tract 394 Census Tract 395.01 Census Tract 395.02 Census Tract 396
2020 or later 0 0 0 0 0 69 0 0 0
2010–2019 68 0 0 19 186 0 13 4 0
2000–2009 0 106 49 40 23 0 28 88 13
1990–1999 0 0 38 119 237 114 12 0 14
1980–1989 5 41 64 0 21 23 113 75 129
1970–1979 74 129 40 66 56 104 10 215 225
1960–1969 53 0 40 65 8 183 7 104 216
1950–1959 1 26 53 181 143 299 142 84 329
1940–1949 3 81 141 148 140 197 74 21 124
1939 or earlier 54 202 732 274 164 708 493 310 412
Total units 258 585 1,157 912 978 1,697 892 901 1,462
Study Area Total 516 1,170 2,314 1,824 1,956 3,394 1,784 1,802 2,924
Source: U.S. Census Bureau, ACS 5-Year Estimates, Table B25034

###Occupants per room (overcrowding)

## Getting data from the 2019-2023 5-year ACS
Owner-Occupied Overcrowding by Census Tract
Plainfield NRTC / West End Study Area — ACS 5-Year Estimates, Table B25014
Occupants per Room Census Tract 389 Census Tract 390 Census Tract 392 Census Tract 393.01 Census Tract 393.02 Census Tract 394 Census Tract 395.01 Census Tract 395.02 Census Tract 396
0.50 or less per room 30 0 178 62 0 267 260 191 628
0.51 to 1.00 0 18 17 9 0 178 145 198 116
1.01 to 1.50 (overcrowded) 0 0 0 24 0 37 21 59 0
1.51 to 2.00 0 0 0 0 0 0 16 0 0
2.01 or more (severe) 0 0 0 0 0 0 0 0 0
Owner-occupied (total) 30 18 195 95 0 482 442 448 744
Source: U.S. Census Bureau, ACS 5-Year Estimates, Table B25014