Visualizing The Intervention

Introduction

NOTE: Values below are duplicates from Middle Atlantic Division and serve solely as an example

The New Markets Tax Credit (NMTC) program was created in 2000 and authorized by Congress under the Community Renewal and Tax Relief Act of 2000 (CDFI Fund, 2022). The program distributes tax credit dollars to Community Development Entities who award Qualified Low-Income Community Investments (QLICIs), such as business loans, to investors in Low-Income Communities. The ongoing goal of the NMTC program is to improve low income communities by encouraging developers to build new projects that can create jobs and provide additional services within financially risky communities (Novogradac, 2023). There are numerous eligibility criteria to qualify census tracts recipients.

The Low Income Housing Tax Credit (LIHTC) program is a much older program that was started in 1986 and authorized by Congress under the Tax Reform Act of 1986. Most recently, the Inflation Reduction Act of 2022 increased credits/bonuses (Urban Institute, 2018; Congressional Research Service, 2023). In addition, in contrast to CDE/QLICI model of the NMTC program, LIHTC dollars go directly to investors, but the funds are limited to affordable housing developments for economically disadvantaged individuals. The Urban Institute (2018) describes the program as “an incentive to make equity investments in affordable rental housing. The equity raised is used to construct new properties, acquire and renovate existing buildings, and refinance and renovate existing affordable rental housing properties that have previously been financed through other federal housing programs” (Urban Institute, 2018).

In the following analysis we explore correlations between these programs and the amount of funding they provide to our identified areas of vulnerability within the West South Central Division. Specifically we discovered that there is a strong positive correlation between NMTC dollars and SVI Flag Counts in 2010 for the majority of counties/census tracts in [STATES]. While not quite as strong, we still found a moderate correlation between LIHTC dollars and SVI Flag Counts in 2010.

Library

# Turn off scientific notation
options(scipen=999)

# Load packages
library(here)        # relative file paths for reproducibility
library(tidyverse)   # data wrangling
library(stringi)     # string data wrangling
library(tigris)      # US census TIGER/Line shapefiles
library(ggplot2)     # data visualization
library(cowplot)     # data visualization plotting
library(gridExtra)   # grid for data visualizations
library(biscale)     # bivariate mapping
library(kableExtra)  # table formatting
library(scales)      # palette and number formatting
library(cluster)     # clustering algorithms
library(factoextra)  # clustering algorithms & visualization

Functions

import::here( "fips_census_regions",
              "load_svi_data",
              "merge_svi_data",
              "census_division",
              "flag_summarize",
              "summarize_county_nmtc",
              "summarize_county_lihtc",
              "elbow_plot",
             # notice the use of here::here() that points to the .R file
             # where all these R objects are created
             .from = here::here("analysis/project_data_steps_nala.R"),
             .character_only = TRUE)

SVI Data

# Load SVI data sets
svi_2010 <- readRDS(here::here("data/raw/Census_Data_SVI/svi_2010_trt10.rds"))
svi_2020 <- readRDS(here::here("data/raw/Census_Data_SVI/svi_2020_trt10.rds"))

# Load mapping data sets
svi_county_map2010 <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_county_svi_flags10.rds")))

svi_county_map2020 <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_county_svi_flags20.rds")))

divisional_st_sf <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_st_sf.rds")))

NMTC & LIHTC Data

# Load NMTC & LIHTC Tract Eligibility Data

orig_nmtc <- readxl::read_excel(here::here("data/raw/NMTC_LIHTC_tracts/nmtc_2011-2015_lic_110217.xlsx"), sheet="NMTC LICs 2011-2015 ACS")

high_migration_nmtc <- readxl::read_excel(here::here("data/raw/NMTC_LIHTC_tracts/nmtc_2011-2015_lic_110217.xlsx"), sheet="High migration tracts", skip=1)

nmtc_awards_data <- readxl::read_excel(here::here("data/raw/NMTC_LIHTC_tracts/NMTC_Public_Data_Release_includes_FY_2021_Data_final.xlsx"), sheet = "Projects 2 - Data Set PUBLISH.P")

lihtc_eligible <- readxl::read_excel(here::here("data/raw/NMTC_LIHTC_tracts/qct_data_2010_2011_2012.xlsx"))

lihtc_projects <- read.csv(here::here("data/raw/NMTC_LIHTC_tracts/lihtcpub/LIHTCPUB.csv"))

Load 2010 SVI Data

# National 2010 Data
svi_2010_national <- load_svi_data(svi_2010, percentile=.75)
svi_2010_national %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1	RPL_THEME1	F_THEME1	SPL_THEME2	RPL_THEME2	F_THEME2	SPL_THEME3	RPL_THEME3	F_THEME3	SPL_THEME4	RPL_THEME4	F_THEME4	SPL_THEMES	RPL_THEMES	F_TOTAL
01001020100	01	001	020100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1809	771	696	297	1809	16.41791	0.3871	0	36	889	4.049494	0.1790	0	127	598	21.23746	0.20770	0	47	98	47.95918	0.5767	0	174	696	25.00000	0.18790	0	196	1242	15.780998	0.6093	0	186	1759	10.574190	0.3790	0	222	12.271973	0.4876	0	445	24.59923	0.5473	0	298	1335	22.32210	0.8454	1	27	545	4.954128	0.09275	0	36	1705	2.1114370	0.59040	0	385	1809	21.282477	0.4524	0	771	0	0.0000000	0.1224	0	92	11.9325551	0.8005	1	0	696	0.0000000	0.1238	0	50	696	7.183908	0.6134	0	0	1809	0	0.364	0	1.74230	0.28200	0	2.56345	0.5296	1	0.4524	0.4482	0	2.0241	0.2519	1	6.78225	0.3278	2
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.5754	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.3019	0	154	730	21.09589	0.09312	0	339	1265	26.798419	0.8392	1	313	2012	15.556660	0.6000	0	204	10.099010	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.83510	1	15	1890	0.7936508	0.40130	0	1243	2020	61.534653	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.7808219	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0	0.364	0	2.70312	0.56650	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6
01001020300	01	001	020300	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3543	1403	1287	656	3533	18.56779	0.4443	0	93	1552	5.992268	0.3724	0	273	957	28.52665	0.45780	0	178	330	53.93939	0.7152	0	451	1287	35.04274	0.49930	0	346	2260	15.309734	0.5950	0	252	3102	8.123791	0.2596	0	487	13.745413	0.5868	0	998	28.16822	0.7606	1	371	2224	16.68165	0.6266	0	126	913	13.800657	0.46350	0	0	3365	0.0000000	0.09298	0	637	3543	17.979114	0.4049	0	1403	10	0.7127584	0.3015	0	2	0.1425517	0.4407	0	0	1287	0.0000000	0.1238	0	101	1287	7.847708	0.6443	0	0	3543	0	0.364	0	2.17060	0.41010	0	2.53048	0.5116	1	0.4049	0.4011	0	1.8743	0.1942	0	6.98028	0.3576	1
01001020400	01	001	020400	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	4840	1957	1839	501	4840	10.35124	0.2177	0	101	2129	4.744011	0.2447	0	310	1549	20.01291	0.17080	0	89	290	30.68966	0.2044	0	399	1839	21.69657	0.10540	0	274	3280	8.353658	0.3205	0	399	4293	9.294200	0.3171	0	955	19.731405	0.8643	1	1195	24.69008	0.5530	0	625	3328	18.78005	0.7233	0	152	1374	11.062591	0.34710	0	10	4537	0.2204100	0.22560	0	297	4840	6.136364	0.1647	0	1957	33	1.6862545	0.3843	0	25	1.2774655	0.5516	0	14	1839	0.7612833	0.3564	0	19	1839	1.033170	0.1127	0	0	4840	0	0.364	0	1.20540	0.13470	0	2.71330	0.6129	1	0.1647	0.1632	0	1.7690	0.1591	0	5.85240	0.1954	1
01001020500	01	001	020500	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	9938	3969	3741	1096	9938	11.02838	0.2364	0	188	4937	3.807981	0.1577	0	426	2406	17.70574	0.11050	0	528	1335	39.55056	0.3753	0	954	3741	25.50120	0.20140	0	293	5983	4.897209	0.1655	0	740	10110	7.319486	0.2211	0	837	8.422218	0.2408	0	3012	30.30791	0.8455	1	759	7155	10.60797	0.2668	0	476	2529	18.821669	0.63540	0	78	9297	0.8389803	0.41110	0	1970	9938	19.822902	0.4330	0	3969	306	7.7097506	0.6153	0	0	0.0000000	0.2198	0	7	3741	0.1871157	0.2535	0	223	3741	5.960973	0.5483	0	0	9938	0	0.364	0	0.98210	0.08468	0	2.39960	0.4381	1	0.4330	0.4290	0	2.0009	0.2430	0	5.81560	0.1905	1
01001020600	01	001	020600	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3402	1456	1308	735	3402	21.60494	0.5199	0	134	1720	7.790698	0.5436	0	242	1032	23.44961	0.28010	0	62	276	22.46377	0.1035	0	304	1308	23.24159	0.14070	0	301	2151	13.993491	0.5510	0	355	3445	10.304790	0.3656	0	386	11.346267	0.4232	0	931	27.36626	0.7200	0	440	2439	18.04018	0.6912	0	143	924	15.476190	0.52900	0	4	3254	0.1229256	0.19840	0	723	3402	21.252205	0.4519	0	1456	18	1.2362637	0.3507	0	433	29.7390110	0.9468	1	16	1308	1.2232416	0.4493	0	28	1308	2.140673	0.2298	0	0	3402	0	0.364	0	2.12080	0.39510	0	2.56180	0.5288	0	0.4519	0.4477	0	2.3406	0.4048	1	7.47510	0.4314	1

# Divisional 2010 Data
svi_2010_divisional <- load_svi_data(svi_2010, rank_by = "divisional", location = census_division, percentile=.75)
svi_2010_divisional %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

• DATA TABLE

Load 2020 Data

# National 2020 Data
svi_2020_national <- load_svi_data(svi_2020, percentile=.75)
svi_2020_national %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1	RPL_THEME1	F_THEME1	SPL_THEME2	RPL_THEME2	F_THEME2	SPL_THEME3	RPL_THEME3	F_THEME3	SPL_THEME4	RPL_THEME4	F_THEME4	SPL_THEMES	RPL_THEMES	F_TOTAL
01001020100	01	001	020100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1941	710	693	352	1941	18.13498	0.4630	0	18	852	2.112676	0.15070	0	81	507	15.976331	0.26320	0	63	186	33.87097	0.2913	0	144	693	20.77922	0.2230	0	187	1309	14.285714	0.6928	0	187	1941	9.634209	0.6617	0	295	15.19835	0.4601	0	415	21.38073	0.4681	0	391	1526	25.62254	0.9011	1	58	555	10.45045	0.3451	0	0	1843	0.0000000	0.09479	0	437	1941	22.51417	0.3902	0	710	0	0.0000000	0.1079	0	88	12.3943662	0.8263	1	0	693	0.0000000	0.09796	0	10	693	1.443001	0.1643	0	0	1941	0.000000	0.1831	0	2.19120	0.4084	0	2.26919	0.3503	1	0.3902	0.3869	0	1.37956	0.07216	1	6.23015	0.2314	2
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.41320	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.4041	0	139	1313	10.586443	0.5601	0	91	1533	5.936073	0.4343	0	284	16.16392	0.5169	0	325	18.49744	0.2851	0	164	1208	13.57616	0.4127	0	42	359	11.69916	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.46880	0	57	573	9.947644	0.7317	0	212	1757	12.066022	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.91300	0.68620	1	7.83579	0.4802	2
01001020300	01	001	020300	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3694	1464	1351	842	3694	22.79372	0.5833	0	53	1994	2.657974	0.22050	0	117	967	12.099276	0.11370	0	147	384	38.28125	0.3856	0	264	1351	19.54108	0.1827	0	317	2477	12.797739	0.6460	0	127	3673	3.457664	0.2308	0	464	12.56091	0.3088	0	929	25.14889	0.7080	0	473	2744	17.23761	0.6211	0	263	975	26.97436	0.8234	1	128	3586	3.5694367	0.70770	0	1331	3694	36.03140	0.5515	0	1464	26	1.7759563	0.3675	0	14	0.9562842	0.5389	0	35	1351	2.5906736	0.60550	0	42	1351	3.108808	0.3415	0	0	3694	0.000000	0.1831	0	1.86330	0.3063	0	3.16900	0.8380	1	0.5515	0.5468	0	2.03650	0.26830	0	7.62030	0.4460	1
01001020400	01	001	020400	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3539	1741	1636	503	3539	14.21305	0.3472	0	39	1658	2.352232	0.17990	0	219	1290	16.976744	0.30880	0	74	346	21.38728	0.1037	0	293	1636	17.90954	0.1333	0	173	2775	6.234234	0.3351	0	169	3529	4.788892	0.3448	0	969	27.38062	0.9225	1	510	14.41085	0.1208	0	670	3019	22.19278	0.8194	1	148	1137	13.01671	0.4541	0	89	3409	2.6107363	0.64690	0	454	3539	12.82848	0.2364	0	1741	143	8.2136703	0.6028	0	0	0.0000000	0.2186	0	10	1636	0.6112469	0.28340	0	72	1636	4.400978	0.4538	0	0	3539	0.000000	0.1831	0	1.34030	0.1575	0	2.96370	0.7496	2	0.2364	0.2344	0	1.74170	0.16270	0	6.28210	0.2389	2
01001020500	01	001	020500	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	10674	4504	4424	1626	10509	15.47245	0.3851	0	81	5048	1.604596	0.09431	0	321	2299	13.962592	0.17970	0	711	2125	33.45882	0.2836	0	1032	4424	23.32731	0.3109	0	531	6816	7.790493	0.4251	0	301	10046	2.996217	0.1894	0	1613	15.11149	0.4553	0	2765	25.90407	0.7494	0	1124	7281	15.43744	0.5253	0	342	2912	11.74451	0.4019	0	52	9920	0.5241935	0.35230	0	2603	10674	24.38636	0.4160	0	4504	703	15.6083481	0.7378	0	29	0.6438721	0.5037	0	37	4424	0.8363472	0.33420	0	207	4424	4.679023	0.4754	0	176	10674	1.648866	0.7598	1	1.40481	0.1743	0	2.48420	0.4802	0	0.4160	0.4125	0	2.81090	0.63730	1	7.11591	0.3654	1
01001020600	01	001	020600	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3536	1464	1330	1279	3523	36.30429	0.8215	1	34	1223	2.780049	0.23780	0	321	1111	28.892889	0.75870	1	67	219	30.59361	0.2305	0	388	1330	29.17293	0.5075	0	306	2380	12.857143	0.6480	0	415	3496	11.870709	0.7535	1	547	15.46946	0.4760	0	982	27.77149	0.8327	1	729	2514	28.99761	0.9488	1	95	880	10.79545	0.3601	0	0	3394	0.0000000	0.09479	0	985	3536	27.85633	0.4608	0	1464	0	0.0000000	0.1079	0	364	24.8633880	0.9300	1	0	1330	0.0000000	0.09796	0	17	1330	1.278196	0.1463	0	0	3536	0.000000	0.1831	0	2.96830	0.6434	2	2.71239	0.6156	2	0.4608	0.4569	0	1.46526	0.08976	1	7.60675	0.4440	5

# Divisional 2020 Data
svi_2020_divisional <- load_svi_data(svi_2020, rank_by = "divisional", location =  census_division, percentile=.75)
svi_2020_divisional %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

• DATA TABLE

Merge 2010 and 2020 Data

# Find tracts with divisional data in both 2010 and 2020
svi_divisional <- merge_svi_data(svi_2010_divisional, svi_2020_divisional)
svi_divisional %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

• DATA TABLE

# Find tracts with national data in both 2010 and 2020
svi_national <- merge_svi_data(svi_2010_national, svi_2020_national)
svi_national %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20
01001020100	01	001	020100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1809	771	696	297	1809	16.41791	0.3871	0	36	889	4.049494	0.1790	0	127	598	21.23746	0.20770	0	47	98	47.95918	0.5767	0	174	696	25.00000	0.18790	0	196	1242	15.780998	0.6093	0	186	1759	10.574190	0.3790	0	222	12.271973	0.4876	0	445	24.59923	0.5473	0	298	1335	22.32210	0.8454	1	27	545	4.954128	0.09275	0	36	1705	2.1114370	0.59040	0	385	1809	21.282477	0.4524	0	771	0	0.0000000	0.1224	0	92	11.9325551	0.8005	1	0	696	0.0000000	0.1238	0	50	696	7.183908	0.6134	0	0	1809	0	0.364	0	1.74230	0.28200	0	2.56345	0.5296	1	0.4524	0.4482	0	2.0241	0.2519	1	6.78225	0.3278	2	1941	710	693	352	1941	18.13498	0.4630	0	18	852	2.112676	0.15070	0	81	507	15.976331	0.26320	0	63	186	33.87097	0.2913	0	144	693	20.77922	0.2230	0	187	1309	14.285714	0.6928	0	187	1941	9.634209	0.6617	0	295	15.19835	0.4601	0	415	21.38073	0.4681	0	391	1526	25.62254	0.9011	1	58	555	10.45045	0.3451	0	0	1843	0.0000000	0.09479	0	437	1941	22.51417	0.3902	0	710	0	0.0000000	0.1079	0	88	12.3943662	0.8263	1	0	693	0.0000000	0.09796	0	10	693	1.443001	0.1643	0	0	1941	0.000000	0.1831	0	2.19120	0.4084	0	2.26919	0.3503	1	0.3902	0.3869	0	1.37956	0.07216	1	6.23015	0.2314	2
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.5754	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.3019	0	154	730	21.09589	0.09312	0	339	1265	26.798419	0.8392	1	313	2012	15.556660	0.6000	0	204	10.099010	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.83510	1	15	1890	0.7936508	0.40130	0	1243	2020	61.534653	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.7808219	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0	0.364	0	2.70312	0.56650	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.41320	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.4041	0	139	1313	10.586443	0.5601	0	91	1533	5.936073	0.4343	0	284	16.16392	0.5169	0	325	18.49744	0.2851	0	164	1208	13.57616	0.4127	0	42	359	11.69916	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.46880	0	57	573	9.947644	0.7317	0	212	1757	12.066022	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.91300	0.68620	1	7.83579	0.4802	2
01001020300	01	001	020300	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3543	1403	1287	656	3533	18.56779	0.4443	0	93	1552	5.992268	0.3724	0	273	957	28.52665	0.45780	0	178	330	53.93939	0.7152	0	451	1287	35.04274	0.49930	0	346	2260	15.309734	0.5950	0	252	3102	8.123791	0.2596	0	487	13.745413	0.5868	0	998	28.16822	0.7606	1	371	2224	16.68165	0.6266	0	126	913	13.800657	0.46350	0	0	3365	0.0000000	0.09298	0	637	3543	17.979114	0.4049	0	1403	10	0.7127584	0.3015	0	2	0.1425517	0.4407	0	0	1287	0.0000000	0.1238	0	101	1287	7.847708	0.6443	0	0	3543	0	0.364	0	2.17060	0.41010	0	2.53048	0.5116	1	0.4049	0.4011	0	1.8743	0.1942	0	6.98028	0.3576	1	3694	1464	1351	842	3694	22.79372	0.5833	0	53	1994	2.657974	0.22050	0	117	967	12.099276	0.11370	0	147	384	38.28125	0.3856	0	264	1351	19.54108	0.1827	0	317	2477	12.797739	0.6460	0	127	3673	3.457664	0.2308	0	464	12.56091	0.3088	0	929	25.14889	0.7080	0	473	2744	17.23761	0.6211	0	263	975	26.97436	0.8234	1	128	3586	3.5694367	0.70770	0	1331	3694	36.03140	0.5515	0	1464	26	1.7759563	0.3675	0	14	0.9562842	0.5389	0	35	1351	2.5906736	0.60550	0	42	1351	3.108808	0.3415	0	0	3694	0.000000	0.1831	0	1.86330	0.3063	0	3.16900	0.8380	1	0.5515	0.5468	0	2.03650	0.26830	0	7.62030	0.4460	1
01001020400	01	001	020400	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	4840	1957	1839	501	4840	10.35124	0.2177	0	101	2129	4.744011	0.2447	0	310	1549	20.01291	0.17080	0	89	290	30.68966	0.2044	0	399	1839	21.69657	0.10540	0	274	3280	8.353658	0.3205	0	399	4293	9.294200	0.3171	0	955	19.731405	0.8643	1	1195	24.69008	0.5530	0	625	3328	18.78005	0.7233	0	152	1374	11.062591	0.34710	0	10	4537	0.2204100	0.22560	0	297	4840	6.136364	0.1647	0	1957	33	1.6862545	0.3843	0	25	1.2774655	0.5516	0	14	1839	0.7612833	0.3564	0	19	1839	1.033170	0.1127	0	0	4840	0	0.364	0	1.20540	0.13470	0	2.71330	0.6129	1	0.1647	0.1632	0	1.7690	0.1591	0	5.85240	0.1954	1	3539	1741	1636	503	3539	14.21305	0.3472	0	39	1658	2.352232	0.17990	0	219	1290	16.976744	0.30880	0	74	346	21.38728	0.1037	0	293	1636	17.90954	0.1333	0	173	2775	6.234234	0.3351	0	169	3529	4.788892	0.3448	0	969	27.38062	0.9225	1	510	14.41085	0.1208	0	670	3019	22.19278	0.8194	1	148	1137	13.01671	0.4541	0	89	3409	2.6107363	0.64690	0	454	3539	12.82848	0.2364	0	1741	143	8.2136703	0.6028	0	0	0.0000000	0.2186	0	10	1636	0.6112469	0.28340	0	72	1636	4.400978	0.4538	0	0	3539	0.000000	0.1831	0	1.34030	0.1575	0	2.96370	0.7496	2	0.2364	0.2344	0	1.74170	0.16270	0	6.28210	0.2389	2
01001020500	01	001	020500	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	9938	3969	3741	1096	9938	11.02838	0.2364	0	188	4937	3.807981	0.1577	0	426	2406	17.70574	0.11050	0	528	1335	39.55056	0.3753	0	954	3741	25.50120	0.20140	0	293	5983	4.897209	0.1655	0	740	10110	7.319486	0.2211	0	837	8.422218	0.2408	0	3012	30.30791	0.8455	1	759	7155	10.60797	0.2668	0	476	2529	18.821669	0.63540	0	78	9297	0.8389803	0.41110	0	1970	9938	19.822902	0.4330	0	3969	306	7.7097506	0.6153	0	0	0.0000000	0.2198	0	7	3741	0.1871157	0.2535	0	223	3741	5.960973	0.5483	0	0	9938	0	0.364	0	0.98210	0.08468	0	2.39960	0.4381	1	0.4330	0.4290	0	2.0009	0.2430	0	5.81560	0.1905	1	10674	4504	4424	1626	10509	15.47245	0.3851	0	81	5048	1.604596	0.09431	0	321	2299	13.962592	0.17970	0	711	2125	33.45882	0.2836	0	1032	4424	23.32731	0.3109	0	531	6816	7.790493	0.4251	0	301	10046	2.996217	0.1894	0	1613	15.11149	0.4553	0	2765	25.90407	0.7494	0	1124	7281	15.43744	0.5253	0	342	2912	11.74451	0.4019	0	52	9920	0.5241935	0.35230	0	2603	10674	24.38636	0.4160	0	4504	703	15.6083481	0.7378	0	29	0.6438721	0.5037	0	37	4424	0.8363472	0.33420	0	207	4424	4.679023	0.4754	0	176	10674	1.648866	0.7598	1	1.40481	0.1743	0	2.48420	0.4802	0	0.4160	0.4125	0	2.81090	0.63730	1	7.11591	0.3654	1
01001020600	01	001	020600	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3402	1456	1308	735	3402	21.60494	0.5199	0	134	1720	7.790698	0.5436	0	242	1032	23.44961	0.28010	0	62	276	22.46377	0.1035	0	304	1308	23.24159	0.14070	0	301	2151	13.993491	0.5510	0	355	3445	10.304790	0.3656	0	386	11.346267	0.4232	0	931	27.36626	0.7200	0	440	2439	18.04018	0.6912	0	143	924	15.476190	0.52900	0	4	3254	0.1229256	0.19840	0	723	3402	21.252205	0.4519	0	1456	18	1.2362637	0.3507	0	433	29.7390110	0.9468	1	16	1308	1.2232416	0.4493	0	28	1308	2.140673	0.2298	0	0	3402	0	0.364	0	2.12080	0.39510	0	2.56180	0.5288	0	0.4519	0.4477	0	2.3406	0.4048	1	7.47510	0.4314	1	3536	1464	1330	1279	3523	36.30429	0.8215	1	34	1223	2.780049	0.23780	0	321	1111	28.892889	0.75870	1	67	219	30.59361	0.2305	0	388	1330	29.17293	0.5075	0	306	2380	12.857143	0.6480	0	415	3496	11.870709	0.7535	1	547	15.46946	0.4760	0	982	27.77149	0.8327	1	729	2514	28.99761	0.9488	1	95	880	10.79545	0.3601	0	0	3394	0.0000000	0.09479	0	985	3536	27.85633	0.4608	0	1464	0	0.0000000	0.1079	0	364	24.8633880	0.9300	1	0	1330	0.0000000	0.09796	0	17	1330	1.278196	0.1463	0	0	3536	0.000000	0.1831	0	2.96830	0.6434	2	2.71239	0.6156	2	0.4608	0.4569	0	1.46526	0.08976	1	7.60675	0.4440	5

NMTC Data Wrangling

orig_nmtc_df <- orig_nmtc %>% 
  rename("GEOID10" = "2010 Census Tract Number FIPS code. GEOID",
         "nmtc_eligibility_orig" = "Does Census Tract Qualify For NMTC Low-Income Community (LIC) on Poverty or Income Criteria?")

orig_nmtc_df %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	OMB Metro/Non-metro Designation, July 2015 (OMB 15-01)	nmtc_eligibility_orig	Census Tract Poverty Rate % (2011-2015 ACS)	Does Census Tract Qualify on Poverty Criteria\>=20%?	Census Tract Percent of Benchmarked Median Family Income (%) 2011-2015 ACS	Does Census Tract Qualify on Median Family Income Criteria\<=80%?	Census Tract Unemployment Rate (%) 2011-2015	County Code	State Abbreviation	State Name	County Name	Census Tract Unemployment to National Unemployment Ratio	Is Tract Unemployment to National Unemployment Ratio \>1.5?	Population for whom poverty status is determined 2011-2015 ACS
01001020100	Metropolitan	No	8.1	No	122.930646878856	No	5.4	01001	AL	Alabama	Autauga	0.6506024096385542	No	1948
01001020200	Metropolitan	Yes	25.5	Yes	82.402258244451573	No	13.3	01001	AL	Alabama	Autauga	1.6024096385542168	Yes	1983
01001020300	Metropolitan	No	12.7	No	94.261422220719723	No	6.2	01001	AL	Alabama	Autauga	0.74698795180722888	No	2968
01001020400	Metropolitan	No	2.1	No	116.82358310373388	No	10.8	01001	AL	Alabama	Autauga	1.3012048192771084	No	4423
01001020500	Metropolitan	No	11.4	No	127.74293876033198	No	4.2	01001	AL	Alabama	Autauga	0.50602409638554213	No	10563
01001020600	Metropolitan	No	14.4	No	111.98255607579317	No	10.9	01001	AL	Alabama	Autauga	1.3132530120481927	No	3851

high_migration_nmtc_df <- high_migration_nmtc %>% rename("GEOID10" = "2010 Census Tract Number FIPS code GEOID")

high_migration_nmtc_df %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	20-year County population loss 1990-2010 census	% Median Family Income (MFI) / Area Income 2011-2015 (between 80%-85% MFI)
01087231601	-0.1394416	82.06754
05039970300	-0.1558144	84.78236
08017960600	-0.2340426	84.36239
17067953800	-0.1061620	80.36788
17067954200	-0.1061620	84.48551
17067954300	-0.1061620	84.44497

# Add column to label tracts as high migration
high_migration_nmtc_df <- high_migration_nmtc_df %>% mutate(high_migration = "Yes")

# Join to original column
orig_nmtc_df <- left_join(orig_nmtc_df, high_migration_nmtc_df, join_by(GEOID10 == GEOID10))

# Update eligibility column with coalesce()
nmtc_df <- orig_nmtc_df %>% 
  mutate(nmtc_eligibility = coalesce(high_migration, nmtc_eligibility_orig))

nmtc_df %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	OMB Metro/Non-metro Designation, July 2015 (OMB 15-01)	nmtc_eligibility_orig	Census Tract Poverty Rate % (2011-2015 ACS)	Does Census Tract Qualify on Poverty Criteria\>=20%?	Census Tract Percent of Benchmarked Median Family Income (%) 2011-2015 ACS	Does Census Tract Qualify on Median Family Income Criteria\<=80%?	Census Tract Unemployment Rate (%) 2011-2015	County Code	State Abbreviation	State Name	County Name	Census Tract Unemployment to National Unemployment Ratio	Is Tract Unemployment to National Unemployment Ratio \>1.5?	Population for whom poverty status is determined 2011-2015 ACS	20-year County population loss 1990-2010 census	% Median Family Income (MFI) / Area Income 2011-2015 (between 80%-85% MFI)	high_migration	nmtc_eligibility
01001020100	Metropolitan	No	8.1	No	122.930646878856	No	5.4	01001	AL	Alabama	Autauga	0.6506024096385542	No	1948	NA	NA	NA	No
01001020200	Metropolitan	Yes	25.5	Yes	82.402258244451573	No	13.3	01001	AL	Alabama	Autauga	1.6024096385542168	Yes	1983	NA	NA	NA	Yes
01001020300	Metropolitan	No	12.7	No	94.261422220719723	No	6.2	01001	AL	Alabama	Autauga	0.74698795180722888	No	2968	NA	NA	NA	No
01001020400	Metropolitan	No	2.1	No	116.82358310373388	No	10.8	01001	AL	Alabama	Autauga	1.3012048192771084	No	4423	NA	NA	NA	No
01001020500	Metropolitan	No	11.4	No	127.74293876033198	No	4.2	01001	AL	Alabama	Autauga	0.50602409638554213	No	10563	NA	NA	NA	No
01001020600	Metropolitan	No	14.4	No	111.98255607579317	No	10.9	01001	AL	Alabama	Autauga	1.3132530120481927	No	3851	NA	NA	NA	No

nmtc_eligible <- nmtc_df %>% 
  select(GEOID10, nmtc_eligibility, `County Code`, `County Name`, `State Abbreviation`, `State Name`) %>% 
  filter(tolower(nmtc_eligibility) == "yes")

nmtc_eligible %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	nmtc_eligibility	County Code	County Name	State Abbreviation	State Name
01001020200	Yes	01001	Autauga	AL	Alabama
01001020700	Yes	01001	Autauga	AL	Alabama
01001021100	Yes	01001	Autauga	AL	Alabama
01003010200	Yes	01003	Baldwin	AL	Alabama
01003010500	Yes	01003	Baldwin	AL	Alabama
01003010600	Yes	01003	Baldwin	AL	Alabama

# Save just tract ID and eligibility
nmtc_eligible_df <- nmtc_eligible %>% select(GEOID10, nmtc_eligibility)
nmtc_eligible_df %>% head()

## # A tibble: 6 × 2
##   GEOID10     nmtc_eligibility
##   <chr>       <chr>           
## 1 01001020200 Yes             
## 2 01001020700 Yes             
## 3 01001021100 Yes             
## 4 01003010200 Yes             
## 5 01003010500 Yes             
## 6 01003010600 Yes

nmtc_awards_data %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

Project ID	2010 Census Tract	Metro/Non-Metro, 2010 Census	Origination Year	Community Development Entity (CDE) Name	Project QLICI Amount	Estimated Total Project Cost	City	State	Zip Code	QALICB Type	Multi-CDE	Multi-Tract Project
AK0001	2070000100	Non-Metropolitan	2008	Alaska Growth Capital BIDCO, Inc.	300000	300000	Aleknagik	Alaska	99555	NRE	NO	NO
AK0002	2020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	1008750	1345000	Anchorage	Alaska	99501	NRE	NO	NO
AK0003	2020000600	Metropolitan	2006	HEDC New Markets, Inc	5061506	8694457	Anchorage	Alaska	99508	NRE	NO	NO
AK0004	2020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	187500	250000	Anchorage	Alaska	99501	NRE	NO	NO
AK0006	2020001802	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	750000	1180000	Anchorage	Alaska	99507	NRE	NO	NO
AK0007	2020001900	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	127500	150000	Anchorage	Alaska	99503	NRE	NO	NO

nmtc_awards <- nmtc_awards_data %>% 
  mutate(`2010 Census Tract` = str_pad(`2010 Census Tract`, 11, "left", pad=0)) %>%
  rename("GEOID10" =`2010 Census Tract`)

nmtc_awards %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

Project ID	GEOID10	Metro/Non-Metro, 2010 Census	Origination Year	Community Development Entity (CDE) Name	Project QLICI Amount	Estimated Total Project Cost	City	State	Zip Code	QALICB Type	Multi-CDE	Multi-Tract Project
AK0001	02070000100	Non-Metropolitan	2008	Alaska Growth Capital BIDCO, Inc.	300000	300000	Aleknagik	Alaska	99555	NRE	NO	NO
AK0002	02020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	1008750	1345000	Anchorage	Alaska	99501	NRE	NO	NO
AK0003	02020000600	Metropolitan	2006	HEDC New Markets, Inc	5061506	8694457	Anchorage	Alaska	99508	NRE	NO	NO
AK0004	02020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	187500	250000	Anchorage	Alaska	99501	NRE	NO	NO
AK0006	02020001802	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	750000	1180000	Anchorage	Alaska	99507	NRE	NO	NO
AK0007	02020001900	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	127500	150000	Anchorage	Alaska	99503	NRE	NO	NO

# Create character zip_code column:
nmtc_awards <- nmtc_awards %>% 
  mutate(zip_code = str_pad(`Zip Code`, 5, "left", pad=0))

nmtc_awards %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

Project ID	GEOID10	Metro/Non-Metro, 2010 Census	Origination Year	Community Development Entity (CDE) Name	Project QLICI Amount	Estimated Total Project Cost	City	State	Zip Code	QALICB Type	Multi-CDE	Multi-Tract Project	zip_code
AK0001	02070000100	Non-Metropolitan	2008	Alaska Growth Capital BIDCO, Inc.	300000	300000	Aleknagik	Alaska	99555	NRE	NO	NO	99555
AK0002	02020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	1008750	1345000	Anchorage	Alaska	99501	NRE	NO	NO	99501
AK0003	02020000600	Metropolitan	2006	HEDC New Markets, Inc	5061506	8694457	Anchorage	Alaska	99508	NRE	NO	NO	99508
AK0004	02020001000	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	187500	250000	Anchorage	Alaska	99501	NRE	NO	NO	99501
AK0006	02020001802	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	750000	1180000	Anchorage	Alaska	99507	NRE	NO	NO	99507
AK0007	02020001900	Metropolitan	2006	Alaska Growth Capital BIDCO, Inc.	127500	150000	Anchorage	Alaska	99503	NRE	NO	NO	99503

# View tracts
nmtc_awards_pre2010 <- nmtc_awards %>% 
  filter(`Origination Year` <= 2010) %>% 
  count(GEOID10) %>% 
  rename("pre10_nmtc_project_cnt" = "n")

nmtc_awards_dollars_pre2010 <- nmtc_awards %>% 
  filter(`Origination Year` <= 2010) %>% 
  group_by(GEOID10) %>% 
  summarise(pre10_nmtc_dollars = sum(`Project QLICI Amount`, na.rm = TRUE))

nmtc_awards_pre2010 <- left_join(nmtc_awards_pre2010, 
                                 nmtc_awards_dollars_pre2010, 
                                 join_by(GEOID10 == GEOID10))

nmtc_awards_pre2010$pre10_nmtc_dollars_formatted <- scales::dollar_format()(nmtc_awards_pre2010$pre10_nmtc_dollars)

nmtc_awards_pre2010 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted
01059973500	1	5000000	\$5,000,000
01069041400	1	2500000	\$2,500,000
01073001902	1	14400000	\$14,400,000
01073002700	1	1000000	\$1,000,000
01073004200	1	5908129	\$5,908,129
01073004500	3	37950000	\$37,950,000

nmtc_awards_post2010 <- nmtc_awards %>% 
  filter(`Origination Year` > 2010 & `Origination Year` <= 2020) %>% 
  count(GEOID10) %>% 
  rename("post10_nmtc_project_cnt" = "n")

nmtc_awards_dollars_post2010 <- nmtc_awards %>% 
  filter(`Origination Year` > 2010 & `Origination Year` <= 2020) %>% 
  group_by(GEOID10) %>% 
  summarise(post10_nmtc_dollars = sum(`Project QLICI Amount`, na.rm = TRUE))

nmtc_awards_post2010 <- left_join(nmtc_awards_post2010, 
                                  nmtc_awards_dollars_post2010, 
                                  join_by(GEOID10 == GEOID10))

nmtc_awards_post2010$post10_nmtc_dollars_formatted <- scales::dollar_format()(nmtc_awards_post2010$post10_nmtc_dollars)

nmtc_awards_post2010 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID10	post10_nmtc_project_cnt	post10_nmtc_dollars	post10_nmtc_dollars_formatted
0.	3	24200000	\$24,200,000
01003010200	1	408000	\$408,000
01003010300	1	9880000	\$9,880,000
01003010600	1	8000000	\$8,000,000
01003010904	1	22460000	\$22,460,000
01003011501	6	37147460	\$37,147,460

# Divisional data
svi_divisional_nmtc_eligible <- left_join(svi_divisional, nmtc_eligible_df, join_by("GEOID_2010_trt" == "GEOID10")) %>% filter(tolower(nmtc_eligibility) == "yes")

svi_divisional_nmtc_eligible %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility
34001000100	34	001	000100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2907	1088	983	1127	2907	38.76849	0.8482	1	144	1433	10.048849	0.7544	1	280	435	64.36782	0.9529	1	204	548	37.22628	0.2998	0	484	983	49.23703	0.7813	1	468	1759	26.60603	0.8634	1	532	2543	20.92017	0.8978	1	250	8.599931	0.1777	0	944	32.47334	0.94170	1	186	1851	10.04862	0.2706	0	266	678	39.233038	0.8981	1	177	2611	6.779012	0.7778	1	1928	2907	66.32267	0.7743	1	1088	113	10.386029	0.6229	0	9	0.8272059	0.7223	0	80	983	8.138352	0.8657	1	265	983	26.95829	0.7354	0	0	2907	0.000000	0.3512	0	4.1451	0.8935	5	3.06590	0.7944	3	0.7743	0.7667	1	3.2975	0.8414	1	11.28280	0.8862	10	2157	941	784	1182	2157	54.79833	0.9571	1	242	1058	22.873346	0.9922	1	215	342	62.86550	0.9780	1	316	442	71.49321	0.9481	1	531	784	67.72959	0.9893	1	396	1274	31.08320	0.9497	1	266	2157	12.331943	0.9041	1	185	8.576727	0.09430	0	552	25.59110	0.8128	1	297	1605	18.504673	0.74880	0	83	510	16.27451	0.6090	0	251	2020	12.425743	0.8710	1	1852	2157	85.85999	0.8476	1	941	118	12.5398512	0.6385	0	0	0.0000000	0.3216	0	67	784	8.545918	0.8657	1	212	784	27.04082	0.7502	1	0	2157	0.0000000	0.1517	0	4.7924	0.9850	5	3.13590	0.8217	2	0.8476	0.8400	1	2.7277	0.6085	2	11.50360	0.9104	10	Yes
34001000200	34	001	000200	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3189	2217	1473	519	3189	16.27469	0.4806	0	109	1558	6.996149	0.5179	0	573	955	60.00000	0.9323	1	199	518	38.41699	0.3261	0	772	1473	52.41005	0.8418	1	405	2579	15.70376	0.6491	0	484	3547	13.64533	0.7154	0	847	26.560050	0.9629	1	436	13.67200	0.08181	0	608	3005	20.23295	0.8466	1	42	857	4.900817	0.1204	0	422	3072	13.736979	0.8799	1	1792	3189	56.19316	0.7390	0	2217	901	40.640505	0.8693	1	0	0.0000000	0.3251	0	48	1473	3.258656	0.7064	0	250	1473	16.97217	0.6444	0	0	3189	0.000000	0.3512	0	3.2048	0.6963	1	2.89161	0.7231	3	0.7390	0.7317	0	2.8964	0.6887	1	9.73181	0.7340	5	3510	2046	1353	1021	3510	29.08832	0.7682	1	121	1852	6.533477	0.6717	0	343	696	49.28161	0.9273	1	416	657	63.31811	0.8696	1	759	1353	56.09756	0.9321	1	553	2338	23.65269	0.8871	1	354	3510	10.085470	0.8530	1	643	18.319088	0.60310	0	1002	28.54701	0.9055	1	450	2508	17.942584	0.72330	0	237	786	30.15267	0.8539	1	534	3375	15.822222	0.9062	1	2534	3510	72.19373	0.7818	1	2046	906	44.2815249	0.8690	1	0	0.0000000	0.3216	0	119	1353	8.795270	0.8711	1	324	1353	23.94678	0.7255	0	0	3510	0.0000000	0.1517	0	4.1121	0.9003	4	3.99200	0.9781	3	0.7818	0.7747	1	2.9389	0.7011	2	11.82480	0.9310	10	Yes
34001000300	34	001	000300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3997	1823	1357	1401	3968	35.30746	0.8164	1	382	2238	17.068811	0.9376	1	176	329	53.49544	0.8855	1	604	1028	58.75486	0.7947	1	780	1357	57.47973	0.9165	1	920	2677	34.36683	0.9346	1	1351	4149	32.56206	0.9811	1	314	7.855892	0.1437	0	937	23.44258	0.55900	0	319	3054	10.44532	0.3000	0	187	782	23.913044	0.7498	0	1080	3671	29.419777	0.9742	1	3357	3997	83.98799	0.8419	1	1823	363	19.912233	0.7535	1	0	0.0000000	0.3251	0	150	1357	11.053795	0.9136	1	651	1357	47.97347	0.8585	1	0	3997	0.000000	0.3512	0	4.5862	0.9691	5	2.72670	0.6360	1	0.8419	0.8336	1	3.2019	0.8054	3	11.35670	0.8920	10	3801	1640	1226	1857	3801	48.85556	0.9333	1	226	1800	12.555556	0.9267	1	111	280	39.64286	0.8339	1	608	946	64.27061	0.8842	1	719	1226	58.64600	0.9528	1	650	2275	28.57143	0.9337	1	1027	3801	27.019206	0.9914	1	380	9.997369	0.14040	0	1223	32.17574	0.9607	1	219	2578	8.494957	0.15680	0	268	909	29.48295	0.8456	1	940	3400	27.647059	0.9728	1	3318	3801	87.29282	0.8579	1	1640	262	15.9756098	0.6917	0	0	0.0000000	0.3216	0	124	1226	10.114192	0.8955	1	477	1226	38.90701	0.8258	1	0	3801	0.0000000	0.1517	0	4.7379	0.9829	5	3.07630	0.8013	3	0.8579	0.8501	1	2.8863	0.6781	2	11.55840	0.9150	11	Yes
34001000400	34	001	000400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2902	2683	1401	1172	2902	40.38594	0.8615	1	190	1389	13.678906	0.8811	1	364	707	51.48515	0.8627	1	507	694	73.05476	0.9503	1	871	1401	62.16988	0.9572	1	481	1981	24.28067	0.8339	1	674	3204	21.03620	0.8998	1	434	14.955203	0.6083	0	596	20.53756	0.33980	0	426	2607	16.34062	0.6886	0	111	652	17.024540	0.6204	0	215	2736	7.858187	0.8008	1	1792	2902	61.75052	0.7584	1	2683	2049	76.369735	0.9401	1	0	0.0000000	0.3251	0	69	1401	4.925053	0.7847	1	511	1401	36.47395	0.7992	1	72	2902	2.481048	0.8114	1	4.4335	0.9468	5	3.05790	0.7908	1	0.7584	0.7510	1	3.6605	0.9391	4	11.91030	0.9339	11	3178	2264	1390	1508	3176	47.48111	0.9246	1	172	1804	9.534368	0.8460	1	205	468	43.80342	0.8858	1	622	922	67.46204	0.9192	1	827	1390	59.49640	0.9587	1	364	2076	17.53372	0.8013	1	476	3178	14.977974	0.9390	1	483	15.198238	0.41220	0	539	16.96035	0.2484	0	319	2639	12.087912	0.38790	0	101	565	17.87611	0.6539	0	583	3022	19.291860	0.9349	1	2186	3178	68.78540	0.7658	1	2264	1609	71.0689046	0.9266	1	15	0.6625442	0.7078	0	226	1390	16.258993	0.9567	1	599	1390	43.09353	0.8474	1	20	3178	0.6293266	0.6292	0	4.4696	0.9558	5	2.63730	0.5864	1	0.7658	0.7588	1	4.0677	0.9762	3	11.94040	0.9387	10	Yes
34001000500	34	001	000500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3483	1241	1027	1938	3483	55.64169	0.9533	1	124	1630	7.607362	0.5830	0	227	446	50.89686	0.8549	1	478	581	82.27194	0.9799	1	705	1027	68.64654	0.9863	1	733	2077	35.29129	0.9396	1	727	3258	22.31430	0.9149	1	377	10.824002	0.3081	0	1055	30.28998	0.90140	1	268	2401	11.16202	0.3549	0	209	763	27.391874	0.7940	1	911	3077	29.606760	0.9746	1	3036	3483	87.16624	0.8550	1	1241	52	4.190169	0.4505	0	4	0.3223207	0.6567	0	113	1027	11.002921	0.9128	1	422	1027	41.09056	0.8250	1	0	3483	0.000000	0.3512	0	4.3771	0.9379	4	3.33300	0.8766	3	0.8550	0.8467	1	3.1962	0.8026	2	11.76130	0.9229	10	3385	1185	945	1682	3364	50.00000	0.9391	1	72	1577	4.565631	0.4586	0	185	468	39.52991	0.8332	1	362	477	75.89099	0.9703	1	547	945	57.88360	0.9477	1	592	1983	29.85376	0.9422	1	738	3385	21.802068	0.9817	1	240	7.090103	0.05988	0	1129	33.35303	0.9689	1	135	2256	5.984043	0.04817	0	110	717	15.34170	0.5822	0	721	3076	23.439532	0.9569	1	3029	3385	89.48301	0.8727	1	1185	9	0.7594937	0.2382	0	0	0.0000000	0.3216	0	103	945	10.899471	0.9072	1	263	945	27.83069	0.7560	1	0	3385	0.0000000	0.1517	0	4.2693	0.9283	4	2.61605	0.5709	2	0.8727	0.8648	1	2.3747	0.4357	2	10.13275	0.7921	9	Yes
34001001100	34	001	001100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2204	1204	1204	1185	2204	53.76588	0.9457	1	219	927	23.624596	0.9830	1	97	172	56.39535	0.9094	1	462	1032	44.76744	0.4746	0	559	1204	46.42857	0.7197	0	346	1440	24.02778	0.8306	1	469	1942	24.15036	0.9360	1	363	16.470054	0.7020	0	578	26.22505	0.74410	0	442	1558	28.36970	0.9675	1	247	396	62.373737	0.9898	1	104	2051	5.070697	0.7260	0	2118	2204	96.09800	0.9204	1	1204	570	47.342193	0.8858	1	0	0.0000000	0.3251	0	14	1204	1.162791	0.4877	0	817	1204	67.85714	0.9413	1	0	2204	0.000000	0.3512	0	4.4150	0.9451	4	4.12940	0.9805	2	0.9204	0.9114	1	2.9911	0.7243	2	12.45590	0.9597	9	1950	1267	1096	1131	1950	58.00000	0.9678	1	66	706	9.348442	0.8395	1	42	101	41.58416	0.8612	1	309	995	31.05528	0.1959	0	351	1096	32.02555	0.4782	0	510	1379	36.98332	0.9763	1	155	1950	7.948718	0.7660	1	392	20.102564	0.69880	0	447	22.92308	0.6712	0	570	1503	37.924152	0.99200	1	143	374	38.23529	0.9167	1	109	1841	5.920695	0.7464	0	1909	1950	97.89744	0.9529	1	1267	479	37.8058406	0.8464	1	0	0.0000000	0.3216	0	33	1096	3.010949	0.6446	0	743	1096	67.79197	0.9414	1	0	1950	0.0000000	0.1517	0	4.0278	0.8848	4	4.02510	0.9798	2	0.9529	0.9442	1	2.9057	0.6869	2	11.91150	0.9365	9	Yes

# National data
svi_national_nmtc_eligible <- left_join(svi_national, nmtc_eligible_df, join_by("GEOID_2010_trt" == "GEOID10")) %>% filter(tolower(nmtc_eligibility) == "yes")

svi_national_nmtc_eligible %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.57540	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.30190	0	154	730	21.09589	0.09312	0	339	1265	26.79842	0.8392	1	313	2012	15.55666	0.6000	0	204	10.09901	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.8351	1	15	1890	0.7936508	0.40130	0	1243	2020	61.53465	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.780822	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0.0000	0.3640	0	2.70312	0.5665	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.4132	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.40410	0	139	1313	10.58644	0.5601	0	91	1533	5.936073	0.4343	0	284	16.163916	0.5169	0	325	18.49744	0.2851	0	164	1208.000	13.57616	0.4127	0	42	359.0000	11.699164	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757.000	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.4688	0	57	573.000	9.947644	0.7317	0	212	1757	12.0660216	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.9130	0.6862	1	7.83579	0.4802	2	Yes
01001020700	01	001	020700	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2664	1254	1139	710	2664	26.65165	0.6328	0	29	1310	2.213741	0.05255	0	134	710	18.87324	0.13890	0	187	429	43.58974	0.47090	0	321	1139	28.18262	0.28130	0	396	1852	21.38229	0.7478	0	345	2878	11.98749	0.4459	0	389	14.60210	0.6417	0	599	22.48499	0.4007	0	510	2168	23.52399	0.8752	1	228	712	32.022472	0.8712	1	0	2480	0.0000000	0.09298	0	694	2664	26.05105	0.5138	0	1254	8	0.6379585	0.2931	0	460	36.6826156	0.9714	1	0	1139	0.000000	0.1238	0	125	1139	10.974539	0.7477	0	0	2664	0.0000	0.3640	0	2.16035	0.4069	0	2.88178	0.6997	2	0.5138	0.5090	0	2.5000	0.4882	1	8.05593	0.5185	3	3562	1313	1248	1370	3528	38.83220	0.8512	1	128	1562	8.194622	0.7935	1	168	844	19.905213	0.44510	0	237	404	58.66337	0.8359	1	405	1248	32.45192	0.60420	0	396	2211	17.91045	0.7857	1	444	3547	12.517620	0.7758	1	355	9.966311	0.1800	0	954	26.78271	0.7923	1	629	2593.000	24.25762	0.8730	1	171	797.0000	21.455458	0.7186	0	0	3211	0.0000000	0.09479	0	1009	3562.000	28.32678	0.4668	0	1313	14	1.0662605	0.3165	0	443	33.7395278	0.9663	1	73	1248	5.8493590	0.8211	1	17	1248.000	1.362180	0.1554	0	112	3562	3.1443010	0.8514	1	3.81040	0.8569	4	2.65869	0.5847	2	0.4668	0.4629	0	3.1107	0.7714	3	10.04659	0.7851	9	Yes
01001021100	01	001	021100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3298	1502	1323	860	3298	26.07641	0.6211	0	297	1605	18.504673	0.94340	1	250	1016	24.60630	0.32070	0	74	307	24.10423	0.11920	0	324	1323	24.48980	0.17380	0	710	2231	31.82429	0.8976	1	654	3565	18.34502	0.7018	0	411	12.46210	0.5001	0	738	22.37720	0.3934	0	936	2861	32.71583	0.9807	1	138	825	16.727273	0.5715	0	9	3155	0.2852615	0.25010	0	1979	3298	60.00606	0.7703	1	1502	14	0.9320905	0.3234	0	659	43.8748336	0.9849	1	44	1323	3.325775	0.7062	0	137	1323	10.355253	0.7313	0	0	3298	0.0000	0.3640	0	3.33770	0.7351	2	2.69580	0.6028	1	0.7703	0.7631	1	3.1098	0.7827	1	9.91360	0.7557	5	3499	1825	1462	1760	3499	50.30009	0.9396	1	42	966	4.347826	0.4539	0	426	1274	33.437991	0.85200	1	52	188	27.65957	0.1824	0	478	1462	32.69494	0.61110	0	422	2488	16.96141	0.7638	1	497	3499	14.204058	0.8246	1	853	24.378394	0.8688	1	808	23.09231	0.5829	0	908	2691.100	33.74084	0.9808	1	179	811.6985	22.052524	0.7323	0	8	3248	0.2463054	0.26220	0	1986	3498.713	56.76373	0.7175	0	1825	29	1.5890411	0.3551	0	576	31.5616438	0.9594	1	88	1462	6.0191518	0.8269	1	148	1461.993	10.123166	0.7364	0	38	3499	1.0860246	0.7013	0	3.59300	0.8073	3	3.42700	0.9156	2	0.7175	0.7114	0	3.5791	0.9216	2	11.31660	0.9150	7	Yes
01003010200	01	003	010200	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	2612	1220	1074	338	2605	12.97505	0.2907	0	44	1193	3.688181	0.14720	0	172	928	18.53448	0.13090	0	31	146	21.23288	0.09299	0	203	1074	18.90130	0.05657	0	455	1872	24.30556	0.8016	1	456	2730	16.70330	0.6445	0	401	15.35222	0.6847	0	563	21.55436	0.3406	0	410	2038	20.11776	0.7755	1	64	779	8.215661	0.2181	0	0	2510	0.0000000	0.09298	0	329	2612	12.59571	0.3113	0	1220	38	3.1147541	0.4648	0	385	31.5573770	0.9545	1	20	1074	1.862197	0.5509	0	43	1074	4.003724	0.4088	0	0	2612	0.0000	0.3640	0	1.94057	0.3398	1	2.11188	0.2802	1	0.3113	0.3084	0	2.7430	0.6129	1	7.10675	0.3771	3	2928	1312	1176	884	2928	30.19126	0.7334	0	29	1459	1.987663	0.1356	0	71	830	8.554217	0.03726	0	134	346	38.72832	0.3964	0	205	1176	17.43197	0.12010	0	294	2052	14.32749	0.6940	0	219	2925	7.487179	0.5423	0	556	18.989071	0.6705	0	699	23.87295	0.6339	0	489	2226.455	21.96317	0.8122	1	191	783.8820	24.365914	0.7799	1	0	2710	0.0000000	0.09479	0	398	2927.519	13.59513	0.2511	0	1312	13	0.9908537	0.3111	0	400	30.4878049	0.9557	1	6	1176	0.5102041	0.2590	0	81	1176.202	6.886570	0.6115	0	7	2928	0.2390710	0.4961	0	2.22540	0.4183	0	2.99129	0.7634	2	0.2511	0.2490	0	2.6334	0.5496	1	8.10119	0.5207	3	Yes
01003010500	01	003	010500	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	4230	1779	1425	498	3443	14.46413	0.3337	0	166	1625	10.215385	0.71790	0	151	1069	14.12535	0.04638	0	196	356	55.05618	0.73830	0	347	1425	24.35088	0.17010	0	707	2945	24.00679	0.7967	1	528	4001	13.19670	0.5005	0	619	14.63357	0.6436	0	790	18.67612	0.1937	0	536	3096	17.31266	0.6572	0	165	920	17.934783	0.6102	0	20	4021	0.4973887	0.32320	0	754	4230	17.82506	0.4023	0	1779	97	5.4525014	0.5525	0	8	0.4496908	0.4600	0	63	1425	4.421053	0.7762	1	90	1425	6.315790	0.5691	0	787	4230	18.6052	0.9649	1	2.51890	0.5121	1	2.42790	0.4539	0	0.4023	0.3986	0	3.3227	0.8628	2	8.67180	0.6054	3	5877	1975	1836	820	5244	15.63692	0.3902	0	90	2583	3.484321	0.3361	0	159	1345	11.821561	0.10530	0	139	491	28.30957	0.1924	0	298	1836	16.23094	0.09053	0	570	4248	13.41808	0.6669	0	353	5247	6.727654	0.4924	0	1109	18.870172	0.6645	0	1144	19.46571	0.3411	0	717	4102.545	17.47696	0.6332	0	103	1286.1180	8.008596	0.2341	0	0	5639	0.0000000	0.09479	0	868	5877.481	14.76823	0.2709	0	1975	26	1.3164557	0.3359	0	45	2.2784810	0.6271	0	9	1836	0.4901961	0.2540	0	116	1835.798	6.318779	0.5811	0	633	5877	10.7708014	0.9507	1	1.97613	0.3410	0	1.96769	0.1961	0	0.2709	0.2686	0	2.7488	0.6077	1	6.96352	0.3406	1	Yes
01003010600	01	003	010600	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	3724	1440	1147	1973	3724	52.98067	0.9342	1	142	1439	9.867964	0.69680	0	235	688	34.15698	0.62950	0	187	459	40.74074	0.40290	0	422	1147	36.79163	0.55150	0	497	1876	26.49254	0.8354	1	511	3661	13.95794	0.5334	0	246	6.60580	0.1481	0	1256	33.72718	0.9305	1	496	2522	19.66693	0.7587	1	274	838	32.696897	0.8779	1	32	3479	0.9198045	0.42810	0	2606	3724	69.97852	0.8184	1	1440	21	1.4583333	0.3683	0	321	22.2916667	0.9036	1	97	1147	8.456844	0.8956	1	167	1147	14.559721	0.8209	1	0	3724	0.0000	0.3640	0	3.55130	0.7859	2	3.14330	0.8145	3	0.8184	0.8108	1	3.3524	0.8725	3	10.86540	0.8550	9	4115	1534	1268	1676	3997	41.93145	0.8814	1	294	1809	16.252073	0.9674	1	341	814	41.891892	0.94320	1	204	454	44.93392	0.5438	0	545	1268	42.98107	0.83620	1	624	2425	25.73196	0.9002	1	994	4115	24.155529	0.9602	1	642	15.601458	0.4841	0	1126	27.36331	0.8175	1	568	2989.000	19.00301	0.7045	0	212	715.0000	29.650350	0.8592	1	56	3825	1.4640523	0.53120	0	2715	4115.000	65.97813	0.7732	1	1534	0	0.0000000	0.1079	0	529	34.4850065	0.9685	1	101	1268	7.9652997	0.8795	1	89	1268.000	7.018927	0.6184	0	17	4115	0.4131227	0.5707	0	4.54540	0.9754	5	3.39650	0.9081	2	0.7732	0.7667	1	3.1450	0.7858	2	11.86010	0.9520	10	Yes

# Join divisional data to nmtc_awards_pre2010, set count to 0 if no data
svi_divisional_nmtc_eligible <- 
  left_join(svi_divisional_nmtc_eligible, nmtc_awards_pre2010, join_by("GEOID_2010_trt" == "GEOID10")) %>%
  mutate(pre10_nmtc_project_cnt = if_else(is.na(pre10_nmtc_project_cnt), 0, pre10_nmtc_project_cnt)) %>%
    mutate(pre10_nmtc_dollars = if_else(is.na(pre10_nmtc_dollars), 0, pre10_nmtc_dollars)) %>%
    mutate(pre10_nmtc_dollars_formatted = if_else(is.na(pre10_nmtc_dollars_formatted), "$0", pre10_nmtc_dollars_formatted))

# View table
svi_divisional_nmtc_eligible %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted
34001000100	34	001	000100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2907	1088	983	1127	2907	38.76849	0.8482	1	144	1433	10.048849	0.7544	1	280	435	64.36782	0.9529	1	204	548	37.22628	0.2998	0	484	983	49.23703	0.7813	1	468	1759	26.60603	0.8634	1	532	2543	20.92017	0.8978	1	250	8.599931	0.1777	0	944	32.47334	0.94170	1	186	1851	10.04862	0.2706	0	266	678	39.233038	0.8981	1	177	2611	6.779012	0.7778	1	1928	2907	66.32267	0.7743	1	1088	113	10.386029	0.6229	0	9	0.8272059	0.7223	0	80	983	8.138352	0.8657	1	265	983	26.95829	0.7354	0	0	2907	0.000000	0.3512	0	4.1451	0.8935	5	3.06590	0.7944	3	0.7743	0.7667	1	3.2975	0.8414	1	11.28280	0.8862	10	2157	941	784	1182	2157	54.79833	0.9571	1	242	1058	22.873346	0.9922	1	215	342	62.86550	0.9780	1	316	442	71.49321	0.9481	1	531	784	67.72959	0.9893	1	396	1274	31.08320	0.9497	1	266	2157	12.331943	0.9041	1	185	8.576727	0.09430	0	552	25.59110	0.8128	1	297	1605	18.504673	0.74880	0	83	510	16.27451	0.6090	0	251	2020	12.425743	0.8710	1	1852	2157	85.85999	0.8476	1	941	118	12.5398512	0.6385	0	0	0.0000000	0.3216	0	67	784	8.545918	0.8657	1	212	784	27.04082	0.7502	1	0	2157	0.0000000	0.1517	0	4.7924	0.9850	5	3.13590	0.8217	2	0.8476	0.8400	1	2.7277	0.6085	2	11.50360	0.9104	10	Yes	0	0	\$0
34001000200	34	001	000200	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3189	2217	1473	519	3189	16.27469	0.4806	0	109	1558	6.996149	0.5179	0	573	955	60.00000	0.9323	1	199	518	38.41699	0.3261	0	772	1473	52.41005	0.8418	1	405	2579	15.70376	0.6491	0	484	3547	13.64533	0.7154	0	847	26.560050	0.9629	1	436	13.67200	0.08181	0	608	3005	20.23295	0.8466	1	42	857	4.900817	0.1204	0	422	3072	13.736979	0.8799	1	1792	3189	56.19316	0.7390	0	2217	901	40.640505	0.8693	1	0	0.0000000	0.3251	0	48	1473	3.258656	0.7064	0	250	1473	16.97217	0.6444	0	0	3189	0.000000	0.3512	0	3.2048	0.6963	1	2.89161	0.7231	3	0.7390	0.7317	0	2.8964	0.6887	1	9.73181	0.7340	5	3510	2046	1353	1021	3510	29.08832	0.7682	1	121	1852	6.533477	0.6717	0	343	696	49.28161	0.9273	1	416	657	63.31811	0.8696	1	759	1353	56.09756	0.9321	1	553	2338	23.65269	0.8871	1	354	3510	10.085470	0.8530	1	643	18.319088	0.60310	0	1002	28.54701	0.9055	1	450	2508	17.942584	0.72330	0	237	786	30.15267	0.8539	1	534	3375	15.822222	0.9062	1	2534	3510	72.19373	0.7818	1	2046	906	44.2815249	0.8690	1	0	0.0000000	0.3216	0	119	1353	8.795270	0.8711	1	324	1353	23.94678	0.7255	0	0	3510	0.0000000	0.1517	0	4.1121	0.9003	4	3.99200	0.9781	3	0.7818	0.7747	1	2.9389	0.7011	2	11.82480	0.9310	10	Yes	0	0	\$0
34001000300	34	001	000300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3997	1823	1357	1401	3968	35.30746	0.8164	1	382	2238	17.068811	0.9376	1	176	329	53.49544	0.8855	1	604	1028	58.75486	0.7947	1	780	1357	57.47973	0.9165	1	920	2677	34.36683	0.9346	1	1351	4149	32.56206	0.9811	1	314	7.855892	0.1437	0	937	23.44258	0.55900	0	319	3054	10.44532	0.3000	0	187	782	23.913044	0.7498	0	1080	3671	29.419777	0.9742	1	3357	3997	83.98799	0.8419	1	1823	363	19.912233	0.7535	1	0	0.0000000	0.3251	0	150	1357	11.053795	0.9136	1	651	1357	47.97347	0.8585	1	0	3997	0.000000	0.3512	0	4.5862	0.9691	5	2.72670	0.6360	1	0.8419	0.8336	1	3.2019	0.8054	3	11.35670	0.8920	10	3801	1640	1226	1857	3801	48.85556	0.9333	1	226	1800	12.555556	0.9267	1	111	280	39.64286	0.8339	1	608	946	64.27061	0.8842	1	719	1226	58.64600	0.9528	1	650	2275	28.57143	0.9337	1	1027	3801	27.019206	0.9914	1	380	9.997369	0.14040	0	1223	32.17574	0.9607	1	219	2578	8.494957	0.15680	0	268	909	29.48295	0.8456	1	940	3400	27.647059	0.9728	1	3318	3801	87.29282	0.8579	1	1640	262	15.9756098	0.6917	0	0	0.0000000	0.3216	0	124	1226	10.114192	0.8955	1	477	1226	38.90701	0.8258	1	0	3801	0.0000000	0.1517	0	4.7379	0.9829	5	3.07630	0.8013	3	0.8579	0.8501	1	2.8863	0.6781	2	11.55840	0.9150	11	Yes	0	0	\$0
34001000400	34	001	000400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2902	2683	1401	1172	2902	40.38594	0.8615	1	190	1389	13.678906	0.8811	1	364	707	51.48515	0.8627	1	507	694	73.05476	0.9503	1	871	1401	62.16988	0.9572	1	481	1981	24.28067	0.8339	1	674	3204	21.03620	0.8998	1	434	14.955203	0.6083	0	596	20.53756	0.33980	0	426	2607	16.34062	0.6886	0	111	652	17.024540	0.6204	0	215	2736	7.858187	0.8008	1	1792	2902	61.75052	0.7584	1	2683	2049	76.369735	0.9401	1	0	0.0000000	0.3251	0	69	1401	4.925053	0.7847	1	511	1401	36.47395	0.7992	1	72	2902	2.481048	0.8114	1	4.4335	0.9468	5	3.05790	0.7908	1	0.7584	0.7510	1	3.6605	0.9391	4	11.91030	0.9339	11	3178	2264	1390	1508	3176	47.48111	0.9246	1	172	1804	9.534368	0.8460	1	205	468	43.80342	0.8858	1	622	922	67.46204	0.9192	1	827	1390	59.49640	0.9587	1	364	2076	17.53372	0.8013	1	476	3178	14.977974	0.9390	1	483	15.198238	0.41220	0	539	16.96035	0.2484	0	319	2639	12.087912	0.38790	0	101	565	17.87611	0.6539	0	583	3022	19.291860	0.9349	1	2186	3178	68.78540	0.7658	1	2264	1609	71.0689046	0.9266	1	15	0.6625442	0.7078	0	226	1390	16.258993	0.9567	1	599	1390	43.09353	0.8474	1	20	3178	0.6293266	0.6292	0	4.4696	0.9558	5	2.63730	0.5864	1	0.7658	0.7588	1	4.0677	0.9762	3	11.94040	0.9387	10	Yes	1	4200000	\$4,200,000
34001000500	34	001	000500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3483	1241	1027	1938	3483	55.64169	0.9533	1	124	1630	7.607362	0.5830	0	227	446	50.89686	0.8549	1	478	581	82.27194	0.9799	1	705	1027	68.64654	0.9863	1	733	2077	35.29129	0.9396	1	727	3258	22.31430	0.9149	1	377	10.824002	0.3081	0	1055	30.28998	0.90140	1	268	2401	11.16202	0.3549	0	209	763	27.391874	0.7940	1	911	3077	29.606760	0.9746	1	3036	3483	87.16624	0.8550	1	1241	52	4.190169	0.4505	0	4	0.3223207	0.6567	0	113	1027	11.002921	0.9128	1	422	1027	41.09056	0.8250	1	0	3483	0.000000	0.3512	0	4.3771	0.9379	4	3.33300	0.8766	3	0.8550	0.8467	1	3.1962	0.8026	2	11.76130	0.9229	10	3385	1185	945	1682	3364	50.00000	0.9391	1	72	1577	4.565631	0.4586	0	185	468	39.52991	0.8332	1	362	477	75.89099	0.9703	1	547	945	57.88360	0.9477	1	592	1983	29.85376	0.9422	1	738	3385	21.802068	0.9817	1	240	7.090103	0.05988	0	1129	33.35303	0.9689	1	135	2256	5.984043	0.04817	0	110	717	15.34170	0.5822	0	721	3076	23.439532	0.9569	1	3029	3385	89.48301	0.8727	1	1185	9	0.7594937	0.2382	0	0	0.0000000	0.3216	0	103	945	10.899471	0.9072	1	263	945	27.83069	0.7560	1	0	3385	0.0000000	0.1517	0	4.2693	0.9283	4	2.61605	0.5709	2	0.8727	0.8648	1	2.3747	0.4357	2	10.13275	0.7921	9	Yes	0	0	\$0
34001001100	34	001	001100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2204	1204	1204	1185	2204	53.76588	0.9457	1	219	927	23.624596	0.9830	1	97	172	56.39535	0.9094	1	462	1032	44.76744	0.4746	0	559	1204	46.42857	0.7197	0	346	1440	24.02778	0.8306	1	469	1942	24.15036	0.9360	1	363	16.470054	0.7020	0	578	26.22505	0.74410	0	442	1558	28.36970	0.9675	1	247	396	62.373737	0.9898	1	104	2051	5.070697	0.7260	0	2118	2204	96.09800	0.9204	1	1204	570	47.342193	0.8858	1	0	0.0000000	0.3251	0	14	1204	1.162791	0.4877	0	817	1204	67.85714	0.9413	1	0	2204	0.000000	0.3512	0	4.4150	0.9451	4	4.12940	0.9805	2	0.9204	0.9114	1	2.9911	0.7243	2	12.45590	0.9597	9	1950	1267	1096	1131	1950	58.00000	0.9678	1	66	706	9.348442	0.8395	1	42	101	41.58416	0.8612	1	309	995	31.05528	0.1959	0	351	1096	32.02555	0.4782	0	510	1379	36.98332	0.9763	1	155	1950	7.948718	0.7660	1	392	20.102564	0.69880	0	447	22.92308	0.6712	0	570	1503	37.924152	0.99200	1	143	374	38.23529	0.9167	1	109	1841	5.920695	0.7464	0	1909	1950	97.89744	0.9529	1	1267	479	37.8058406	0.8464	1	0	0.0000000	0.3216	0	33	1096	3.010949	0.6446	0	743	1096	67.79197	0.9414	1	0	1950	0.0000000	0.1517	0	4.0278	0.8848	4	4.02510	0.9798	2	0.9529	0.9442	1	2.9057	0.6869	2	11.91150	0.9365	9	Yes	0	0	\$0

# Join national data to nmtc_awards_pre2010, set count to 0 if no data
svi_national_nmtc_eligible <- 
  left_join(svi_national_nmtc_eligible, nmtc_awards_pre2010, join_by("GEOID_2010_trt" == "GEOID10")) %>%
  mutate(pre10_nmtc_project_cnt = if_else(is.na(pre10_nmtc_project_cnt), 0, pre10_nmtc_project_cnt)) %>%
    mutate(pre10_nmtc_dollars = if_else(is.na(pre10_nmtc_dollars), 0, pre10_nmtc_dollars))%>%
    mutate(pre10_nmtc_dollars_formatted = if_else(is.na(pre10_nmtc_dollars_formatted), "$0", pre10_nmtc_dollars_formatted))

# View table
svi_national_nmtc_eligible %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.57540	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.30190	0	154	730	21.09589	0.09312	0	339	1265	26.79842	0.8392	1	313	2012	15.55666	0.6000	0	204	10.09901	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.8351	1	15	1890	0.7936508	0.40130	0	1243	2020	61.53465	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.780822	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0.0000	0.3640	0	2.70312	0.5665	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.4132	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.40410	0	139	1313	10.58644	0.5601	0	91	1533	5.936073	0.4343	0	284	16.163916	0.5169	0	325	18.49744	0.2851	0	164	1208.000	13.57616	0.4127	0	42	359.0000	11.699164	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757.000	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.4688	0	57	573.000	9.947644	0.7317	0	212	1757	12.0660216	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.9130	0.6862	1	7.83579	0.4802	2	Yes	0	0	\$0
01001020700	01	001	020700	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2664	1254	1139	710	2664	26.65165	0.6328	0	29	1310	2.213741	0.05255	0	134	710	18.87324	0.13890	0	187	429	43.58974	0.47090	0	321	1139	28.18262	0.28130	0	396	1852	21.38229	0.7478	0	345	2878	11.98749	0.4459	0	389	14.60210	0.6417	0	599	22.48499	0.4007	0	510	2168	23.52399	0.8752	1	228	712	32.022472	0.8712	1	0	2480	0.0000000	0.09298	0	694	2664	26.05105	0.5138	0	1254	8	0.6379585	0.2931	0	460	36.6826156	0.9714	1	0	1139	0.000000	0.1238	0	125	1139	10.974539	0.7477	0	0	2664	0.0000	0.3640	0	2.16035	0.4069	0	2.88178	0.6997	2	0.5138	0.5090	0	2.5000	0.4882	1	8.05593	0.5185	3	3562	1313	1248	1370	3528	38.83220	0.8512	1	128	1562	8.194622	0.7935	1	168	844	19.905213	0.44510	0	237	404	58.66337	0.8359	1	405	1248	32.45192	0.60420	0	396	2211	17.91045	0.7857	1	444	3547	12.517620	0.7758	1	355	9.966311	0.1800	0	954	26.78271	0.7923	1	629	2593.000	24.25762	0.8730	1	171	797.0000	21.455458	0.7186	0	0	3211	0.0000000	0.09479	0	1009	3562.000	28.32678	0.4668	0	1313	14	1.0662605	0.3165	0	443	33.7395278	0.9663	1	73	1248	5.8493590	0.8211	1	17	1248.000	1.362180	0.1554	0	112	3562	3.1443010	0.8514	1	3.81040	0.8569	4	2.65869	0.5847	2	0.4668	0.4629	0	3.1107	0.7714	3	10.04659	0.7851	9	Yes	0	0	\$0
01001021100	01	001	021100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3298	1502	1323	860	3298	26.07641	0.6211	0	297	1605	18.504673	0.94340	1	250	1016	24.60630	0.32070	0	74	307	24.10423	0.11920	0	324	1323	24.48980	0.17380	0	710	2231	31.82429	0.8976	1	654	3565	18.34502	0.7018	0	411	12.46210	0.5001	0	738	22.37720	0.3934	0	936	2861	32.71583	0.9807	1	138	825	16.727273	0.5715	0	9	3155	0.2852615	0.25010	0	1979	3298	60.00606	0.7703	1	1502	14	0.9320905	0.3234	0	659	43.8748336	0.9849	1	44	1323	3.325775	0.7062	0	137	1323	10.355253	0.7313	0	0	3298	0.0000	0.3640	0	3.33770	0.7351	2	2.69580	0.6028	1	0.7703	0.7631	1	3.1098	0.7827	1	9.91360	0.7557	5	3499	1825	1462	1760	3499	50.30009	0.9396	1	42	966	4.347826	0.4539	0	426	1274	33.437991	0.85200	1	52	188	27.65957	0.1824	0	478	1462	32.69494	0.61110	0	422	2488	16.96141	0.7638	1	497	3499	14.204058	0.8246	1	853	24.378394	0.8688	1	808	23.09231	0.5829	0	908	2691.100	33.74084	0.9808	1	179	811.6985	22.052524	0.7323	0	8	3248	0.2463054	0.26220	0	1986	3498.713	56.76373	0.7175	0	1825	29	1.5890411	0.3551	0	576	31.5616438	0.9594	1	88	1462	6.0191518	0.8269	1	148	1461.993	10.123166	0.7364	0	38	3499	1.0860246	0.7013	0	3.59300	0.8073	3	3.42700	0.9156	2	0.7175	0.7114	0	3.5791	0.9216	2	11.31660	0.9150	7	Yes	0	0	\$0
01003010200	01	003	010200	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	2612	1220	1074	338	2605	12.97505	0.2907	0	44	1193	3.688181	0.14720	0	172	928	18.53448	0.13090	0	31	146	21.23288	0.09299	0	203	1074	18.90130	0.05657	0	455	1872	24.30556	0.8016	1	456	2730	16.70330	0.6445	0	401	15.35222	0.6847	0	563	21.55436	0.3406	0	410	2038	20.11776	0.7755	1	64	779	8.215661	0.2181	0	0	2510	0.0000000	0.09298	0	329	2612	12.59571	0.3113	0	1220	38	3.1147541	0.4648	0	385	31.5573770	0.9545	1	20	1074	1.862197	0.5509	0	43	1074	4.003724	0.4088	0	0	2612	0.0000	0.3640	0	1.94057	0.3398	1	2.11188	0.2802	1	0.3113	0.3084	0	2.7430	0.6129	1	7.10675	0.3771	3	2928	1312	1176	884	2928	30.19126	0.7334	0	29	1459	1.987663	0.1356	0	71	830	8.554217	0.03726	0	134	346	38.72832	0.3964	0	205	1176	17.43197	0.12010	0	294	2052	14.32749	0.6940	0	219	2925	7.487179	0.5423	0	556	18.989071	0.6705	0	699	23.87295	0.6339	0	489	2226.455	21.96317	0.8122	1	191	783.8820	24.365914	0.7799	1	0	2710	0.0000000	0.09479	0	398	2927.519	13.59513	0.2511	0	1312	13	0.9908537	0.3111	0	400	30.4878049	0.9557	1	6	1176	0.5102041	0.2590	0	81	1176.202	6.886570	0.6115	0	7	2928	0.2390710	0.4961	0	2.22540	0.4183	0	2.99129	0.7634	2	0.2511	0.2490	0	2.6334	0.5496	1	8.10119	0.5207	3	Yes	0	0	\$0
01003010500	01	003	010500	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	4230	1779	1425	498	3443	14.46413	0.3337	0	166	1625	10.215385	0.71790	0	151	1069	14.12535	0.04638	0	196	356	55.05618	0.73830	0	347	1425	24.35088	0.17010	0	707	2945	24.00679	0.7967	1	528	4001	13.19670	0.5005	0	619	14.63357	0.6436	0	790	18.67612	0.1937	0	536	3096	17.31266	0.6572	0	165	920	17.934783	0.6102	0	20	4021	0.4973887	0.32320	0	754	4230	17.82506	0.4023	0	1779	97	5.4525014	0.5525	0	8	0.4496908	0.4600	0	63	1425	4.421053	0.7762	1	90	1425	6.315790	0.5691	0	787	4230	18.6052	0.9649	1	2.51890	0.5121	1	2.42790	0.4539	0	0.4023	0.3986	0	3.3227	0.8628	2	8.67180	0.6054	3	5877	1975	1836	820	5244	15.63692	0.3902	0	90	2583	3.484321	0.3361	0	159	1345	11.821561	0.10530	0	139	491	28.30957	0.1924	0	298	1836	16.23094	0.09053	0	570	4248	13.41808	0.6669	0	353	5247	6.727654	0.4924	0	1109	18.870172	0.6645	0	1144	19.46571	0.3411	0	717	4102.545	17.47696	0.6332	0	103	1286.1180	8.008596	0.2341	0	0	5639	0.0000000	0.09479	0	868	5877.481	14.76823	0.2709	0	1975	26	1.3164557	0.3359	0	45	2.2784810	0.6271	0	9	1836	0.4901961	0.2540	0	116	1835.798	6.318779	0.5811	0	633	5877	10.7708014	0.9507	1	1.97613	0.3410	0	1.96769	0.1961	0	0.2709	0.2686	0	2.7488	0.6077	1	6.96352	0.3406	1	Yes	0	0	\$0
01003010600	01	003	010600	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	3724	1440	1147	1973	3724	52.98067	0.9342	1	142	1439	9.867964	0.69680	0	235	688	34.15698	0.62950	0	187	459	40.74074	0.40290	0	422	1147	36.79163	0.55150	0	497	1876	26.49254	0.8354	1	511	3661	13.95794	0.5334	0	246	6.60580	0.1481	0	1256	33.72718	0.9305	1	496	2522	19.66693	0.7587	1	274	838	32.696897	0.8779	1	32	3479	0.9198045	0.42810	0	2606	3724	69.97852	0.8184	1	1440	21	1.4583333	0.3683	0	321	22.2916667	0.9036	1	97	1147	8.456844	0.8956	1	167	1147	14.559721	0.8209	1	0	3724	0.0000	0.3640	0	3.55130	0.7859	2	3.14330	0.8145	3	0.8184	0.8108	1	3.3524	0.8725	3	10.86540	0.8550	9	4115	1534	1268	1676	3997	41.93145	0.8814	1	294	1809	16.252073	0.9674	1	341	814	41.891892	0.94320	1	204	454	44.93392	0.5438	0	545	1268	42.98107	0.83620	1	624	2425	25.73196	0.9002	1	994	4115	24.155529	0.9602	1	642	15.601458	0.4841	0	1126	27.36331	0.8175	1	568	2989.000	19.00301	0.7045	0	212	715.0000	29.650350	0.8592	1	56	3825	1.4640523	0.53120	0	2715	4115.000	65.97813	0.7732	1	1534	0	0.0000000	0.1079	0	529	34.4850065	0.9685	1	101	1268	7.9652997	0.8795	1	89	1268.000	7.018927	0.6184	0	17	4115	0.4131227	0.5707	0	4.54540	0.9754	5	3.39650	0.9081	2	0.7732	0.7667	1	3.1450	0.7858	2	11.86010	0.9520	10	Yes	0	0	\$0

# Find count of NMTC projects after 2010
# Remove all tracts that do not have SVI flag counts for 2010
# Remove all tracts that do not have SVI flag counts for 2020
# Remove all tracts that had an NMTC project before 2010
svi_divisional_nmtc <- 
  left_join(svi_divisional_nmtc_eligible, nmtc_awards_post2010, join_by("GEOID_2010_trt" == "GEOID10")) %>%
  mutate(post10_nmtc_project_cnt = if_else(is.na(post10_nmtc_project_cnt), 0, post10_nmtc_project_cnt)) %>%
  mutate(post10_nmtc_dollars = if_else(is.na(post10_nmtc_dollars), 0, post10_nmtc_dollars))%>%
  mutate(post10_nmtc_dollars_formatted = if_else(is.na(post10_nmtc_dollars_formatted), "$0", post10_nmtc_dollars_formatted)) %>%
  mutate(nmtc_flag = if_else(post10_nmtc_project_cnt > 0, 1, 0)) %>% 
  filter(!is.na(F_TOTAL_10)) %>% 
  filter(!is.na(F_TOTAL_20)) %>% 
  filter(pre10_nmtc_project_cnt < 1)

svi_divisional_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted	post10_nmtc_project_cnt	post10_nmtc_dollars	post10_nmtc_dollars_formatted	nmtc_flag
34001000100	34	001	000100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2907	1088	983	1127	2907	38.76849	0.8482	1	144	1433	10.048849	0.7544	1	280	435	64.36782	0.9529	1	204	548	37.22628	0.2998	0	484	983	49.23703	0.7813	1	468	1759	26.60603	0.8634	1	532	2543	20.92017	0.8978	1	250	8.599931	0.1777	0	944	32.47334	0.94170	1	186	1851	10.04862	0.2706	0	266	678	39.233038	0.8981	1	177	2611	6.779012	0.7778	1	1928	2907	66.32267	0.7743	1	1088	113	10.386029	0.6229	0	9	0.8272059	0.7223	0	80	983	8.138352	0.8657	1	265	983	26.95829	0.7354	0	0	2907	0	0.3512	0	4.1451	0.8935	5	3.06590	0.7944	3	0.7743	0.7667	1	3.2975	0.8414	1	11.28280	0.8862	10	2157	941	784	1182	2157	54.79833	0.9571	1	242	1058	22.873346	0.9922	1	215	342	62.86550	0.9780	1	316	442	71.49321	0.9481	1	531	784	67.72959	0.9893	1	396	1274	31.08320	0.9497	1	266	2157	12.331943	0.9041	1	185	8.576727	0.09430	0	552	25.59110	0.8128	1	297	1605	18.504673	0.74880	0	83	510	16.27451	0.6090	0	251	2020	12.425743	0.87100	1	1852	2157	85.85999	0.8476	1	941	118	12.5398512	0.6385	0	0	0.00000	0.3216	0	67	784	8.545918	0.8657	1	212	784	27.04082	0.7502	1	0	2157	0.0000000	0.1517	0	4.7924	0.9850	5	3.13590	0.8217	2	0.8476	0.8400	1	2.7277	0.6085	2	11.50360	0.9104	10	Yes	0	0	\$0	0	0	\$0	0
34001000200	34	001	000200	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3189	2217	1473	519	3189	16.27469	0.4806	0	109	1558	6.996149	0.5179	0	573	955	60.00000	0.9323	1	199	518	38.41699	0.3261	0	772	1473	52.41005	0.8418	1	405	2579	15.70376	0.6491	0	484	3547	13.64533	0.7154	0	847	26.560050	0.9629	1	436	13.67200	0.08181	0	608	3005	20.23295	0.8466	1	42	857	4.900817	0.1204	0	422	3072	13.736979	0.8799	1	1792	3189	56.19316	0.7390	0	2217	901	40.640505	0.8693	1	0	0.0000000	0.3251	0	48	1473	3.258656	0.7064	0	250	1473	16.97217	0.6444	0	0	3189	0	0.3512	0	3.2048	0.6963	1	2.89161	0.7231	3	0.7390	0.7317	0	2.8964	0.6887	1	9.73181	0.7340	5	3510	2046	1353	1021	3510	29.08832	0.7682	1	121	1852	6.533477	0.6717	0	343	696	49.28161	0.9273	1	416	657	63.31811	0.8696	1	759	1353	56.09756	0.9321	1	553	2338	23.65269	0.8871	1	354	3510	10.085470	0.8530	1	643	18.319088	0.60310	0	1002	28.54701	0.9055	1	450	2508	17.942584	0.72330	0	237	786	30.15267	0.8539	1	534	3375	15.822222	0.90620	1	2534	3510	72.19373	0.7818	1	2046	906	44.2815249	0.8690	1	0	0.00000	0.3216	0	119	1353	8.795270	0.8711	1	324	1353	23.94678	0.7255	0	0	3510	0.0000000	0.1517	0	4.1121	0.9003	4	3.99200	0.9781	3	0.7818	0.7747	1	2.9389	0.7011	2	11.82480	0.9310	10	Yes	0	0	\$0	0	0	\$0	0
34001000300	34	001	000300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3997	1823	1357	1401	3968	35.30746	0.8164	1	382	2238	17.068811	0.9376	1	176	329	53.49544	0.8855	1	604	1028	58.75486	0.7947	1	780	1357	57.47973	0.9165	1	920	2677	34.36683	0.9346	1	1351	4149	32.56206	0.9811	1	314	7.855892	0.1437	0	937	23.44258	0.55900	0	319	3054	10.44532	0.3000	0	187	782	23.913044	0.7498	0	1080	3671	29.419777	0.9742	1	3357	3997	83.98799	0.8419	1	1823	363	19.912233	0.7535	1	0	0.0000000	0.3251	0	150	1357	11.053795	0.9136	1	651	1357	47.97347	0.8585	1	0	3997	0	0.3512	0	4.5862	0.9691	5	2.72670	0.6360	1	0.8419	0.8336	1	3.2019	0.8054	3	11.35670	0.8920	10	3801	1640	1226	1857	3801	48.85556	0.9333	1	226	1800	12.555556	0.9267	1	111	280	39.64286	0.8339	1	608	946	64.27061	0.8842	1	719	1226	58.64600	0.9528	1	650	2275	28.57143	0.9337	1	1027	3801	27.019206	0.9914	1	380	9.997369	0.14040	0	1223	32.17574	0.9607	1	219	2578	8.494957	0.15680	0	268	909	29.48295	0.8456	1	940	3400	27.647059	0.97280	1	3318	3801	87.29282	0.8579	1	1640	262	15.9756098	0.6917	0	0	0.00000	0.3216	0	124	1226	10.114192	0.8955	1	477	1226	38.90701	0.8258	1	0	3801	0.0000000	0.1517	0	4.7379	0.9829	5	3.07630	0.8013	3	0.8579	0.8501	1	2.8863	0.6781	2	11.55840	0.9150	11	Yes	0	0	\$0	0	0	\$0	0
34001000500	34	001	000500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3483	1241	1027	1938	3483	55.64169	0.9533	1	124	1630	7.607362	0.5830	0	227	446	50.89686	0.8549	1	478	581	82.27194	0.9799	1	705	1027	68.64654	0.9863	1	733	2077	35.29129	0.9396	1	727	3258	22.31430	0.9149	1	377	10.824002	0.3081	0	1055	30.28998	0.90140	1	268	2401	11.16202	0.3549	0	209	763	27.391874	0.7940	1	911	3077	29.606760	0.9746	1	3036	3483	87.16624	0.8550	1	1241	52	4.190169	0.4505	0	4	0.3223207	0.6567	0	113	1027	11.002921	0.9128	1	422	1027	41.09056	0.8250	1	0	3483	0	0.3512	0	4.3771	0.9379	4	3.33300	0.8766	3	0.8550	0.8467	1	3.1962	0.8026	2	11.76130	0.9229	10	3385	1185	945	1682	3364	50.00000	0.9391	1	72	1577	4.565631	0.4586	0	185	468	39.52991	0.8332	1	362	477	75.89099	0.9703	1	547	945	57.88360	0.9477	1	592	1983	29.85376	0.9422	1	738	3385	21.802068	0.9817	1	240	7.090103	0.05988	0	1129	33.35303	0.9689	1	135	2256	5.984043	0.04817	0	110	717	15.34170	0.5822	0	721	3076	23.439532	0.95690	1	3029	3385	89.48301	0.8727	1	1185	9	0.7594937	0.2382	0	0	0.00000	0.3216	0	103	945	10.899471	0.9072	1	263	945	27.83069	0.7560	1	0	3385	0.0000000	0.1517	0	4.2693	0.9283	4	2.61605	0.5709	2	0.8727	0.8648	1	2.3747	0.4357	2	10.13275	0.7921	9	Yes	0	0	\$0	0	0	\$0	0
34001001100	34	001	001100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2204	1204	1204	1185	2204	53.76588	0.9457	1	219	927	23.624596	0.9830	1	97	172	56.39535	0.9094	1	462	1032	44.76744	0.4746	0	559	1204	46.42857	0.7197	0	346	1440	24.02778	0.8306	1	469	1942	24.15036	0.9360	1	363	16.470054	0.7020	0	578	26.22505	0.74410	0	442	1558	28.36970	0.9675	1	247	396	62.373737	0.9898	1	104	2051	5.070697	0.7260	0	2118	2204	96.09800	0.9204	1	1204	570	47.342193	0.8858	1	0	0.0000000	0.3251	0	14	1204	1.162791	0.4877	0	817	1204	67.85714	0.9413	1	0	2204	0	0.3512	0	4.4150	0.9451	4	4.12940	0.9805	2	0.9204	0.9114	1	2.9911	0.7243	2	12.45590	0.9597	9	1950	1267	1096	1131	1950	58.00000	0.9678	1	66	706	9.348442	0.8395	1	42	101	41.58416	0.8612	1	309	995	31.05528	0.1959	0	351	1096	32.02555	0.4782	0	510	1379	36.98332	0.9763	1	155	1950	7.948718	0.7660	1	392	20.102564	0.69880	0	447	22.92308	0.6712	0	570	1503	37.924152	0.99200	1	143	374	38.23529	0.9167	1	109	1841	5.920695	0.74640	0	1909	1950	97.89744	0.9529	1	1267	479	37.8058406	0.8464	1	0	0.00000	0.3216	0	33	1096	3.010949	0.6446	0	743	1096	67.79197	0.9414	1	0	1950	0.0000000	0.1517	0	4.0278	0.8848	4	4.02510	0.9798	2	0.9529	0.9442	1	2.9057	0.6869	2	11.91150	0.9365	9	Yes	0	0	\$0	0	0	\$0	0
34001001300	34	001	001300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2153	1026	857	695	2153	32.28054	0.7840	1	266	1112	23.920863	0.9840	1	168	432	38.88889	0.6425	0	271	425	63.76471	0.8714	1	439	857	51.22520	0.8184	1	210	1471	14.27600	0.5989	0	463	2215	20.90293	0.8974	1	334	15.513237	0.6436	0	539	25.03484	0.66990	0	222	1687	13.15945	0.4984	0	265	608	43.585526	0.9249	1	92	1905	4.829396	0.7187	0	1993	2153	92.56851	0.8890	1	1026	147	14.327485	0.6885	0	0	0.0000000	0.3251	0	20	857	2.333722	0.6326	0	142	857	16.56943	0.6382	0	0	2153	0	0.3512	0	4.0827	0.8798	4	3.45550	0.9039	1	0.8890	0.8804	1	2.6356	0.5687	0	11.06280	0.8673	6	1632	917	770	591	1632	36.21324	0.8455	1	203	854	23.770492	0.9928	1	164	291	56.35739	0.9604	1	364	479	75.99165	0.9710	1	528	770	68.57143	0.9914	1	150	1056	14.20455	0.7232	0	97	1632	5.943627	0.6352	0	301	18.443628	0.60940	0	271	16.60539	0.2292	0	314	1361	23.071271	0.88960	1	148	410	36.09756	0.9025	1	0	1585	0.000000	0.06953	0	1512	1632	92.64706	0.8931	1	917	246	26.8266085	0.7912	1	16	1.74482	0.7855	1	0	770	0.000000	0.1194	0	219	770	28.44156	0.7606	1	14	1632	0.8578431	0.6722	0	4.1881	0.9131	3	2.70023	0.6211	2	0.8931	0.8850	1	3.1289	0.7740	3	10.91033	0.8638	9	Yes	0	0	\$0	0	0	\$0	0

# Find count of NMTC projects after 2010
# Remove all tracts that do not have SVI flag counts for 2010
# Remove all tracts that do not have SVI flag counts for 2020
# Remove all tracts that had an NMTC project before 2010
svi_national_nmtc <- 
  left_join(svi_national_nmtc_eligible, nmtc_awards_post2010, join_by("GEOID_2010_trt" == "GEOID10")) %>%
  mutate(post10_nmtc_project_cnt = if_else(is.na(post10_nmtc_project_cnt), 0, post10_nmtc_project_cnt)) %>%
  mutate(post10_nmtc_dollars = if_else(is.na(post10_nmtc_dollars), 0, post10_nmtc_dollars))%>%
  mutate(post10_nmtc_dollars_formatted = if_else(is.na(post10_nmtc_dollars_formatted), "$0", post10_nmtc_dollars_formatted)) %>%
  mutate(nmtc_flag = if_else(post10_nmtc_project_cnt > 0, 1, 0)) %>% 
  filter(!is.na(F_TOTAL_10)) %>% 
  filter(!is.na(F_TOTAL_20)) %>% 
  filter(pre10_nmtc_project_cnt < 1)

svi_national_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted	post10_nmtc_project_cnt	post10_nmtc_dollars	post10_nmtc_dollars_formatted	nmtc_flag
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.57540	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.30190	0	154	730	21.09589	0.09312	0	339	1265	26.79842	0.8392	1	313	2012	15.55666	0.6000	0	204	10.09901	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.8351	1	15	1890	0.7936508	0.40130	0	1243	2020	61.53465	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.780822	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0.0000	0.3640	0	2.70312	0.5665	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.4132	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.40410	0	139	1313	10.58644	0.5601	0	91	1533	5.936073	0.4343	0	284	16.163916	0.5169	0	325	18.49744	0.2851	0	164	1208.000	13.57616	0.4127	0	42	359.0000	11.699164	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757.000	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.4688	0	57	573.000	9.947644	0.7317	0	212	1757	12.0660216	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.9130	0.6862	1	7.83579	0.4802	2	Yes	0	0	\$0	0	0	\$0	0
01001020700	01	001	020700	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2664	1254	1139	710	2664	26.65165	0.6328	0	29	1310	2.213741	0.05255	0	134	710	18.87324	0.13890	0	187	429	43.58974	0.47090	0	321	1139	28.18262	0.28130	0	396	1852	21.38229	0.7478	0	345	2878	11.98749	0.4459	0	389	14.60210	0.6417	0	599	22.48499	0.4007	0	510	2168	23.52399	0.8752	1	228	712	32.022472	0.8712	1	0	2480	0.0000000	0.09298	0	694	2664	26.05105	0.5138	0	1254	8	0.6379585	0.2931	0	460	36.6826156	0.9714	1	0	1139	0.000000	0.1238	0	125	1139	10.974539	0.7477	0	0	2664	0.0000	0.3640	0	2.16035	0.4069	0	2.88178	0.6997	2	0.5138	0.5090	0	2.5000	0.4882	1	8.05593	0.5185	3	3562	1313	1248	1370	3528	38.83220	0.8512	1	128	1562	8.194622	0.7935	1	168	844	19.905213	0.44510	0	237	404	58.66337	0.8359	1	405	1248	32.45192	0.60420	0	396	2211	17.91045	0.7857	1	444	3547	12.517620	0.7758	1	355	9.966311	0.1800	0	954	26.78271	0.7923	1	629	2593.000	24.25762	0.8730	1	171	797.0000	21.455458	0.7186	0	0	3211	0.0000000	0.09479	0	1009	3562.000	28.32678	0.4668	0	1313	14	1.0662605	0.3165	0	443	33.7395278	0.9663	1	73	1248	5.8493590	0.8211	1	17	1248.000	1.362180	0.1554	0	112	3562	3.1443010	0.8514	1	3.81040	0.8569	4	2.65869	0.5847	2	0.4668	0.4629	0	3.1107	0.7714	3	10.04659	0.7851	9	Yes	0	0	\$0	0	0	\$0	0
01001021100	01	001	021100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3298	1502	1323	860	3298	26.07641	0.6211	0	297	1605	18.504673	0.94340	1	250	1016	24.60630	0.32070	0	74	307	24.10423	0.11920	0	324	1323	24.48980	0.17380	0	710	2231	31.82429	0.8976	1	654	3565	18.34502	0.7018	0	411	12.46210	0.5001	0	738	22.37720	0.3934	0	936	2861	32.71583	0.9807	1	138	825	16.727273	0.5715	0	9	3155	0.2852615	0.25010	0	1979	3298	60.00606	0.7703	1	1502	14	0.9320905	0.3234	0	659	43.8748336	0.9849	1	44	1323	3.325775	0.7062	0	137	1323	10.355253	0.7313	0	0	3298	0.0000	0.3640	0	3.33770	0.7351	2	2.69580	0.6028	1	0.7703	0.7631	1	3.1098	0.7827	1	9.91360	0.7557	5	3499	1825	1462	1760	3499	50.30009	0.9396	1	42	966	4.347826	0.4539	0	426	1274	33.437991	0.85200	1	52	188	27.65957	0.1824	0	478	1462	32.69494	0.61110	0	422	2488	16.96141	0.7638	1	497	3499	14.204058	0.8246	1	853	24.378394	0.8688	1	808	23.09231	0.5829	0	908	2691.100	33.74084	0.9808	1	179	811.6985	22.052524	0.7323	0	8	3248	0.2463054	0.26220	0	1986	3498.713	56.76373	0.7175	0	1825	29	1.5890411	0.3551	0	576	31.5616438	0.9594	1	88	1462	6.0191518	0.8269	1	148	1461.993	10.123166	0.7364	0	38	3499	1.0860246	0.7013	0	3.59300	0.8073	3	3.42700	0.9156	2	0.7175	0.7114	0	3.5791	0.9216	2	11.31660	0.9150	7	Yes	0	0	\$0	0	0	\$0	0
01003010200	01	003	010200	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	2612	1220	1074	338	2605	12.97505	0.2907	0	44	1193	3.688181	0.14720	0	172	928	18.53448	0.13090	0	31	146	21.23288	0.09299	0	203	1074	18.90130	0.05657	0	455	1872	24.30556	0.8016	1	456	2730	16.70330	0.6445	0	401	15.35222	0.6847	0	563	21.55436	0.3406	0	410	2038	20.11776	0.7755	1	64	779	8.215661	0.2181	0	0	2510	0.0000000	0.09298	0	329	2612	12.59571	0.3113	0	1220	38	3.1147541	0.4648	0	385	31.5573770	0.9545	1	20	1074	1.862197	0.5509	0	43	1074	4.003724	0.4088	0	0	2612	0.0000	0.3640	0	1.94057	0.3398	1	2.11188	0.2802	1	0.3113	0.3084	0	2.7430	0.6129	1	7.10675	0.3771	3	2928	1312	1176	884	2928	30.19126	0.7334	0	29	1459	1.987663	0.1356	0	71	830	8.554217	0.03726	0	134	346	38.72832	0.3964	0	205	1176	17.43197	0.12010	0	294	2052	14.32749	0.6940	0	219	2925	7.487179	0.5423	0	556	18.989071	0.6705	0	699	23.87295	0.6339	0	489	2226.455	21.96317	0.8122	1	191	783.8820	24.365914	0.7799	1	0	2710	0.0000000	0.09479	0	398	2927.519	13.59513	0.2511	0	1312	13	0.9908537	0.3111	0	400	30.4878049	0.9557	1	6	1176	0.5102041	0.2590	0	81	1176.202	6.886570	0.6115	0	7	2928	0.2390710	0.4961	0	2.22540	0.4183	0	2.99129	0.7634	2	0.2511	0.2490	0	2.6334	0.5496	1	8.10119	0.5207	3	Yes	0	0	\$0	1	408000	\$408,000	1
01003010500	01	003	010500	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	4230	1779	1425	498	3443	14.46413	0.3337	0	166	1625	10.215385	0.71790	0	151	1069	14.12535	0.04638	0	196	356	55.05618	0.73830	0	347	1425	24.35088	0.17010	0	707	2945	24.00679	0.7967	1	528	4001	13.19670	0.5005	0	619	14.63357	0.6436	0	790	18.67612	0.1937	0	536	3096	17.31266	0.6572	0	165	920	17.934783	0.6102	0	20	4021	0.4973887	0.32320	0	754	4230	17.82506	0.4023	0	1779	97	5.4525014	0.5525	0	8	0.4496908	0.4600	0	63	1425	4.421053	0.7762	1	90	1425	6.315790	0.5691	0	787	4230	18.6052	0.9649	1	2.51890	0.5121	1	2.42790	0.4539	0	0.4023	0.3986	0	3.3227	0.8628	2	8.67180	0.6054	3	5877	1975	1836	820	5244	15.63692	0.3902	0	90	2583	3.484321	0.3361	0	159	1345	11.821561	0.10530	0	139	491	28.30957	0.1924	0	298	1836	16.23094	0.09053	0	570	4248	13.41808	0.6669	0	353	5247	6.727654	0.4924	0	1109	18.870172	0.6645	0	1144	19.46571	0.3411	0	717	4102.545	17.47696	0.6332	0	103	1286.1180	8.008596	0.2341	0	0	5639	0.0000000	0.09479	0	868	5877.481	14.76823	0.2709	0	1975	26	1.3164557	0.3359	0	45	2.2784810	0.6271	0	9	1836	0.4901961	0.2540	0	116	1835.798	6.318779	0.5811	0	633	5877	10.7708014	0.9507	1	1.97613	0.3410	0	1.96769	0.1961	0	0.2709	0.2686	0	2.7488	0.6077	1	6.96352	0.3406	1	Yes	0	0	\$0	0	0	\$0	0
01003010600	01	003	010600	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	3724	1440	1147	1973	3724	52.98067	0.9342	1	142	1439	9.867964	0.69680	0	235	688	34.15698	0.62950	0	187	459	40.74074	0.40290	0	422	1147	36.79163	0.55150	0	497	1876	26.49254	0.8354	1	511	3661	13.95794	0.5334	0	246	6.60580	0.1481	0	1256	33.72718	0.9305	1	496	2522	19.66693	0.7587	1	274	838	32.696897	0.8779	1	32	3479	0.9198045	0.42810	0	2606	3724	69.97852	0.8184	1	1440	21	1.4583333	0.3683	0	321	22.2916667	0.9036	1	97	1147	8.456844	0.8956	1	167	1147	14.559721	0.8209	1	0	3724	0.0000	0.3640	0	3.55130	0.7859	2	3.14330	0.8145	3	0.8184	0.8108	1	3.3524	0.8725	3	10.86540	0.8550	9	4115	1534	1268	1676	3997	41.93145	0.8814	1	294	1809	16.252073	0.9674	1	341	814	41.891892	0.94320	1	204	454	44.93392	0.5438	0	545	1268	42.98107	0.83620	1	624	2425	25.73196	0.9002	1	994	4115	24.155529	0.9602	1	642	15.601458	0.4841	0	1126	27.36331	0.8175	1	568	2989.000	19.00301	0.7045	0	212	715.0000	29.650350	0.8592	1	56	3825	1.4640523	0.53120	0	2715	4115.000	65.97813	0.7732	1	1534	0	0.0000000	0.1079	0	529	34.4850065	0.9685	1	101	1268	7.9652997	0.8795	1	89	1268.000	7.018927	0.6184	0	17	4115	0.4131227	0.5707	0	4.54540	0.9754	5	3.39650	0.9081	2	0.7732	0.7667	1	3.1450	0.7858	2	11.86010	0.9520	10	Yes	0	0	\$0	1	8000000	\$8,000,000	1

svi_national_nmtc_county_sum <- summarize_county_nmtc(svi_national_nmtc)

svi_national_nmtc_county_sum %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted
AK	Aleutians East Borough	Pacific Division	1	1	15762500	\$15,762,500
AK	Aleutians West Census Area	Pacific Division	0	1	0	\$0
AK	Anchorage Municipality	Pacific Division	1	13	9800000	\$9,800,000
AK	Bethel Census Area	Pacific Division	0	1	0	\$0
AK	Fairbanks North Star Borough	Pacific Division	0	4	0	\$0
AK	Hoonah-Angoon Census Area	Pacific Division	0	1	0	\$0

svi_divisional_nmtc_county_sum <- summarize_county_nmtc(svi_divisional_nmtc)
svi_divisional_nmtc_county_sum %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted
NJ	Atlantic County	Middle Atlantic Division	0	29	0	\$0
NJ	Bergen County	Middle Atlantic Division	1	30	10000000	\$10,000,000
NJ	Burlington County	Middle Atlantic Division	0	20	0	\$0
NJ	Camden County	Middle Atlantic Division	5	47	79664200	\$79,664,200
NJ	Cape May County	Middle Atlantic Division	0	12	0	\$0
NJ	Cumberland County	Middle Atlantic Division	2	21	33187593	\$33,187,593

# Create data frame of NMTC eligible tracts 2010 nationally
svi_national_nmtc10 <- svi_national_nmtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_10, E_TOTPOP_10) %>% rename("F_TOTAL" = "F_TOTAL_10")

# Count national-level SVI flags for 2010, create unified fips column
svi_2010_national_county_flags_nmtc <- flag_summarize(svi_national_nmtc10, "E_TOTPOP_10") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Add suffix to flag columns 2010
colnames(svi_2010_national_county_flags_nmtc)[11:15] <- paste0(colnames(svi_2010_national_county_flags_nmtc)[11:15], 10)

# Create data frame of NMTC eligible tracts 2020 nationally
svi_national_nmtc20 <- svi_national_nmtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_20, E_TOTPOP_20) %>% rename("F_TOTAL" = "F_TOTAL_20")

# Count national-level SVI flags for 2020, create unified fips column
svi_2020_national_county_flags_nmtc <- flag_summarize(svi_national_nmtc20, "E_TOTPOP_20") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Identify needed columns for 2020, add suffix
colnames(svi_2020_national_county_flags_nmtc)[11:15] <- paste0(colnames(svi_2020_national_county_flags_nmtc)[11:15], "20")

# Filter to needed columns for 2020 to avoid duplicate column column names
svi_2020_national_county_flags_join_nmtc <- svi_2020_national_county_flags_nmtc %>% ungroup() %>% select("fips_county_st", all_of(colnames(svi_2020_national_county_flags_nmtc)[11:15]))
 
# Join 2010 and 2020 data
svi_national_county_flags_nmtc <- left_join(svi_2010_national_county_flags_nmtc, svi_2020_national_county_flags_join_nmtc, join_by("fips_county_st" == "fips_county_st")) 

svi_national_county_flags_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
01001	01	001	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	14	7982	0.0017539	0.6	0.8	18	8818	0.0020413	0.6	1.0
01003	01	003	AL	Alabama	Baldwin County	1	South Region	6	East South Central Division	34	38458	0.0008841	0.8	0.4	34	46255	0.0007351	0.8	0.2
01005	01	005	AL	Alabama	Barbour County	1	South Region	6	East South Central Division	43	21287	0.0020200	0.8	1.0	44	18811	0.0023391	0.8	1.0
01007	01	007	AL	Alabama	Bibb County	1	South Region	6	East South Central Division	11	17570	0.0006261	0.4	0.2	16	17663	0.0009058	0.6	0.4
01009	01	009	AL	Alabama	Blount County	1	South Region	6	East South Central Division	12	16995	0.0007061	0.4	0.2	8	16546	0.0004835	0.4	0.2
01011	01	011	AL	Alabama	Bullock County	1	South Region	6	East South Central Division	21	10923	0.0019225	0.6	1.0	18	10173	0.0017694	0.6	0.8

svi_national_county_nmtc <- left_join(svi_national_nmtc_county_sum,
                                      svi_national_county_flags_nmtc,
                                    join_by("State" == "state", "County" == "county",
                                            "Division" == "division"))

svi_national_county_nmtc$post10_nmtc_project_cnt[is.na(svi_national_county_nmtc$post10_nmtc_project_cnt)] <- 0

svi_national_county_nmtc$county_name <- paste0(svi_national_county_nmtc$County, ", ", svi_national_county_nmtc$State)

svi_national_county_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name
AK	Aleutians East Borough	Pacific Division	1	1	15762500	\$15,762,500	02013	02	013	Alaska	1	West Region	9	8	3703	0.0021604	0.4	1.0	5	3389	0.0014754	0.2	0.8	Aleutians East Borough, AK
AK	Aleutians West Census Area	Pacific Division	0	1	0	\$0	02016	02	016	Alaska	1	West Region	9	6	1774	0.0033822	0.2	1.0	6	950	0.0063158	0.2	1.0	Aleutians West Census Area, AK
AK	Anchorage Municipality	Pacific Division	1	13	9800000	\$9,800,000	02020	02	020	Alaska	1	West Region	9	72	64432	0.0011175	1.0	0.4	87	69679	0.0012486	1.0	0.6	Anchorage Municipality, AK
AK	Bethel Census Area	Pacific Division	0	1	0	\$0	02050	02	050	Alaska	1	West Region	9	8	1386	0.0057720	0.4	1.0	10	1404	0.0071225	0.4	1.0	Bethel Census Area, AK
AK	Fairbanks North Star Borough	Pacific Division	0	4	0	\$0	02090	02	090	Alaska	1	West Region	9	13	17281	0.0007523	0.4	0.2	17	20094	0.0008460	0.6	0.4	Fairbanks North Star Borough, AK
AK	Hoonah-Angoon Census Area	Pacific Division	0	1	0	\$0	02105	02	105	Alaska	1	West Region	9	4	1888	0.0021186	0.2	1.0	5	2073	0.0024120	0.2	1.0	Hoonah-Angoon Census Area, AK

# Create data frame of NMTC eligible tracts 2020 nationally
svi_divisional_nmtc10 <- svi_divisional_nmtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_10, E_TOTPOP_10) %>% rename("F_TOTAL" = "F_TOTAL_10")

# Count divisional-level SVI flags for 2010, create unified fips column
svi_2010_divisional_county_flags_nmtc <- flag_summarize(svi_divisional_nmtc10, "E_TOTPOP_10") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Add suffix to flag columns 2010
colnames(svi_2010_divisional_county_flags_nmtc)[11:15] <- paste0(colnames(svi_2010_divisional_county_flags_nmtc)[11:15], "10")

# Create data frame of NMTC eligible tracts 2020 nationally
svi_divisional_nmtc20 <- svi_divisional_nmtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_20, E_TOTPOP_20) %>% rename("F_TOTAL" = "F_TOTAL_20")

# Count divisional-level SVI flags for 2020, create unified fips column
svi_2020_divisional_county_flags_nmtc <- flag_summarize(svi_divisional_nmtc20, "E_TOTPOP_20") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Identify needed columns for 2020
colnames(svi_2020_divisional_county_flags_nmtc)[11:15] <- paste0(colnames(svi_2020_divisional_county_flags_nmtc)[11:15], "20")

# Filter to needed columns for 2020 to avoid duplicate column column names
svi_2020_divisional_county_flags_join_nmtc <- svi_2020_divisional_county_flags_nmtc %>% ungroup() %>% select("fips_county_st", all_of(colnames(svi_2020_divisional_county_flags_nmtc)[11:15]))
 
# Join 2010 and 2020 data
svi_divisional_county_flags_nmtc <- left_join(svi_2010_divisional_county_flags_nmtc, svi_2020_divisional_county_flags_join_nmtc, join_by("fips_county_st" == "fips_county_st")) 

svi_divisional_county_flags_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
34001	34	001	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	202	111752	0.0018076	1.0	1.0	220	108778	0.0020225	1.0	1.0
34003	34	003	NJ	New Jersey	Bergen County	1	Northeast Region	2	Middle Atlantic Division	146	143973	0.0010141	1.0	0.4	165	154365	0.0010689	1.0	0.4
34005	34	005	NJ	New Jersey	Burlington County	1	Northeast Region	2	Middle Atlantic Division	84	62519	0.0013436	0.8	0.6	86	61250	0.0014041	0.8	0.6
34007	34	007	NJ	New Jersey	Camden County	1	Northeast Region	2	Middle Atlantic Division	332	183630	0.0018080	1.0	1.0	315	180659	0.0017436	1.0	0.8
34009	34	009	NJ	New Jersey	Cape May County	1	Northeast Region	2	Middle Atlantic Division	59	39917	0.0014781	0.8	0.8	47	39348	0.0011945	0.6	0.6
34011	34	011	NJ	New Jersey	Cumberland County	1	Northeast Region	2	Middle Atlantic Division	138	101151	0.0013643	0.8	0.6	135	97989	0.0013777	0.8	0.6

svi_divisional_county_nmtc <- left_join(svi_divisional_nmtc_county_sum, 
                                        svi_divisional_county_flags_nmtc,
                                    join_by("State" == "state", "County" == "county",
                                            "Division" == "division"))

svi_divisional_county_nmtc$post10_nmtc_project_cnt[is.na(svi_divisional_county_nmtc $post10_nmtc_project_cnt)] <- 0

svi_divisional_county_nmtc$county_name <- paste0(svi_divisional_county_nmtc$County, ", ", svi_divisional_county_nmtc$State)

svi_divisional_county_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name
NJ	Atlantic County	Middle Atlantic Division	0	29	0	\$0	34001	34	001	New Jersey	1	Northeast Region	2	202	111752	0.0018076	1.0	1.0	220	108778	0.0020225	1.0	1.0	Atlantic County, NJ
NJ	Bergen County	Middle Atlantic Division	1	30	10000000	\$10,000,000	34003	34	003	New Jersey	1	Northeast Region	2	146	143973	0.0010141	1.0	0.4	165	154365	0.0010689	1.0	0.4	Bergen County, NJ
NJ	Burlington County	Middle Atlantic Division	0	20	0	\$0	34005	34	005	New Jersey	1	Northeast Region	2	84	62519	0.0013436	0.8	0.6	86	61250	0.0014041	0.8	0.6	Burlington County, NJ
NJ	Camden County	Middle Atlantic Division	5	47	79664200	\$79,664,200	34007	34	007	New Jersey	1	Northeast Region	2	332	183630	0.0018080	1.0	1.0	315	180659	0.0017436	1.0	0.8	Camden County, NJ
NJ	Cape May County	Middle Atlantic Division	0	12	0	\$0	34009	34	009	New Jersey	1	Northeast Region	2	59	39917	0.0014781	0.8	0.8	47	39348	0.0011945	0.6	0.6	Cape May County, NJ
NJ	Cumberland County	Middle Atlantic Division	2	21	33187593	\$33,187,593	34011	34	011	New Jersey	1	Northeast Region	2	138	101151	0.0013643	0.8	0.6	135	97989	0.0013777	0.8	0.6	Cumberland County, NJ

LIHTC Data Wrangling

lihtc_eligible_flag <- lihtc_eligible %>% 
  select("fips", "state", "county", "stcnty", "tract", "metro", "cbsa", "qct_2010") %>% 
  rename("GEOID10" = "fips") %>% 
  mutate(lihtc_eligibility = if_else(qct_2010 == 1, "Yes", "No")) %>% 
  filter(tolower(lihtc_eligibility) == "yes") %>% 
  select(GEOID10, lihtc_eligibility)

lihtc_eligible_flag %>% head() 

## # A tibble: 6 × 2
##   GEOID10     lihtc_eligibility
##   <chr>       <chr>            
## 1 01003010600 Yes              
## 2 01005950200 Yes              
## 3 01005950300 Yes              
## 4 01005950400 Yes              
## 5 01005950600 Yes              
## 6 01005950700 Yes

lihtc_projects10 <- lihtc_projects %>% 
  filter(yr_alloc < 8000) %>% 
  filter(yr_alloc <= 2010) %>% 
  count(fips2010) %>% 
  rename("pre10_lihtc_project_cnt" = "n")

lihtc_projects10 %>% head() 

##      fips2010 pre10_lihtc_project_cnt
## 1 01001020300                       2
## 2 01001020500                       5
## 3 01001021100                       1
## 4 01003010200                       1
## 5 01003010600                       1
## 6 01003010703                       1

lihtc_dollars10 <- lihtc_projects %>% 
  filter(yr_alloc < 8000) %>% 
  filter(yr_alloc <= 2010) %>%
  select(fips2010, allocamt)

lihtc_dollars10$allocamt[is.na(lihtc_dollars10$allocamt)] <- 0

lihtc_dollars10 <- lihtc_dollars10 %>% 
  group_by(fips2010) %>% 
  summarise(pre10_lihtc_project_dollars = sum(allocamt, na.rm = TRUE))

lihtc_dollars10 %>% head() 

## # A tibble: 6 × 2
##   fips2010    pre10_lihtc_project_dollars
##   <chr>                             <dbl>
## 1 01001020300                      216593
## 2 01001020500                     2250459
## 3 01001021100                       53109
## 4 01003010200                           0
## 5 01003010600                      376889
## 6 01003010703                      717113

lihtc_projects10 <- left_join(lihtc_projects10, lihtc_dollars10, join_by(fips2010 == fips2010))

lihtc_projects10 %>% head()

##      fips2010 pre10_lihtc_project_cnt pre10_lihtc_project_dollars
## 1 01001020300                       2                      216593
## 2 01001020500                       5                     2250459
## 3 01001021100                       1                       53109
## 4 01003010200                       1                           0
## 5 01003010600                       1                      376889
## 6 01003010703                       1                      717113

lihtc_projects20 <- lihtc_projects %>% 
  filter(yr_alloc < 8000) %>% 
  filter(yr_alloc > 2010) %>% 
  filter(yr_alloc < 2021) %>% 
  count(fips2010) %>% 
  rename("post10_lihtc_project_cnt" = "n")

lihtc_projects20 %>% head() 

##      fips2010 post10_lihtc_project_cnt
## 1 01003010500                        1
## 2 01003011403                        1
## 3 01003011601                        1
## 4 01005950900                        1
## 5 01009050102                        1
## 6 01017954600                        2

lihtc_dollars20 <- lihtc_projects %>% 
  filter(yr_alloc < 8000) %>% 
  filter(yr_alloc > 2010) %>% 
  filter(yr_alloc < 2021) %>% 
  select(fips2010, allocamt)

lihtc_dollars20$allocamt[is.na(lihtc_dollars20$allocamt)] <- 0

lihtc_dollars20 <- lihtc_dollars20 %>% 
  group_by(fips2010) %>% 
  summarise(post10_lihtc_project_dollars = sum(allocamt, na.rm = TRUE))

lihtc_dollars20 %>% head() 

## # A tibble: 6 × 2
##   fips2010    post10_lihtc_project_dollars
##   <chr>                              <dbl>
## 1 01003010500                       481325
## 2 01003011403                       828342
## 3 01003011601                       887856
## 4 01005950900                       400758
## 5 01009050102                       463000
## 6 01017954600                       950192

lihtc_projects20 <- left_join(lihtc_projects20, lihtc_dollars20, join_by(fips2010 == fips2010))

lihtc_projects20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

fips2010	post10_lihtc_project_cnt	post10_lihtc_project_dollars
01003010500	1	481325
01003011403	1	828342
01003011601	1	887856
01005950900	1	400758
01009050102	1	463000
01017954600	2	950192

svi_divisional_lihtc10 <- left_join(svi_divisional, lihtc_projects10, join_by("GEOID_2010_trt" == "fips2010"))

svi_divisional_lihtc10 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars
34001000100	34	001	000100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2907	1088	983	1127	2907	38.76849	0.8482	1	144	1433	10.048849	0.7544	1	280	435	64.36782	0.9529	1	204	548	37.22628	0.2998	0	484	983	49.23703	0.7813	1	468	1759	26.60603	0.8634	1	532	2543	20.92017	0.8978	1	250	8.599931	0.1777	0	944	32.47334	0.94170	1	186	1851	10.04862	0.2706	0	266	678	39.233038	0.8981	1	177	2611	6.779012	0.7778	1	1928	2907	66.32267	0.7743	1	1088	113	10.386029	0.6229	0	9	0.8272059	0.7223	0	80	983	8.138352	0.8657	1	265	983	26.95829	0.7354	0	0	2907	0.000000	0.3512	0	4.1451	0.8935	5	3.06590	0.7944	3	0.7743	0.7667	1	3.2975	0.8414	1	11.28280	0.8862	10	2157	941	784	1182	2157	54.79833	0.9571	1	242	1058	22.873346	0.9922	1	215	342	62.86550	0.9780	1	316	442	71.49321	0.9481	1	531	784	67.72959	0.9893	1	396	1274	31.08320	0.9497	1	266	2157	12.331943	0.9041	1	185	8.576727	0.09430	0	552	25.59110	0.8128	1	297	1605	18.504673	0.74880	0	83	510	16.27451	0.6090	0	251	2020	12.425743	0.8710	1	1852	2157	85.85999	0.8476	1	941	118	12.5398512	0.6385	0	0	0.0000000	0.3216	0	67	784	8.545918	0.8657	1	212	784	27.04082	0.7502	1	0	2157	0.0000000	0.1517	0	4.7924	0.9850	5	3.13590	0.8217	2	0.8476	0.8400	1	2.7277	0.6085	2	11.50360	0.9104	10	NA	NA
34001000200	34	001	000200	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3189	2217	1473	519	3189	16.27469	0.4806	0	109	1558	6.996149	0.5179	0	573	955	60.00000	0.9323	1	199	518	38.41699	0.3261	0	772	1473	52.41005	0.8418	1	405	2579	15.70376	0.6491	0	484	3547	13.64533	0.7154	0	847	26.560050	0.9629	1	436	13.67200	0.08181	0	608	3005	20.23295	0.8466	1	42	857	4.900817	0.1204	0	422	3072	13.736979	0.8799	1	1792	3189	56.19316	0.7390	0	2217	901	40.640505	0.8693	1	0	0.0000000	0.3251	0	48	1473	3.258656	0.7064	0	250	1473	16.97217	0.6444	0	0	3189	0.000000	0.3512	0	3.2048	0.6963	1	2.89161	0.7231	3	0.7390	0.7317	0	2.8964	0.6887	1	9.73181	0.7340	5	3510	2046	1353	1021	3510	29.08832	0.7682	1	121	1852	6.533477	0.6717	0	343	696	49.28161	0.9273	1	416	657	63.31811	0.8696	1	759	1353	56.09756	0.9321	1	553	2338	23.65269	0.8871	1	354	3510	10.085470	0.8530	1	643	18.319088	0.60310	0	1002	28.54701	0.9055	1	450	2508	17.942584	0.72330	0	237	786	30.15267	0.8539	1	534	3375	15.822222	0.9062	1	2534	3510	72.19373	0.7818	1	2046	906	44.2815249	0.8690	1	0	0.0000000	0.3216	0	119	1353	8.795270	0.8711	1	324	1353	23.94678	0.7255	0	0	3510	0.0000000	0.1517	0	4.1121	0.9003	4	3.99200	0.9781	3	0.7818	0.7747	1	2.9389	0.7011	2	11.82480	0.9310	10	NA	NA
34001000300	34	001	000300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3997	1823	1357	1401	3968	35.30746	0.8164	1	382	2238	17.068811	0.9376	1	176	329	53.49544	0.8855	1	604	1028	58.75486	0.7947	1	780	1357	57.47973	0.9165	1	920	2677	34.36683	0.9346	1	1351	4149	32.56206	0.9811	1	314	7.855892	0.1437	0	937	23.44258	0.55900	0	319	3054	10.44532	0.3000	0	187	782	23.913044	0.7498	0	1080	3671	29.419777	0.9742	1	3357	3997	83.98799	0.8419	1	1823	363	19.912233	0.7535	1	0	0.0000000	0.3251	0	150	1357	11.053795	0.9136	1	651	1357	47.97347	0.8585	1	0	3997	0.000000	0.3512	0	4.5862	0.9691	5	2.72670	0.6360	1	0.8419	0.8336	1	3.2019	0.8054	3	11.35670	0.8920	10	3801	1640	1226	1857	3801	48.85556	0.9333	1	226	1800	12.555556	0.9267	1	111	280	39.64286	0.8339	1	608	946	64.27061	0.8842	1	719	1226	58.64600	0.9528	1	650	2275	28.57143	0.9337	1	1027	3801	27.019206	0.9914	1	380	9.997369	0.14040	0	1223	32.17574	0.9607	1	219	2578	8.494957	0.15680	0	268	909	29.48295	0.8456	1	940	3400	27.647059	0.9728	1	3318	3801	87.29282	0.8579	1	1640	262	15.9756098	0.6917	0	0	0.0000000	0.3216	0	124	1226	10.114192	0.8955	1	477	1226	38.90701	0.8258	1	0	3801	0.0000000	0.1517	0	4.7379	0.9829	5	3.07630	0.8013	3	0.8579	0.8501	1	2.8863	0.6781	2	11.55840	0.9150	11	NA	NA
34001000400	34	001	000400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2902	2683	1401	1172	2902	40.38594	0.8615	1	190	1389	13.678906	0.8811	1	364	707	51.48515	0.8627	1	507	694	73.05476	0.9503	1	871	1401	62.16988	0.9572	1	481	1981	24.28067	0.8339	1	674	3204	21.03620	0.8998	1	434	14.955203	0.6083	0	596	20.53756	0.33980	0	426	2607	16.34062	0.6886	0	111	652	17.024540	0.6204	0	215	2736	7.858187	0.8008	1	1792	2902	61.75052	0.7584	1	2683	2049	76.369735	0.9401	1	0	0.0000000	0.3251	0	69	1401	4.925053	0.7847	1	511	1401	36.47395	0.7992	1	72	2902	2.481048	0.8114	1	4.4335	0.9468	5	3.05790	0.7908	1	0.7584	0.7510	1	3.6605	0.9391	4	11.91030	0.9339	11	3178	2264	1390	1508	3176	47.48111	0.9246	1	172	1804	9.534368	0.8460	1	205	468	43.80342	0.8858	1	622	922	67.46204	0.9192	1	827	1390	59.49640	0.9587	1	364	2076	17.53372	0.8013	1	476	3178	14.977974	0.9390	1	483	15.198238	0.41220	0	539	16.96035	0.2484	0	319	2639	12.087912	0.38790	0	101	565	17.87611	0.6539	0	583	3022	19.291860	0.9349	1	2186	3178	68.78540	0.7658	1	2264	1609	71.0689046	0.9266	1	15	0.6625442	0.7078	0	226	1390	16.258993	0.9567	1	599	1390	43.09353	0.8474	1	20	3178	0.6293266	0.6292	0	4.4696	0.9558	5	2.63730	0.5864	1	0.7658	0.7588	1	4.0677	0.9762	3	11.94040	0.9387	10	NA	NA
34001000500	34	001	000500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3483	1241	1027	1938	3483	55.64169	0.9533	1	124	1630	7.607362	0.5830	0	227	446	50.89686	0.8549	1	478	581	82.27194	0.9799	1	705	1027	68.64654	0.9863	1	733	2077	35.29129	0.9396	1	727	3258	22.31430	0.9149	1	377	10.824002	0.3081	0	1055	30.28998	0.90140	1	268	2401	11.16202	0.3549	0	209	763	27.391874	0.7940	1	911	3077	29.606760	0.9746	1	3036	3483	87.16624	0.8550	1	1241	52	4.190169	0.4505	0	4	0.3223207	0.6567	0	113	1027	11.002921	0.9128	1	422	1027	41.09056	0.8250	1	0	3483	0.000000	0.3512	0	4.3771	0.9379	4	3.33300	0.8766	3	0.8550	0.8467	1	3.1962	0.8026	2	11.76130	0.9229	10	3385	1185	945	1682	3364	50.00000	0.9391	1	72	1577	4.565631	0.4586	0	185	468	39.52991	0.8332	1	362	477	75.89099	0.9703	1	547	945	57.88360	0.9477	1	592	1983	29.85376	0.9422	1	738	3385	21.802068	0.9817	1	240	7.090103	0.05988	0	1129	33.35303	0.9689	1	135	2256	5.984043	0.04817	0	110	717	15.34170	0.5822	0	721	3076	23.439532	0.9569	1	3029	3385	89.48301	0.8727	1	1185	9	0.7594937	0.2382	0	0	0.0000000	0.3216	0	103	945	10.899471	0.9072	1	263	945	27.83069	0.7560	1	0	3385	0.0000000	0.1517	0	4.2693	0.9283	4	2.61605	0.5709	2	0.8727	0.8648	1	2.3747	0.4357	2	10.13275	0.7921	9	NA	NA
34001001100	34	001	001100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2204	1204	1204	1185	2204	53.76588	0.9457	1	219	927	23.624596	0.9830	1	97	172	56.39535	0.9094	1	462	1032	44.76744	0.4746	0	559	1204	46.42857	0.7197	0	346	1440	24.02778	0.8306	1	469	1942	24.15036	0.9360	1	363	16.470054	0.7020	0	578	26.22505	0.74410	0	442	1558	28.36970	0.9675	1	247	396	62.373737	0.9898	1	104	2051	5.070697	0.7260	0	2118	2204	96.09800	0.9204	1	1204	570	47.342193	0.8858	1	0	0.0000000	0.3251	0	14	1204	1.162791	0.4877	0	817	1204	67.85714	0.9413	1	0	2204	0.000000	0.3512	0	4.4150	0.9451	4	4.12940	0.9805	2	0.9204	0.9114	1	2.9911	0.7243	2	12.45590	0.9597	9	1950	1267	1096	1131	1950	58.00000	0.9678	1	66	706	9.348442	0.8395	1	42	101	41.58416	0.8612	1	309	995	31.05528	0.1959	0	351	1096	32.02555	0.4782	0	510	1379	36.98332	0.9763	1	155	1950	7.948718	0.7660	1	392	20.102564	0.69880	0	447	22.92308	0.6712	0	570	1503	37.924152	0.99200	1	143	374	38.23529	0.9167	1	109	1841	5.920695	0.7464	0	1909	1950	97.89744	0.9529	1	1267	479	37.8058406	0.8464	1	0	0.0000000	0.3216	0	33	1096	3.010949	0.6446	0	743	1096	67.79197	0.9414	1	0	1950	0.0000000	0.1517	0	4.0278	0.8848	4	4.02510	0.9798	2	0.9529	0.9442	1	2.9057	0.6869	2	11.91150	0.9365	9	1	0

svi_national_lihtc10 <- left_join(svi_national, lihtc_projects10, join_by("GEOID_2010_trt" == "fips2010"))

svi_national_lihtc10 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars
01001020100	01	001	020100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1809	771	696	297	1809	16.41791	0.3871	0	36	889	4.049494	0.1790	0	127	598	21.23746	0.20770	0	47	98	47.95918	0.5767	0	174	696	25.00000	0.18790	0	196	1242	15.780998	0.6093	0	186	1759	10.574190	0.3790	0	222	12.271973	0.4876	0	445	24.59923	0.5473	0	298	1335	22.32210	0.8454	1	27	545	4.954128	0.09275	0	36	1705	2.1114370	0.59040	0	385	1809	21.282477	0.4524	0	771	0	0.0000000	0.1224	0	92	11.9325551	0.8005	1	0	696	0.0000000	0.1238	0	50	696	7.183908	0.6134	0	0	1809	0	0.364	0	1.74230	0.28200	0	2.56345	0.5296	1	0.4524	0.4482	0	2.0241	0.2519	1	6.78225	0.3278	2	1941	710	693	352	1941	18.13498	0.4630	0	18	852	2.112676	0.15070	0	81	507	15.976331	0.26320	0	63	186	33.87097	0.2913	0	144	693	20.77922	0.2230	0	187	1309	14.285714	0.6928	0	187	1941	9.634209	0.6617	0	295	15.19835	0.4601	0	415	21.38073	0.4681	0	391	1526	25.62254	0.9011	1	58	555	10.45045	0.3451	0	0	1843	0.0000000	0.09479	0	437	1941	22.51417	0.3902	0	710	0	0.0000000	0.1079	0	88	12.3943662	0.8263	1	0	693	0.0000000	0.09796	0	10	693	1.443001	0.1643	0	0	1941	0.000000	0.1831	0	2.19120	0.4084	0	2.26919	0.3503	1	0.3902	0.3869	0	1.37956	0.07216	1	6.23015	0.2314	2	NA	NA
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.5754	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.3019	0	154	730	21.09589	0.09312	0	339	1265	26.798419	0.8392	1	313	2012	15.556660	0.6000	0	204	10.099010	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.83510	1	15	1890	0.7936508	0.40130	0	1243	2020	61.534653	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.7808219	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0	0.364	0	2.70312	0.56650	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.41320	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.4041	0	139	1313	10.586443	0.5601	0	91	1533	5.936073	0.4343	0	284	16.16392	0.5169	0	325	18.49744	0.2851	0	164	1208	13.57616	0.4127	0	42	359	11.69916	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.46880	0	57	573	9.947644	0.7317	0	212	1757	12.066022	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.91300	0.68620	1	7.83579	0.4802	2	NA	NA
01001020300	01	001	020300	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3543	1403	1287	656	3533	18.56779	0.4443	0	93	1552	5.992268	0.3724	0	273	957	28.52665	0.45780	0	178	330	53.93939	0.7152	0	451	1287	35.04274	0.49930	0	346	2260	15.309734	0.5950	0	252	3102	8.123791	0.2596	0	487	13.745413	0.5868	0	998	28.16822	0.7606	1	371	2224	16.68165	0.6266	0	126	913	13.800657	0.46350	0	0	3365	0.0000000	0.09298	0	637	3543	17.979114	0.4049	0	1403	10	0.7127584	0.3015	0	2	0.1425517	0.4407	0	0	1287	0.0000000	0.1238	0	101	1287	7.847708	0.6443	0	0	3543	0	0.364	0	2.17060	0.41010	0	2.53048	0.5116	1	0.4049	0.4011	0	1.8743	0.1942	0	6.98028	0.3576	1	3694	1464	1351	842	3694	22.79372	0.5833	0	53	1994	2.657974	0.22050	0	117	967	12.099276	0.11370	0	147	384	38.28125	0.3856	0	264	1351	19.54108	0.1827	0	317	2477	12.797739	0.6460	0	127	3673	3.457664	0.2308	0	464	12.56091	0.3088	0	929	25.14889	0.7080	0	473	2744	17.23761	0.6211	0	263	975	26.97436	0.8234	1	128	3586	3.5694367	0.70770	0	1331	3694	36.03140	0.5515	0	1464	26	1.7759563	0.3675	0	14	0.9562842	0.5389	0	35	1351	2.5906736	0.60550	0	42	1351	3.108808	0.3415	0	0	3694	0.000000	0.1831	0	1.86330	0.3063	0	3.16900	0.8380	1	0.5515	0.5468	0	2.03650	0.26830	0	7.62030	0.4460	1	2	216593
01001020400	01	001	020400	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	4840	1957	1839	501	4840	10.35124	0.2177	0	101	2129	4.744011	0.2447	0	310	1549	20.01291	0.17080	0	89	290	30.68966	0.2044	0	399	1839	21.69657	0.10540	0	274	3280	8.353658	0.3205	0	399	4293	9.294200	0.3171	0	955	19.731405	0.8643	1	1195	24.69008	0.5530	0	625	3328	18.78005	0.7233	0	152	1374	11.062591	0.34710	0	10	4537	0.2204100	0.22560	0	297	4840	6.136364	0.1647	0	1957	33	1.6862545	0.3843	0	25	1.2774655	0.5516	0	14	1839	0.7612833	0.3564	0	19	1839	1.033170	0.1127	0	0	4840	0	0.364	0	1.20540	0.13470	0	2.71330	0.6129	1	0.1647	0.1632	0	1.7690	0.1591	0	5.85240	0.1954	1	3539	1741	1636	503	3539	14.21305	0.3472	0	39	1658	2.352232	0.17990	0	219	1290	16.976744	0.30880	0	74	346	21.38728	0.1037	0	293	1636	17.90954	0.1333	0	173	2775	6.234234	0.3351	0	169	3529	4.788892	0.3448	0	969	27.38062	0.9225	1	510	14.41085	0.1208	0	670	3019	22.19278	0.8194	1	148	1137	13.01671	0.4541	0	89	3409	2.6107363	0.64690	0	454	3539	12.82848	0.2364	0	1741	143	8.2136703	0.6028	0	0	0.0000000	0.2186	0	10	1636	0.6112469	0.28340	0	72	1636	4.400978	0.4538	0	0	3539	0.000000	0.1831	0	1.34030	0.1575	0	2.96370	0.7496	2	0.2364	0.2344	0	1.74170	0.16270	0	6.28210	0.2389	2	NA	NA
01001020500	01	001	020500	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	9938	3969	3741	1096	9938	11.02838	0.2364	0	188	4937	3.807981	0.1577	0	426	2406	17.70574	0.11050	0	528	1335	39.55056	0.3753	0	954	3741	25.50120	0.20140	0	293	5983	4.897209	0.1655	0	740	10110	7.319486	0.2211	0	837	8.422218	0.2408	0	3012	30.30791	0.8455	1	759	7155	10.60797	0.2668	0	476	2529	18.821669	0.63540	0	78	9297	0.8389803	0.41110	0	1970	9938	19.822902	0.4330	0	3969	306	7.7097506	0.6153	0	0	0.0000000	0.2198	0	7	3741	0.1871157	0.2535	0	223	3741	5.960973	0.5483	0	0	9938	0	0.364	0	0.98210	0.08468	0	2.39960	0.4381	1	0.4330	0.4290	0	2.0009	0.2430	0	5.81560	0.1905	1	10674	4504	4424	1626	10509	15.47245	0.3851	0	81	5048	1.604596	0.09431	0	321	2299	13.962592	0.17970	0	711	2125	33.45882	0.2836	0	1032	4424	23.32731	0.3109	0	531	6816	7.790493	0.4251	0	301	10046	2.996217	0.1894	0	1613	15.11149	0.4553	0	2765	25.90407	0.7494	0	1124	7281	15.43744	0.5253	0	342	2912	11.74451	0.4019	0	52	9920	0.5241935	0.35230	0	2603	10674	24.38636	0.4160	0	4504	703	15.6083481	0.7378	0	29	0.6438721	0.5037	0	37	4424	0.8363472	0.33420	0	207	4424	4.679023	0.4754	0	176	10674	1.648866	0.7598	1	1.40481	0.1743	0	2.48420	0.4802	0	0.4160	0.4125	0	2.81090	0.63730	1	7.11591	0.3654	1	5	2250459
01001020600	01	001	020600	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3402	1456	1308	735	3402	21.60494	0.5199	0	134	1720	7.790698	0.5436	0	242	1032	23.44961	0.28010	0	62	276	22.46377	0.1035	0	304	1308	23.24159	0.14070	0	301	2151	13.993491	0.5510	0	355	3445	10.304790	0.3656	0	386	11.346267	0.4232	0	931	27.36626	0.7200	0	440	2439	18.04018	0.6912	0	143	924	15.476190	0.52900	0	4	3254	0.1229256	0.19840	0	723	3402	21.252205	0.4519	0	1456	18	1.2362637	0.3507	0	433	29.7390110	0.9468	1	16	1308	1.2232416	0.4493	0	28	1308	2.140673	0.2298	0	0	3402	0	0.364	0	2.12080	0.39510	0	2.56180	0.5288	0	0.4519	0.4477	0	2.3406	0.4048	1	7.47510	0.4314	1	3536	1464	1330	1279	3523	36.30429	0.8215	1	34	1223	2.780049	0.23780	0	321	1111	28.892889	0.75870	1	67	219	30.59361	0.2305	0	388	1330	29.17293	0.5075	0	306	2380	12.857143	0.6480	0	415	3496	11.870709	0.7535	1	547	15.46946	0.4760	0	982	27.77149	0.8327	1	729	2514	28.99761	0.9488	1	95	880	10.79545	0.3601	0	0	3394	0.0000000	0.09479	0	985	3536	27.85633	0.4608	0	1464	0	0.0000000	0.1079	0	364	24.8633880	0.9300	1	0	1330	0.0000000	0.09796	0	17	1330	1.278196	0.1463	0	0	3536	0.000000	0.1831	0	2.96830	0.6434	2	2.71239	0.6156	2	0.4608	0.4569	0	1.46526	0.08976	1	7.60675	0.4440	5	NA	NA

svi_divisional_lihtc20 <- left_join(svi_divisional_lihtc10, lihtc_projects20, join_by("GEOID_2010_trt" == "fips2010"))

svi_divisional_lihtc20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars
34001000100	34	001	000100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2907	1088	983	1127	2907	38.76849	0.8482	1	144	1433	10.048849	0.7544	1	280	435	64.36782	0.9529	1	204	548	37.22628	0.2998	0	484	983	49.23703	0.7813	1	468	1759	26.60603	0.8634	1	532	2543	20.92017	0.8978	1	250	8.599931	0.1777	0	944	32.47334	0.94170	1	186	1851	10.04862	0.2706	0	266	678	39.233038	0.8981	1	177	2611	6.779012	0.7778	1	1928	2907	66.32267	0.7743	1	1088	113	10.386029	0.6229	0	9	0.8272059	0.7223	0	80	983	8.138352	0.8657	1	265	983	26.95829	0.7354	0	0	2907	0.000000	0.3512	0	4.1451	0.8935	5	3.06590	0.7944	3	0.7743	0.7667	1	3.2975	0.8414	1	11.28280	0.8862	10	2157	941	784	1182	2157	54.79833	0.9571	1	242	1058	22.873346	0.9922	1	215	342	62.86550	0.9780	1	316	442	71.49321	0.9481	1	531	784	67.72959	0.9893	1	396	1274	31.08320	0.9497	1	266	2157	12.331943	0.9041	1	185	8.576727	0.09430	0	552	25.59110	0.8128	1	297	1605	18.504673	0.74880	0	83	510	16.27451	0.6090	0	251	2020	12.425743	0.8710	1	1852	2157	85.85999	0.8476	1	941	118	12.5398512	0.6385	0	0	0.0000000	0.3216	0	67	784	8.545918	0.8657	1	212	784	27.04082	0.7502	1	0	2157	0.0000000	0.1517	0	4.7924	0.9850	5	3.13590	0.8217	2	0.8476	0.8400	1	2.7277	0.6085	2	11.50360	0.9104	10	NA	NA	NA	NA
34001000200	34	001	000200	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3189	2217	1473	519	3189	16.27469	0.4806	0	109	1558	6.996149	0.5179	0	573	955	60.00000	0.9323	1	199	518	38.41699	0.3261	0	772	1473	52.41005	0.8418	1	405	2579	15.70376	0.6491	0	484	3547	13.64533	0.7154	0	847	26.560050	0.9629	1	436	13.67200	0.08181	0	608	3005	20.23295	0.8466	1	42	857	4.900817	0.1204	0	422	3072	13.736979	0.8799	1	1792	3189	56.19316	0.7390	0	2217	901	40.640505	0.8693	1	0	0.0000000	0.3251	0	48	1473	3.258656	0.7064	0	250	1473	16.97217	0.6444	0	0	3189	0.000000	0.3512	0	3.2048	0.6963	1	2.89161	0.7231	3	0.7390	0.7317	0	2.8964	0.6887	1	9.73181	0.7340	5	3510	2046	1353	1021	3510	29.08832	0.7682	1	121	1852	6.533477	0.6717	0	343	696	49.28161	0.9273	1	416	657	63.31811	0.8696	1	759	1353	56.09756	0.9321	1	553	2338	23.65269	0.8871	1	354	3510	10.085470	0.8530	1	643	18.319088	0.60310	0	1002	28.54701	0.9055	1	450	2508	17.942584	0.72330	0	237	786	30.15267	0.8539	1	534	3375	15.822222	0.9062	1	2534	3510	72.19373	0.7818	1	2046	906	44.2815249	0.8690	1	0	0.0000000	0.3216	0	119	1353	8.795270	0.8711	1	324	1353	23.94678	0.7255	0	0	3510	0.0000000	0.1517	0	4.1121	0.9003	4	3.99200	0.9781	3	0.7818	0.7747	1	2.9389	0.7011	2	11.82480	0.9310	10	NA	NA	NA	NA
34001000300	34	001	000300	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3997	1823	1357	1401	3968	35.30746	0.8164	1	382	2238	17.068811	0.9376	1	176	329	53.49544	0.8855	1	604	1028	58.75486	0.7947	1	780	1357	57.47973	0.9165	1	920	2677	34.36683	0.9346	1	1351	4149	32.56206	0.9811	1	314	7.855892	0.1437	0	937	23.44258	0.55900	0	319	3054	10.44532	0.3000	0	187	782	23.913044	0.7498	0	1080	3671	29.419777	0.9742	1	3357	3997	83.98799	0.8419	1	1823	363	19.912233	0.7535	1	0	0.0000000	0.3251	0	150	1357	11.053795	0.9136	1	651	1357	47.97347	0.8585	1	0	3997	0.000000	0.3512	0	4.5862	0.9691	5	2.72670	0.6360	1	0.8419	0.8336	1	3.2019	0.8054	3	11.35670	0.8920	10	3801	1640	1226	1857	3801	48.85556	0.9333	1	226	1800	12.555556	0.9267	1	111	280	39.64286	0.8339	1	608	946	64.27061	0.8842	1	719	1226	58.64600	0.9528	1	650	2275	28.57143	0.9337	1	1027	3801	27.019206	0.9914	1	380	9.997369	0.14040	0	1223	32.17574	0.9607	1	219	2578	8.494957	0.15680	0	268	909	29.48295	0.8456	1	940	3400	27.647059	0.9728	1	3318	3801	87.29282	0.8579	1	1640	262	15.9756098	0.6917	0	0	0.0000000	0.3216	0	124	1226	10.114192	0.8955	1	477	1226	38.90701	0.8258	1	0	3801	0.0000000	0.1517	0	4.7379	0.9829	5	3.07630	0.8013	3	0.8579	0.8501	1	2.8863	0.6781	2	11.55840	0.9150	11	NA	NA	NA	NA
34001000400	34	001	000400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2902	2683	1401	1172	2902	40.38594	0.8615	1	190	1389	13.678906	0.8811	1	364	707	51.48515	0.8627	1	507	694	73.05476	0.9503	1	871	1401	62.16988	0.9572	1	481	1981	24.28067	0.8339	1	674	3204	21.03620	0.8998	1	434	14.955203	0.6083	0	596	20.53756	0.33980	0	426	2607	16.34062	0.6886	0	111	652	17.024540	0.6204	0	215	2736	7.858187	0.8008	1	1792	2902	61.75052	0.7584	1	2683	2049	76.369735	0.9401	1	0	0.0000000	0.3251	0	69	1401	4.925053	0.7847	1	511	1401	36.47395	0.7992	1	72	2902	2.481048	0.8114	1	4.4335	0.9468	5	3.05790	0.7908	1	0.7584	0.7510	1	3.6605	0.9391	4	11.91030	0.9339	11	3178	2264	1390	1508	3176	47.48111	0.9246	1	172	1804	9.534368	0.8460	1	205	468	43.80342	0.8858	1	622	922	67.46204	0.9192	1	827	1390	59.49640	0.9587	1	364	2076	17.53372	0.8013	1	476	3178	14.977974	0.9390	1	483	15.198238	0.41220	0	539	16.96035	0.2484	0	319	2639	12.087912	0.38790	0	101	565	17.87611	0.6539	0	583	3022	19.291860	0.9349	1	2186	3178	68.78540	0.7658	1	2264	1609	71.0689046	0.9266	1	15	0.6625442	0.7078	0	226	1390	16.258993	0.9567	1	599	1390	43.09353	0.8474	1	20	3178	0.6293266	0.6292	0	4.4696	0.9558	5	2.63730	0.5864	1	0.7658	0.7588	1	4.0677	0.9762	3	11.94040	0.9387	10	NA	NA	NA	NA
34001000500	34	001	000500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3483	1241	1027	1938	3483	55.64169	0.9533	1	124	1630	7.607362	0.5830	0	227	446	50.89686	0.8549	1	478	581	82.27194	0.9799	1	705	1027	68.64654	0.9863	1	733	2077	35.29129	0.9396	1	727	3258	22.31430	0.9149	1	377	10.824002	0.3081	0	1055	30.28998	0.90140	1	268	2401	11.16202	0.3549	0	209	763	27.391874	0.7940	1	911	3077	29.606760	0.9746	1	3036	3483	87.16624	0.8550	1	1241	52	4.190169	0.4505	0	4	0.3223207	0.6567	0	113	1027	11.002921	0.9128	1	422	1027	41.09056	0.8250	1	0	3483	0.000000	0.3512	0	4.3771	0.9379	4	3.33300	0.8766	3	0.8550	0.8467	1	3.1962	0.8026	2	11.76130	0.9229	10	3385	1185	945	1682	3364	50.00000	0.9391	1	72	1577	4.565631	0.4586	0	185	468	39.52991	0.8332	1	362	477	75.89099	0.9703	1	547	945	57.88360	0.9477	1	592	1983	29.85376	0.9422	1	738	3385	21.802068	0.9817	1	240	7.090103	0.05988	0	1129	33.35303	0.9689	1	135	2256	5.984043	0.04817	0	110	717	15.34170	0.5822	0	721	3076	23.439532	0.9569	1	3029	3385	89.48301	0.8727	1	1185	9	0.7594937	0.2382	0	0	0.0000000	0.3216	0	103	945	10.899471	0.9072	1	263	945	27.83069	0.7560	1	0	3385	0.0000000	0.1517	0	4.2693	0.9283	4	2.61605	0.5709	2	0.8727	0.8648	1	2.3747	0.4357	2	10.13275	0.7921	9	NA	NA	NA	NA
34001001100	34	001	001100	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	2204	1204	1204	1185	2204	53.76588	0.9457	1	219	927	23.624596	0.9830	1	97	172	56.39535	0.9094	1	462	1032	44.76744	0.4746	0	559	1204	46.42857	0.7197	0	346	1440	24.02778	0.8306	1	469	1942	24.15036	0.9360	1	363	16.470054	0.7020	0	578	26.22505	0.74410	0	442	1558	28.36970	0.9675	1	247	396	62.373737	0.9898	1	104	2051	5.070697	0.7260	0	2118	2204	96.09800	0.9204	1	1204	570	47.342193	0.8858	1	0	0.0000000	0.3251	0	14	1204	1.162791	0.4877	0	817	1204	67.85714	0.9413	1	0	2204	0.000000	0.3512	0	4.4150	0.9451	4	4.12940	0.9805	2	0.9204	0.9114	1	2.9911	0.7243	2	12.45590	0.9597	9	1950	1267	1096	1131	1950	58.00000	0.9678	1	66	706	9.348442	0.8395	1	42	101	41.58416	0.8612	1	309	995	31.05528	0.1959	0	351	1096	32.02555	0.4782	0	510	1379	36.98332	0.9763	1	155	1950	7.948718	0.7660	1	392	20.102564	0.69880	0	447	22.92308	0.6712	0	570	1503	37.924152	0.99200	1	143	374	38.23529	0.9167	1	109	1841	5.920695	0.7464	0	1909	1950	97.89744	0.9529	1	1267	479	37.8058406	0.8464	1	0	0.0000000	0.3216	0	33	1096	3.010949	0.6446	0	743	1096	67.79197	0.9414	1	0	1950	0.0000000	0.1517	0	4.0278	0.8848	4	4.02510	0.9798	2	0.9529	0.9442	1	2.9057	0.6869	2	11.91150	0.9365	9	1	0	1	1290441

svi_national_lihtc20 <- left_join(svi_national_lihtc10, lihtc_projects20, join_by("GEOID_2010_trt" == "fips2010"))

svi_national_lihtc20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars
01001020100	01	001	020100	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	1809	771	696	297	1809	16.41791	0.3871	0	36	889	4.049494	0.1790	0	127	598	21.23746	0.20770	0	47	98	47.95918	0.5767	0	174	696	25.00000	0.18790	0	196	1242	15.780998	0.6093	0	186	1759	10.574190	0.3790	0	222	12.271973	0.4876	0	445	24.59923	0.5473	0	298	1335	22.32210	0.8454	1	27	545	4.954128	0.09275	0	36	1705	2.1114370	0.59040	0	385	1809	21.282477	0.4524	0	771	0	0.0000000	0.1224	0	92	11.9325551	0.8005	1	0	696	0.0000000	0.1238	0	50	696	7.183908	0.6134	0	0	1809	0	0.364	0	1.74230	0.28200	0	2.56345	0.5296	1	0.4524	0.4482	0	2.0241	0.2519	1	6.78225	0.3278	2	1941	710	693	352	1941	18.13498	0.4630	0	18	852	2.112676	0.15070	0	81	507	15.976331	0.26320	0	63	186	33.87097	0.2913	0	144	693	20.77922	0.2230	0	187	1309	14.285714	0.6928	0	187	1941	9.634209	0.6617	0	295	15.19835	0.4601	0	415	21.38073	0.4681	0	391	1526	25.62254	0.9011	1	58	555	10.45045	0.3451	0	0	1843	0.0000000	0.09479	0	437	1941	22.51417	0.3902	0	710	0	0.0000000	0.1079	0	88	12.3943662	0.8263	1	0	693	0.0000000	0.09796	0	10	693	1.443001	0.1643	0	0	1941	0.000000	0.1831	0	2.19120	0.4084	0	2.26919	0.3503	1	0.3902	0.3869	0	1.37956	0.07216	1	6.23015	0.2314	2	NA	NA	NA	NA
01001020200	01	001	020200	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	2020	816	730	495	1992	24.84940	0.5954	0	68	834	8.153477	0.5754	0	49	439	11.16173	0.02067	0	105	291	36.08247	0.3019	0	154	730	21.09589	0.09312	0	339	1265	26.798419	0.8392	1	313	2012	15.556660	0.6000	0	204	10.099010	0.3419	0	597	29.55446	0.8192	1	359	1515	23.69637	0.8791	1	132	456	28.947368	0.83510	1	15	1890	0.7936508	0.40130	0	1243	2020	61.534653	0.7781	1	816	0	0.0000000	0.1224	0	34	4.1666667	0.6664	0	13	730	1.7808219	0.5406	0	115	730	15.753425	0.8382	1	0	2020	0	0.364	0	2.70312	0.56650	1	3.27660	0.8614	3	0.7781	0.7709	1	2.5316	0.5047	1	9.28942	0.6832	6	1757	720	573	384	1511	25.41363	0.6427	0	29	717	4.044630	0.41320	0	33	392	8.418367	0.03542	0	116	181	64.08840	0.9086	1	149	573	26.00349	0.4041	0	139	1313	10.586443	0.5601	0	91	1533	5.936073	0.4343	0	284	16.16392	0.5169	0	325	18.49744	0.2851	0	164	1208	13.57616	0.4127	0	42	359	11.69916	0.3998	0	0	1651	0.0000000	0.09479	0	1116	1757	63.51736	0.7591	1	720	3	0.4166667	0.2470	0	5	0.6944444	0.5106	0	9	573	1.5706806	0.46880	0	57	573	9.947644	0.7317	0	212	1757	12.066022	0.9549	1	2.45440	0.4888	0	1.70929	0.1025	0	0.7591	0.7527	1	2.91300	0.68620	1	7.83579	0.4802	2	NA	NA	NA	NA
01001020300	01	001	020300	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3543	1403	1287	656	3533	18.56779	0.4443	0	93	1552	5.992268	0.3724	0	273	957	28.52665	0.45780	0	178	330	53.93939	0.7152	0	451	1287	35.04274	0.49930	0	346	2260	15.309734	0.5950	0	252	3102	8.123791	0.2596	0	487	13.745413	0.5868	0	998	28.16822	0.7606	1	371	2224	16.68165	0.6266	0	126	913	13.800657	0.46350	0	0	3365	0.0000000	0.09298	0	637	3543	17.979114	0.4049	0	1403	10	0.7127584	0.3015	0	2	0.1425517	0.4407	0	0	1287	0.0000000	0.1238	0	101	1287	7.847708	0.6443	0	0	3543	0	0.364	0	2.17060	0.41010	0	2.53048	0.5116	1	0.4049	0.4011	0	1.8743	0.1942	0	6.98028	0.3576	1	3694	1464	1351	842	3694	22.79372	0.5833	0	53	1994	2.657974	0.22050	0	117	967	12.099276	0.11370	0	147	384	38.28125	0.3856	0	264	1351	19.54108	0.1827	0	317	2477	12.797739	0.6460	0	127	3673	3.457664	0.2308	0	464	12.56091	0.3088	0	929	25.14889	0.7080	0	473	2744	17.23761	0.6211	0	263	975	26.97436	0.8234	1	128	3586	3.5694367	0.70770	0	1331	3694	36.03140	0.5515	0	1464	26	1.7759563	0.3675	0	14	0.9562842	0.5389	0	35	1351	2.5906736	0.60550	0	42	1351	3.108808	0.3415	0	0	3694	0.000000	0.1831	0	1.86330	0.3063	0	3.16900	0.8380	1	0.5515	0.5468	0	2.03650	0.26830	0	7.62030	0.4460	1	2	216593	NA	NA
01001020400	01	001	020400	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	4840	1957	1839	501	4840	10.35124	0.2177	0	101	2129	4.744011	0.2447	0	310	1549	20.01291	0.17080	0	89	290	30.68966	0.2044	0	399	1839	21.69657	0.10540	0	274	3280	8.353658	0.3205	0	399	4293	9.294200	0.3171	0	955	19.731405	0.8643	1	1195	24.69008	0.5530	0	625	3328	18.78005	0.7233	0	152	1374	11.062591	0.34710	0	10	4537	0.2204100	0.22560	0	297	4840	6.136364	0.1647	0	1957	33	1.6862545	0.3843	0	25	1.2774655	0.5516	0	14	1839	0.7612833	0.3564	0	19	1839	1.033170	0.1127	0	0	4840	0	0.364	0	1.20540	0.13470	0	2.71330	0.6129	1	0.1647	0.1632	0	1.7690	0.1591	0	5.85240	0.1954	1	3539	1741	1636	503	3539	14.21305	0.3472	0	39	1658	2.352232	0.17990	0	219	1290	16.976744	0.30880	0	74	346	21.38728	0.1037	0	293	1636	17.90954	0.1333	0	173	2775	6.234234	0.3351	0	169	3529	4.788892	0.3448	0	969	27.38062	0.9225	1	510	14.41085	0.1208	0	670	3019	22.19278	0.8194	1	148	1137	13.01671	0.4541	0	89	3409	2.6107363	0.64690	0	454	3539	12.82848	0.2364	0	1741	143	8.2136703	0.6028	0	0	0.0000000	0.2186	0	10	1636	0.6112469	0.28340	0	72	1636	4.400978	0.4538	0	0	3539	0.000000	0.1831	0	1.34030	0.1575	0	2.96370	0.7496	2	0.2364	0.2344	0	1.74170	0.16270	0	6.28210	0.2389	2	NA	NA	NA	NA
01001020500	01	001	020500	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	9938	3969	3741	1096	9938	11.02838	0.2364	0	188	4937	3.807981	0.1577	0	426	2406	17.70574	0.11050	0	528	1335	39.55056	0.3753	0	954	3741	25.50120	0.20140	0	293	5983	4.897209	0.1655	0	740	10110	7.319486	0.2211	0	837	8.422218	0.2408	0	3012	30.30791	0.8455	1	759	7155	10.60797	0.2668	0	476	2529	18.821669	0.63540	0	78	9297	0.8389803	0.41110	0	1970	9938	19.822902	0.4330	0	3969	306	7.7097506	0.6153	0	0	0.0000000	0.2198	0	7	3741	0.1871157	0.2535	0	223	3741	5.960973	0.5483	0	0	9938	0	0.364	0	0.98210	0.08468	0	2.39960	0.4381	1	0.4330	0.4290	0	2.0009	0.2430	0	5.81560	0.1905	1	10674	4504	4424	1626	10509	15.47245	0.3851	0	81	5048	1.604596	0.09431	0	321	2299	13.962592	0.17970	0	711	2125	33.45882	0.2836	0	1032	4424	23.32731	0.3109	0	531	6816	7.790493	0.4251	0	301	10046	2.996217	0.1894	0	1613	15.11149	0.4553	0	2765	25.90407	0.7494	0	1124	7281	15.43744	0.5253	0	342	2912	11.74451	0.4019	0	52	9920	0.5241935	0.35230	0	2603	10674	24.38636	0.4160	0	4504	703	15.6083481	0.7378	0	29	0.6438721	0.5037	0	37	4424	0.8363472	0.33420	0	207	4424	4.679023	0.4754	0	176	10674	1.648866	0.7598	1	1.40481	0.1743	0	2.48420	0.4802	0	0.4160	0.4125	0	2.81090	0.63730	1	7.11591	0.3654	1	5	2250459	NA	NA
01001020600	01	001	020600	AL	Alabama	Autauga County	1	South Region	6	East South Central Division	3402	1456	1308	735	3402	21.60494	0.5199	0	134	1720	7.790698	0.5436	0	242	1032	23.44961	0.28010	0	62	276	22.46377	0.1035	0	304	1308	23.24159	0.14070	0	301	2151	13.993491	0.5510	0	355	3445	10.304790	0.3656	0	386	11.346267	0.4232	0	931	27.36626	0.7200	0	440	2439	18.04018	0.6912	0	143	924	15.476190	0.52900	0	4	3254	0.1229256	0.19840	0	723	3402	21.252205	0.4519	0	1456	18	1.2362637	0.3507	0	433	29.7390110	0.9468	1	16	1308	1.2232416	0.4493	0	28	1308	2.140673	0.2298	0	0	3402	0	0.364	0	2.12080	0.39510	0	2.56180	0.5288	0	0.4519	0.4477	0	2.3406	0.4048	1	7.47510	0.4314	1	3536	1464	1330	1279	3523	36.30429	0.8215	1	34	1223	2.780049	0.23780	0	321	1111	28.892889	0.75870	1	67	219	30.59361	0.2305	0	388	1330	29.17293	0.5075	0	306	2380	12.857143	0.6480	0	415	3496	11.870709	0.7535	1	547	15.46946	0.4760	0	982	27.77149	0.8327	1	729	2514	28.99761	0.9488	1	95	880	10.79545	0.3601	0	0	3394	0.0000000	0.09479	0	985	3536	27.85633	0.4608	0	1464	0	0.0000000	0.1079	0	364	24.8633880	0.9300	1	0	1330	0.0000000	0.09796	0	17	1330	1.278196	0.1463	0	0	3536	0.000000	0.1831	0	2.96830	0.6434	2	2.71239	0.6156	2	0.4608	0.4569	0	1.46526	0.08976	1	7.60675	0.4440	5	NA	NA	NA	NA

svi_divisional_lihtc20 <- svi_divisional_lihtc20 %>% 
  filter(is.na(pre10_lihtc_project_cnt)) %>% 
  filter(post10_lihtc_project_cnt >= 1) %>% 
  select(GEOID_2010_trt, pre10_lihtc_project_cnt, pre10_lihtc_project_dollars, post10_lihtc_project_cnt, post10_lihtc_project_dollars)

# View data
svi_divisional_lihtc20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars
34001001500	NA	NA	1	1497998
34001010600	NA	NA	1	1369830
34001011803	NA	NA	1	0
34003002200	NA	NA	1	0
34003007001	NA	NA	1	601714
34003013001	NA	NA	1	307351

svi_national_lihtc20 <- svi_national_lihtc20 %>% 
  filter(is.na(pre10_lihtc_project_cnt)) %>% 
  filter(post10_lihtc_project_cnt >= 1) %>% 
  select(GEOID_2010_trt, pre10_lihtc_project_cnt, pre10_lihtc_project_dollars, post10_lihtc_project_cnt, post10_lihtc_project_dollars)

# View data
svi_national_lihtc20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars
01003010500	NA	NA	1	481325
01003011601	NA	NA	1	887856
01017954600	NA	NA	2	950192
01021060101	NA	NA	1	812048
01039962600	NA	NA	1	434742
01043964900	NA	NA	1	1046201

# Filter SVI divisional data to remove all tracts that had a project in 2010 or before:
svi_divisional_lihtc <-  svi_divisional %>% 
  filter(! GEOID_2010_trt %in% lihtc_projects10$fips2010)

# Merge SVI divisional data with post 2010 project data, create flag for projects (1 for tracts that have LIHTC project, 0 for those that do not):
svi_divisional_lihtc <- left_join(svi_divisional_lihtc, 
                                  svi_divisional_lihtc20, 
                                  join_by("GEOID_2010_trt" == "GEOID_2010_trt")) %>% 
                        mutate(pre10_lihtc_project_cnt = replace_na(pre10_lihtc_project_cnt, 0),
                               post10_lihtc_project_cnt = replace_na(post10_lihtc_project_cnt, 0),
                               pre10_lihtc_project_dollars = replace_na(pre10_lihtc_project_dollars, 0),
                               post10_lihtc_project_dollars = replace_na(post10_lihtc_project_dollars, 0),
                               lihtc_flag = if_else(post10_lihtc_project_cnt >= 1, 1, 0))

# Finally, we want to filter our dataset to only have tracts that are eligible for the LIHTC program and that have SVI data:
svi_divisional_lihtc <- left_join(svi_divisional_lihtc, lihtc_eligible_flag, 
                                  join_by("GEOID_2010_trt" == "GEOID10")) %>%
                        filter(tolower(lihtc_eligibility) == "yes") %>%
                        filter(!is.na(F_TOTAL_10)) %>% 
                        filter(!is.na(F_TOTAL_20)) 


# View data
svi_divisional_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars	lihtc_flag	lihtc_eligibility
34001001400	34	001	001400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3736	1893	1503	2135	3736	57.14668	0.9592	1	411	1635	25.137615	0.9866	1	267	401	66.58354	0.9617	1	715	1102	64.88203	0.8844	1	982	1503	65.33599	0.9764	1	511	1696	30.129717	0.90050	1	527	4199	12.5506073	0.672800	0	269	7.200214	0.115100	0	1598	42.77302	0.9935	1	345	2252	15.319716	0.63090	0	787	941	83.63443	0.9990	1	63	3192	1.973684	0.54480	0	3463	3736	92.69272	0.8905	1	1893	427	22.556788	0.7770	1	0	0.000000	0.3251	0	22	1503	1.463739	0.5339	0	705	1503	46.90619	0.85330	1	0	3736	0.000000	0.3512	0	4.495500	0.9585	4	3.283300	0.8640	2	0.8905	0.8818	1	2.84050	0.66710	2	11.509800	0.9048	9	3812	1724	1549	2291	3754	61.028236	0.9760	1	380	1547	24.563672	0.9934	1	117	240	48.75000	0.9237	1	753	1309	57.52483	0.7816	1	870	1549	56.16527	0.9326	1	472	1913	24.673288	0.8987	1	294	3802	7.7327722	0.7558	1	363	9.52256	0.123100	0	1463	38.37880	0.9885	1	508	2339.000	21.718683	0.85640	1	564	948.000	59.49367	0.9910	1	201	3159	6.3627730	0.7613	1	3389	3812.000	88.90346	0.8683	1	1724	571	33.1206497	0.8294	1	0	0	0.3216	0	83	1549	5.358296	0.7754	1	661	1549.000	42.672692	0.8448	1	10	3812	0.2623295	0.4739	0	4.5565	0.9673	5	3.720300	0.9522	4	0.8683	0.8605	1	3.2451	0.81590	3	12.390200	0.9595	13	0	0	0	0	0	Yes
34001001500	34	001	001500	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	1074	901	752	656	1074	61.08007	0.9700	1	43	270	15.925926	0.9242	1	30	70	42.85714	0.7276	0	366	682	53.66569	0.6910	0	396	752	52.65957	0.8458	1	266	921	28.881650	0.88860	1	121	1064	11.3721805	0.613100	0	385	35.847300	0.990200	1	129	12.01117	0.0617	0	321	993	32.326284	0.98460	1	62	195	31.79487	0.8408	1	125	1050	11.904762	0.85620	1	965	1074	89.85102	0.8717	1	901	636	70.588235	0.9304	1	0	0.000000	0.3251	0	10	752	1.329787	0.5133	0	626	752	83.24468	0.98880	1	0	1074	0.000000	0.3512	0	4.241700	0.9134	4	3.733500	0.9515	4	0.8717	0.8632	1	3.10880	0.77090	2	11.955700	0.9362	11	1601	976	810	1001	1601	62.523423	0.9797	1	204	563	36.234458	0.9989	1	74	110	67.27273	0.9848	1	224	700	32.00000	0.2097	0	298	810	36.79012	0.6089	0	379	1145	33.100437	0.9610	1	272	1601	16.9893816	0.9572	1	451	28.16989	0.936300	1	251	15.67770	0.1835	0	411	1350.000	30.444444	0.97330	1	196	446.000	43.94619	0.9511	1	220	1532	14.3603133	0.8929	1	1435	1601.000	89.63148	0.8738	1	976	451	46.2090164	0.8742	1	0	0	0.3216	0	24	810	2.962963	0.6412	0	546	810.000	67.407407	0.9401	1	15	1601	0.9369144	0.6832	0	4.5057	0.9617	4	3.937100	0.9752	4	0.8738	0.8659	1	3.4603	0.87740	2	12.776900	0.9705	11	0	0	1	1497998	1	Yes
34001002400	34	001	002400	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	3129	1759	1375	1916	3129	61.23362	0.9705	1	205	1075	19.069767	0.9574	1	28	60	46.66667	0.7987	1	670	1315	50.95057	0.6297	0	698	1375	50.76364	0.8102	1	632	2059	30.694512	0.90660	1	461	2365	19.4926004	0.873700	1	539	17.225951	0.744100	0	850	27.16523	0.7907	1	575	1736	33.122120	0.98650	1	237	594	39.89899	0.9035	1	312	2663	11.716110	0.85490	1	2357	3129	75.32758	0.8038	1	1759	1091	62.023877	0.9176	1	29	1.648664	0.7742	1	57	1375	4.145454	0.7529	1	696	1375	50.61818	0.87140	1	209	3129	6.679450	0.9003	1	4.518400	0.9608	5	4.279700	0.9831	4	0.8038	0.7960	1	4.21640	0.98320	5	13.818300	0.9835	15	2614	1726	1217	1579	2612	60.451761	0.9744	1	290	1171	24.765158	0.9939	1	69	127	54.33071	0.9521	1	538	1090	49.35780	0.5970	0	607	1217	49.87675	0.8624	1	697	1998	34.884885	0.9695	1	551	2614	21.0788064	0.9797	1	516	19.73986	0.679400	0	503	19.24254	0.3999	0	576	2111.000	27.285647	0.95060	1	257	567.000	45.32628	0.9571	1	556	2368	23.4797297	0.9570	1	2029	2614.000	77.62050	0.8058	1	1726	1166	67.5550406	0.9204	1	0	0	0.3216	0	115	1217	9.449466	0.8840	1	673	1217.000	55.299918	0.8978	1	223	2614	8.5309870	0.9307	1	4.7799	0.9845	5	3.944000	0.9756	3	0.8058	0.7985	1	3.9545	0.96510	4	13.484200	0.9845	13	0	0	0	0	0	Yes
34003015400	34	003	015400	NJ	New Jersey	Bergen County	1	Northeast Region	2	Middle Atlantic Division	5086	2258	2100	1485	5063	29.33044	0.7447	0	195	2873	6.787330	0.4938	0	223	478	46.65272	0.7984	1	876	1622	54.00740	0.6974	0	1099	2100	52.33333	0.8405	1	640	3682	17.381858	0.70160	0	1579	6178	25.5584331	0.949900	1	603	11.856075	0.377400	0	961	18.89501	0.2410	0	534	5000	10.680000	0.31600	0	254	1232	20.61688	0.6975	0	681	4763	14.297712	0.88510	1	3916	5086	76.99567	0.8096	1	2258	1028	45.527015	0.8820	1	0	0.000000	0.3251	0	28	2100	1.333333	0.5139	0	643	2100	30.61905	0.76370	1	57	5086	1.120724	0.7485	0	3.730500	0.8072	2	2.517000	0.5136	1	0.8096	0.8017	1	3.23320	0.81730	2	10.290300	0.7914	6	7543	3570	3054	1638	7543	21.715498	0.6364	0	320	4251	7.527641	0.7462	0	238	752	31.64894	0.6832	0	1211	2302	52.60643	0.6776	0	1449	3054	47.44597	0.8252	1	877	5631	15.574498	0.7611	1	1093	7543	14.4902559	0.9339	1	981	13.00544	0.282700	0	1174	15.56410	0.1785	0	756	6369.000	11.869995	0.37380	0	303	2013.000	15.05216	0.5737	0	970	7103	13.6562016	0.8846	1	5610	7543.000	74.37359	0.7916	1	3570	1871	52.4089636	0.8898	1	0	0	0.3216	0	258	3054	8.447937	0.8637	1	301	3054.000	9.855927	0.5207	0	15	7543	0.1988599	0.4315	0	3.9028	0.8603	3	2.293300	0.3701	1	0.7916	0.7845	1	3.0273	0.73680	2	10.015000	0.7805	7	0	0	0	0	0	Yes
34003018100	34	003	018100	NJ	New Jersey	Bergen County	1	Northeast Region	2	Middle Atlantic Division	6907	2665	2569	1865	6863	27.17470	0.7140	0	242	3781	6.400423	0.4509	0	434	834	52.03837	0.8694	1	1123	1735	64.72622	0.8830	1	1557	2569	60.60724	0.9450	1	1521	4649	32.716713	0.92270	1	2703	7124	37.9421673	0.992200	1	1024	14.825539	0.598800	0	1336	19.34270	0.2674	0	452	5848	7.729138	0.11920	0	363	1614	22.49071	0.7280	0	1324	6571	20.149140	0.93510	1	4209	6907	60.93818	0.7551	1	2665	517	19.399625	0.7487	0	0	0.000000	0.3251	0	136	2569	5.293889	0.7960	1	1043	2569	40.59945	0.82350	1	0	6907	0.000000	0.3512	0	4.024800	0.8697	3	2.648500	0.5885	1	0.7551	0.7477	1	3.04450	0.74620	2	10.472900	0.8112	7	7668	2912	2816	1803	7664	23.525574	0.6750	0	370	4727	7.827375	0.7646	1	441	819	53.84615	0.9501	1	1122	1997	56.18428	0.7544	1	1563	2816	55.50426	0.9274	1	1879	5775	32.536797	0.9576	1	1695	7668	22.1048513	0.9829	1	1041	13.57590	0.316600	0	1193	15.55816	0.1784	0	711	6474.819	10.981001	0.31250	0	197	1914.175	10.29164	0.3928	0	2045	7161	28.5574640	0.9756	1	5637	7667.630	73.51685	0.7875	1	2912	806	27.6785714	0.7973	1	0	0	0.3216	0	150	2816	5.326704	0.7742	1	833	2816.042	29.580522	0.7679	1	10	7668	0.1304121	0.3642	0	4.3075	0.9336	4	2.175900	0.2971	1	0.7875	0.7803	1	3.0252	0.73590	3	10.296100	0.8061	9	0	0	0	0	0	Yes
34005702101	34	005	702101	NJ	New Jersey	Burlington County	1	Northeast Region	2	Middle Atlantic Division	1637	702	483	445	1637	27.18387	0.7142	0	63	456	13.815789	0.8857	1	0	0	NaN	NA	NA	222	483	45.96273	0.5037	0	222	483	45.96273	0.7085	0	31	903	3.433001	0.08742	0	14	1965	0.7124682	0.008765	0	0	0.000000	0.002836	0	696	42.51680	0.9928	1	62	898	6.904232	0.08018	0	103	452	22.78761	0.7331	0	0	1379	0.000000	0.07335	0	248	1637	15.14966	0.4224	0	702	25	3.561254	0.4247	0	0	0.000000	0.3251	0	0	483	0.000000	0.1459	0	0	483	0.00000	0.01044	0	0	1637	0.000000	0.3512	0	2.404585	0.4890	1	1.882266	0.1557	1	0.4224	0.4183	0	1.25734	0.03853	0	5.966591	0.2021	2	3997	1271	1235	304	3996	7.607608	0.1919	0	46	901	5.105438	0.5252	0	0	0	NaN	NA	NA	731	1235	59.19028	0.8107	1	731	1235	59.19028	0.9566	1	49	1973	2.483528	0.0993	0	27	3057	0.8832188	0.0568	0	0	0.00000	0.001592	0	1651	41.30598	0.9924	1	58	1412.011	4.107616	0.01556	0	91	1092.793	8.32729	0.3046	0	32	3347	0.9560801	0.3989	0	1411	3996.883	35.30251	0.5750	0	1271	10	0.7867821	0.2414	0	0	0	0.3216	0	27	1235	2.186235	0.5699	0	11	1234.974	0.890707	0.0533	0	0	3997	0.0000000	0.1517	0	1.8298	0.3066	1	1.713052	0.1034	1	0.5750	0.5698	0	1.3379	0.06021	0	5.455752	0.1329	2	0	0	0	0	0	Yes

# Filter SVI national data to remove all tracts that had a project in 2010 or before:
svi_national_lihtc <-  svi_national %>% 
  filter(! GEOID_2010_trt %in% lihtc_projects10$fips2010)

# Merge SVI national data with post 2010 project data, create flag for projects (1 for tracts that have LIHTC project, 0 for those that do not):
svi_national_lihtc <- left_join(svi_national_lihtc, 
                                  svi_national_lihtc20, 
                                  join_by("GEOID_2010_trt" == "GEOID_2010_trt")) %>% 
                        mutate(pre10_lihtc_project_cnt = replace_na(pre10_lihtc_project_cnt, 0),
                               post10_lihtc_project_cnt = replace_na(post10_lihtc_project_cnt, 0),
                                pre10_lihtc_project_dollars = replace_na(pre10_lihtc_project_dollars, 0),
                               post10_lihtc_project_dollars = replace_na(post10_lihtc_project_dollars, 0),
                               lihtc_flag = if_else(post10_lihtc_project_cnt >= 1, 1, 0))

# Finally, we want to filter our dataset to only have tracts that are eligible for the LIHTC program and that have SVI data:
svi_national_lihtc <- left_join(svi_national_lihtc, lihtc_eligible_flag, 
                                  join_by("GEOID_2010_trt" == "GEOID10")) %>%
                        filter(tolower(lihtc_eligibility) == "yes") %>%
                        filter(!is.na(F_TOTAL_10)) %>% 
                        filter(!is.na(F_TOTAL_20)) 


# View data
svi_national_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars	post10_lihtc_project_cnt	post10_lihtc_project_dollars	lihtc_flag	lihtc_eligibility
01005950700	01	005	950700	AL	Alabama	Barbour County	1	South Region	6	East South Central Division	1753	687	563	615	1628	37.77641	0.8088	1	17	667	2.548726	0.06941	0	41	376	10.90426	0.01945	0	62	187	33.15508	0.2464	0	103	563	18.29485	0.04875	0	264	1208	21.85430	0.7570	1	201	1527	13.163065	0.4991	0	368	20.992584	0.89510	1	462	26.354820	0.66130	0	211	1085	19.44700	0.7505	1	107	399	26.81704	0.8048	1	0	1628	0.000000	0.09298	0	861	1753	49.11580	0.7101	0	687	17	2.474527	0.4324	0	38	5.5312955	0.6970	0	3	563	0.5328597	0.3037	0	19	563	3.374778	0.3529	0	233	1753	13.29150	0.9517	1	2.18306	0.4137	2	3.20468	0.8377	3	0.7101	0.7035	0	2.7377	0.6100	1	8.83554	0.6264	6	1527	691	595	565	1365	41.39194	0.8765	1	37	572	6.468532	0.6776	0	70	376	18.617021	0.38590	0	92	219	42.00913	0.4736	0	162	595	27.22689	0.4454	0	280	1114	25.13465	0.8942	1	105	1378	7.619739	0.5505	0	383	25.081860	0.88450	1	337	22.069417	0.51380	0	237	1041.0000	22.76657	0.8360	1	144	413.0000	34.86683	0.9114	1	11	1466	0.7503411	0.40700	0	711	1527.0000	46.56189	0.6441	0	691	13	1.881331	0.3740	0	37	5.3545586	0.7152	0	0	595	0.0000000	0.09796	0	115	595.0000	19.327731	0.8859	1	149	1527	9.757695	0.9470	1	3.4442	0.7707	2	3.55270	0.9403	3	0.6441	0.6387	0	3.02006	0.7337	2	10.66106	0.8537	7	0	0	0	0	0	Yes
01011952100	01	011	952100	AL	Alabama	Bullock County	1	South Region	6	East South Central Division	1652	796	554	564	1652	34.14044	0.7613	1	46	816	5.637255	0.33630	0	96	458	20.96070	0.19930	0	62	96	64.58333	0.8917	1	158	554	28.51986	0.29220	0	271	1076	25.18587	0.8163	1	155	1663	9.320505	0.3183	0	199	12.046005	0.47180	0	420	25.423729	0.60240	0	327	1279	25.56685	0.9151	1	137	375	36.53333	0.9108	1	0	1590	0.000000	0.09298	0	1428	1652	86.44068	0.8939	1	796	0	0.000000	0.1224	0	384	48.2412060	0.9897	1	19	554	3.4296029	0.7145	0	45	554	8.122744	0.6556	0	0	1652	0.00000	0.3640	0	2.52440	0.5138	2	2.99308	0.7515	2	0.8939	0.8856	1	2.8462	0.6637	1	9.25758	0.6790	6	1382	748	549	742	1382	53.69030	0.9560	1	40	511	7.827789	0.7730	1	110	402	27.363184	0.71780	0	45	147	30.61224	0.2307	0	155	549	28.23315	0.4773	0	181	905	20.00000	0.8253	1	232	1382	16.787265	0.8813	1	164	11.866860	0.27170	0	250	18.089725	0.26290	0	258	1132.0000	22.79152	0.8368	1	99	279.0000	35.48387	0.9162	1	33	1275	2.5882353	0.64520	0	1347	1382.0000	97.46744	0.9681	1	748	0	0.000000	0.1079	0	375	50.1336898	0.9922	1	0	549	0.0000000	0.09796	0	37	549.0000	6.739526	0.6039	0	0	1382	0.000000	0.1831	0	3.9129	0.8785	4	2.93280	0.7342	2	0.9681	0.9599	1	1.98506	0.2471	1	9.79886	0.7570	8	0	0	0	0	0	Yes
01015000300	01	015	000300	AL	Alabama	Calhoun County	1	South Region	6	East South Central Division	3074	1635	1330	1904	3067	62.08021	0.9710	1	293	1362	21.512482	0.96630	1	180	513	35.08772	0.65450	0	383	817	46.87882	0.5504	0	563	1330	42.33083	0.70280	0	720	2127	33.85049	0.9148	1	628	2835	22.151675	0.8076	1	380	12.361744	0.49340	0	713	23.194535	0.45030	0	647	2111	30.64898	0.9708	1	298	773	38.55110	0.9247	1	0	2878	0.000000	0.09298	0	2623	3074	85.32856	0.8883	1	1635	148	9.051988	0.6465	0	6	0.3669725	0.4502	0	68	1330	5.1127820	0.8082	1	303	1330	22.781955	0.9029	1	0	3074	0.00000	0.3640	0	4.36250	0.9430	4	2.93218	0.7233	2	0.8883	0.8800	1	3.1718	0.8070	2	11.35478	0.9009	9	2390	1702	1282	1287	2390	53.84937	0.9566	1	102	1066	9.568480	0.8541	1	158	609	25.944171	0.67520	0	286	673	42.49629	0.4856	0	444	1282	34.63339	0.6634	0	467	1685	27.71513	0.9180	1	369	2379	15.510719	0.8562	1	342	14.309623	0.40850	0	548	22.928870	0.57100	0	647	1831.0000	35.33588	0.9862	1	202	576.0000	35.06944	0.9130	1	16	2134	0.7497657	0.40690	0	1896	2390.0000	79.33054	0.8451	1	1702	96	5.640423	0.5329	0	0	0.0000000	0.2186	0	0	1282	0.0000000	0.09796	0	186	1282.0000	14.508580	0.8308	1	43	2390	1.799163	0.7727	1	4.2483	0.9395	4	3.28560	0.8773	2	0.8451	0.8379	1	2.45296	0.4602	2	10.83196	0.8718	9	0	0	0	0	0	Yes
01015000500	01	015	000500	AL	Alabama	Calhoun County	1	South Region	6	East South Central Division	1731	1175	743	1042	1619	64.36072	0.9767	1	124	472	26.271186	0.98460	1	136	461	29.50108	0.48970	0	163	282	57.80142	0.7919	1	299	743	40.24226	0.64910	0	340	1270	26.77165	0.8389	1	460	1794	25.641026	0.8722	1	271	15.655690	0.70190	0	368	21.259388	0.32190	0	507	1449	34.98965	0.9885	1	150	386	38.86010	0.9269	1	0	1677	0.000000	0.09298	0	1559	1731	90.06355	0.9123	1	1175	50	4.255319	0.5128	0	4	0.3404255	0.4480	0	0	743	0.0000000	0.1238	0	122	743	16.419919	0.8473	1	0	1731	0.00000	0.3640	0	4.32150	0.9362	4	3.03218	0.7679	2	0.9123	0.9038	1	2.2959	0.3818	1	10.56188	0.8244	8	940	907	488	586	940	62.34043	0.9815	1	59	297	19.865320	0.9833	1	100	330	30.303030	0.79220	1	58	158	36.70886	0.3497	0	158	488	32.37705	0.6020	0	199	795	25.03145	0.8930	1	118	940	12.553192	0.7770	1	246	26.170213	0.90530	1	118	12.553192	0.08233	0	383	822.5089	46.56484	0.9984	1	30	197.8892	15.16000	0.5363	0	0	889	0.0000000	0.09479	0	898	940.3866	95.49264	0.9489	1	907	0	0.000000	0.1079	0	2	0.2205072	0.4456	0	2	488	0.4098361	0.23670	0	146	487.6463	29.939736	0.9404	1	0	940	0.000000	0.1831	0	4.2368	0.9379	4	2.61712	0.5593	2	0.9489	0.9409	1	1.91370	0.2196	1	9.71652	0.7468	8	0	0	0	0	0	Yes
01015000600	01	015	000600	AL	Alabama	Calhoun County	1	South Region	6	East South Central Division	2571	992	796	1394	2133	65.35396	0.9789	1	263	905	29.060773	0.98990	1	121	306	39.54248	0.75940	1	209	490	42.65306	0.4481	0	330	796	41.45729	0.68030	0	641	1556	41.19537	0.9554	1	416	1760	23.636364	0.8383	1	220	8.556982	0.24910	0	584	22.714897	0.41610	0	539	1353	39.83740	0.9955	1	243	466	52.14592	0.9783	1	30	2366	1.267963	0.48990	0	1944	2571	75.61260	0.8440	1	992	164	16.532258	0.7673	1	8	0.8064516	0.5110	0	46	796	5.7788945	0.8329	1	184	796	23.115578	0.9049	1	614	2571	23.88176	0.9734	1	4.44280	0.9548	4	3.12890	0.8088	2	0.8440	0.8362	1	3.9895	0.9792	4	12.40520	0.9696	11	1950	964	719	837	1621	51.63479	0.9467	1	157	652	24.079755	0.9922	1	22	364	6.043956	0.01547	0	129	355	36.33803	0.3420	0	151	719	21.00139	0.2303	0	363	1387	26.17159	0.9048	1	351	1613	21.760694	0.9435	1	249	12.769231	0.32090	0	356	18.256410	0.27140	0	332	1259.7041	26.35540	0.9135	1	136	435.6156	31.22018	0.8775	1	0	1891	0.0000000	0.09479	0	1463	1949.9821	75.02633	0.8219	1	964	14	1.452282	0.3459	0	8	0.8298755	0.5269	0	19	719	2.6425591	0.61120	0	197	719.0542	27.397100	0.9316	1	329	1950	16.871795	0.9655	1	4.0175	0.9001	4	2.47809	0.4764	2	0.8219	0.8149	1	3.38110	0.8712	2	10.69859	0.8583	9	0	0	0	0	0	Yes
01015002101	01	015	002101	AL	Alabama	Calhoun County	1	South Region	6	East South Central Division	3872	1454	1207	1729	2356	73.38710	0.9916	1	489	2020	24.207921	0.97860	1	20	168	11.90476	0.02541	0	718	1039	69.10491	0.9332	1	738	1207	61.14333	0.96900	1	113	725	15.58621	0.6035	0	664	3943	16.839970	0.6495	0	167	4.313016	0.05978	0	238	6.146694	0.02255	0	264	2359	11.19118	0.3027	0	94	263	35.74144	0.9050	1	46	3769	1.220483	0.48250	0	1601	3872	41.34814	0.6572	0	1454	761	52.338377	0.9504	1	65	4.4704264	0.6738	0	5	1207	0.4142502	0.2791	0	113	1207	9.362055	0.7004	0	1516	3872	39.15289	0.9860	1	4.19220	0.9133	3	1.77253	0.1304	1	0.6572	0.6511	0	3.5897	0.9337	2	10.21163	0.7885	6	3238	1459	1014	1082	1836	58.93246	0.9735	1	251	1403	17.890235	0.9767	1	31	155	20.000000	0.44920	0	515	859	59.95343	0.8554	1	546	1014	53.84615	0.9535	1	134	916	14.62882	0.7033	0	251	3238	7.751699	0.5588	0	167	5.157505	0.03597	0	169	5.219271	0.02111	0	323	1667.0000	19.37612	0.7205	0	94	277.0000	33.93502	0.9040	1	0	3164	0.0000000	0.09479	0	1045	3238.0000	32.27301	0.5125	0	1459	607	41.603838	0.9185	1	65	4.4551062	0.6949	0	24	1014	2.3668639	0.57900	0	85	1014.0000	8.382643	0.6775	0	1402	3238	43.298332	0.9876	1	4.1658	0.9263	3	1.77637	0.1225	1	0.5125	0.5082	0	3.85750	0.9661	2	10.31217	0.8160	6	0	0	0	0	0	Yes

svi_national_lihtc_county_sum <- summarize_county_lihtc(svi_national_lihtc)

svi_national_lihtc_county_sum %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_lihtc_project_cnt	tract_cnt	post10_lihtc_project_dollars	post10_lihtc_dollars_formatted
AK	Bethel Census Area	Pacific Division	0	2	0	\$0
AK	Dillingham Census Area	Pacific Division	0	1	0	\$0
AK	Kenai Peninsula Borough	Pacific Division	0	1	0	\$0
AK	Nome Census Area	Pacific Division	0	1	0	\$0
AK	Yukon-Koyukuk Census Area	Pacific Division	0	2	0	\$0
AL	Barbour County	East South Central Division	0	1	0	\$0

svi_divisional_lihtc_county_sum <- summarize_county_lihtc(svi_divisional_lihtc)
svi_divisional_lihtc_county_sum %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_lihtc_project_cnt	tract_cnt	post10_lihtc_project_dollars	post10_lihtc_dollars_formatted
NJ	Atlantic County	Middle Atlantic Division	1	3	1497998	\$1,497,998
NJ	Bergen County	Middle Atlantic Division	0	2	0	\$0
NJ	Burlington County	Middle Atlantic Division	0	2	0	\$0
NJ	Camden County	Middle Atlantic Division	1	6	0	\$0
NJ	Cape May County	Middle Atlantic Division	0	2	0	\$0
NJ	Cumberland County	Middle Atlantic Division	0	1	0	\$0

# Create data frame of LIHTC eligible tracts 2010 nationally
svi_national_lihtc10 <- svi_national_lihtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_10, E_TOTPOP_10) %>% rename("F_TOTAL" = "F_TOTAL_10")

# Count national-level SVI flags for 2010, create unified fips column
svi_2010_national_county_flags_lihtc <- flag_summarize(svi_national_lihtc10, "E_TOTPOP_10") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Add suffix to flag columns 2010
colnames(svi_2010_national_county_flags_lihtc)[11:15] <- paste0(colnames(svi_2010_national_county_flags_lihtc)[11:15], 10)

# Create data frame of LIHTC eligible tracts 2020 nationally
svi_national_lihtc20 <- svi_national_lihtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_20, E_TOTPOP_20) %>% rename("F_TOTAL" = "F_TOTAL_20")

# Count national-level SVI flags for 2020, create unified fips column
svi_2020_national_county_flags_lihtc <- flag_summarize(svi_national_lihtc20, "E_TOTPOP_20") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Identify needed columns for 2020, add suffix
colnames(svi_2020_national_county_flags_lihtc)[11:15] <- paste0(colnames(svi_2020_national_county_flags_lihtc)[11:15], "20")

# Filter to needed columns for 2020 to avoid duplicate column column names
svi_2020_national_county_flags_join_lihtc <- svi_2020_national_county_flags_lihtc %>% ungroup() %>% select("fips_county_st", all_of(colnames(svi_2020_national_county_flags_lihtc)[11:15]))
 
# Join 2010 and 2020 data
svi_national_county_flags_lihtc <- left_join(svi_2010_national_county_flags_lihtc, svi_2020_national_county_flags_join_lihtc, join_by("fips_county_st" == "fips_county_st")) 

svi_national_county_flags_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
01005	01	005	AL	Alabama	Barbour County	1	South Region	6	East South Central Division	6	1753	0.0034227	0.2	0.8	7	1527	0.0045842	0.2	1.0
01011	01	011	AL	Alabama	Bullock County	1	South Region	6	East South Central Division	6	1652	0.0036320	0.2	0.8	8	1382	0.0057887	0.4	1.0
01015	01	015	AL	Alabama	Calhoun County	1	South Region	6	East South Central Division	40	15130	0.0026438	0.8	0.6	37	11783	0.0031401	0.8	0.8
01023	01	023	AL	Alabama	Choctaw County	1	South Region	6	East South Central Division	12	5578	0.0021513	0.6	0.4	15	5412	0.0027716	0.6	0.8
01031	01	031	AL	Alabama	Coffee County	1	South Region	6	East South Central Division	12	8139	0.0014744	0.6	0.2	13	8517	0.0015264	0.6	0.2
01033	01	033	AL	Alabama	Colbert County	1	South Region	6	East South Central Division	10	1983	0.0050429	0.4	1.0	8	1931	0.0041429	0.4	1.0

svi_national_county_lihtc <- left_join(svi_national_lihtc_county_sum,
                                      svi_national_county_flags_lihtc,
                                    join_by("State" == "state", "County" == "county",
                                            "Division" == "division"))

svi_national_county_lihtc$post10_lihtc_project_cnt[is.na(svi_national_county_lihtc$post10_lihtc_project_cnt)] <- 0

svi_national_county_lihtc$county_name <- paste0(svi_national_county_lihtc$County, ", ", svi_national_county_lihtc$State)

svi_national_county_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_lihtc_project_cnt	tract_cnt	post10_lihtc_project_dollars	post10_lihtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name
AK	Bethel Census Area	Pacific Division	0	2	0	\$0	02050	02	050	Alaska	1	West Region	9	18	10867	0.0016564	0.6	0.4	20	11715	0.0017072	0.8	0.4	Bethel Census Area, AK
AK	Dillingham Census Area	Pacific Division	0	1	0	\$0	02070	02	070	Alaska	1	West Region	9	9	2569	0.0035033	0.4	0.8	10	2801	0.0035702	0.4	0.8	Dillingham Census Area, AK
AK	Kenai Peninsula Borough	Pacific Division	0	1	0	\$0	02122	02	122	Alaska	1	West Region	9	7	251	0.0278884	0.2	1.0	8	531	0.0150659	0.4	1.0	Kenai Peninsula Borough, AK
AK	Nome Census Area	Pacific Division	0	1	0	\$0	02180	02	180	Alaska	1	West Region	9	9	5766	0.0015609	0.4	0.2	10	5901	0.0016946	0.4	0.4	Nome Census Area, AK
AK	Yukon-Koyukuk Census Area	Pacific Division	0	2	0	\$0	02290	02	290	Alaska	1	West Region	9	18	2300	0.0078261	0.6	1.0	21	2153	0.0097538	0.8	1.0	Yukon-Koyukuk Census Area, AK
AL	Barbour County	East South Central Division	0	1	0	\$0	01005	01	005	Alabama	1	South Region	6	6	1753	0.0034227	0.2	0.8	7	1527	0.0045842	0.2	1.0	Barbour County, AL

# Create data frame of LIHTC eligible tracts 2020 nationally
svi_divisional_lihtc10 <- svi_divisional_lihtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_10, E_TOTPOP_10) %>% rename("F_TOTAL" = "F_TOTAL_10")

# Count divisional-level SVI flags for 2010, create unified fips column
svi_2010_divisional_county_flags_lihtc <- flag_summarize(svi_divisional_lihtc10, "E_TOTPOP_10") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Add suffix to flag columns 2010
colnames(svi_2010_divisional_county_flags_lihtc)[11:15] <- paste0(colnames(svi_2010_divisional_county_flags_lihtc)[11:15], "10")

# Create data frame of NMTC eligible tracts 2020 nationally
svi_divisional_lihtc20 <- svi_divisional_lihtc %>% select(GEOID_2010_trt, FIPS_st, FIPS_county, 
    state, state_name, county, region_number, region, division_number, 
    division, F_TOTAL_20, E_TOTPOP_20) %>% rename("F_TOTAL" = "F_TOTAL_20")

# Count divisional-level SVI flags for 2020, create unified fips column
svi_2020_divisional_county_flags_lihtc <- flag_summarize(svi_divisional_lihtc20, "E_TOTPOP_20") %>% unite("fips_county_st", FIPS_st:FIPS_county, remove = FALSE, sep="")

# Identify needed columns for 2020
colnames(svi_2020_divisional_county_flags_lihtc)[11:15] <- paste0(colnames(svi_2020_divisional_county_flags_lihtc)[11:15], "20")

# Filter to needed columns for 2020 to avoid duplicate column column names
svi_2020_divisional_county_flags_join_lihtc <- svi_2020_divisional_county_flags_lihtc %>% ungroup() %>% select("fips_county_st", all_of(colnames(svi_2020_divisional_county_flags_lihtc)[11:15]))
 
# Join 2010 and 2020 data
svi_divisional_county_flags_lihtc <- left_join(svi_2010_divisional_county_flags_lihtc, svi_2020_divisional_county_flags_join_lihtc, join_by("fips_county_st" == "fips_county_st")) 

svi_divisional_county_flags_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
34001	34	001	NJ	New Jersey	Atlantic County	1	Northeast Region	2	Middle Atlantic Division	35	7939	0.0044086	0.8	1.0	37	8027	0.0046094	0.8	1.0
34003	34	003	NJ	New Jersey	Bergen County	1	Northeast Region	2	Middle Atlantic Division	13	11993	0.0010840	0.6	0.2	16	15211	0.0010519	0.6	0.2
34005	34	005	NJ	New Jersey	Burlington County	1	Northeast Region	2	Middle Atlantic Division	11	4637	0.0023722	0.4	0.6	6	6493	0.0009241	0.2	0.2
34007	34	007	NJ	New Jersey	Camden County	1	Northeast Region	2	Middle Atlantic Division	72	22516	0.0031977	1.0	0.8	61	20790	0.0029341	0.8	0.8
34009	34	009	NJ	New Jersey	Cape May County	1	Northeast Region	2	Middle Atlantic Division	15	5839	0.0025689	0.6	0.8	10	5394	0.0018539	0.4	0.4
34011	34	011	NJ	New Jersey	Cumberland County	1	Northeast Region	2	Middle Atlantic Division	10	1053	0.0094967	0.4	1.0	10	801	0.0124844	0.4	1.0

svi_divisional_county_lihtc <- left_join(svi_divisional_lihtc_county_sum, 
                                        svi_divisional_county_flags_lihtc,
                                    join_by("State" == "state", "County" == "county",
                                            "Division" == "division"))

svi_divisional_county_lihtc$post10_lihtc_project_cnt[is.na(svi_divisional_county_lihtc $post10_lihtc_project_cnt)] <- 0

svi_divisional_county_lihtc$county_name <- paste0(svi_divisional_county_lihtc$County, ", ", svi_divisional_county_lihtc$State)

svi_divisional_county_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_lihtc_project_cnt	tract_cnt	post10_lihtc_project_dollars	post10_lihtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name
NJ	Atlantic County	Middle Atlantic Division	1	3	1497998	\$1,497,998	34001	34	001	New Jersey	1	Northeast Region	2	35	7939	0.0044086	0.8	1.0	37	8027	0.0046094	0.8	1.0	Atlantic County, NJ
NJ	Bergen County	Middle Atlantic Division	0	2	0	\$0	34003	34	003	New Jersey	1	Northeast Region	2	13	11993	0.0010840	0.6	0.2	16	15211	0.0010519	0.6	0.2	Bergen County, NJ
NJ	Burlington County	Middle Atlantic Division	0	2	0	\$0	34005	34	005	New Jersey	1	Northeast Region	2	11	4637	0.0023722	0.4	0.6	6	6493	0.0009241	0.2	0.2	Burlington County, NJ
NJ	Camden County	Middle Atlantic Division	1	6	0	\$0	34007	34	007	New Jersey	1	Northeast Region	2	72	22516	0.0031977	1.0	0.8	61	20790	0.0029341	0.8	0.8	Camden County, NJ
NJ	Cape May County	Middle Atlantic Division	0	2	0	\$0	34009	34	009	New Jersey	1	Northeast Region	2	15	5839	0.0025689	0.6	0.8	10	5394	0.0018539	0.4	0.4	Cape May County, NJ
NJ	Cumberland County	Middle Atlantic Division	0	1	0	\$0	34011	34	011	New Jersey	1	Northeast Region	2	10	1053	0.0094967	0.4	1.0	10	801	0.0124844	0.4	1.0	Cumberland County, NJ

Exploratory Data Analysis

NMTC in West South Central Division

svi_divisional_county_nmtc_projects <- svi_divisional_county_nmtc %>% filter(post10_nmtc_project_cnt > 0)

Data Summary

summary(svi_divisional_county_nmtc_projects$flag_count10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    5.00   54.75  134.50  399.71  346.00 3869.00

summary(svi_divisional_county_nmtc_projects$post10_nmtc_project_dollars)

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
##   1460000   7800000  16225000  51968192  41860000 550969964

• DESCRIPTION

# Scatterplot
# y is our independent variable (NMTC Project Dollars),  
# x is our dependent variable (SVI flag count)
ggplot2::ggplot(svi_divisional_county_nmtc_projects,
                aes(x=flag_count10,
                    y=post10_nmtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

## `geom_smooth()` using formula = 'y ~ x'

# Pearson's r calculation
cor(svi_divisional_county_nmtc_projects$flag_count10, svi_divisional_county_nmtc_projects$post10_nmtc_project_dollars, method = "pearson")

## [1] 0.7085789

• DESCRIPTION

boxplot(svi_divisional_county_nmtc_projects$flag_count10)

boxplot.stats(svi_divisional_county_nmtc_projects$flag_count10)$out %>% sort(decreasing = TRUE)

## [1] 3869 2688 2347 1961 1019  879  841

svi_divisional_county_nmtc_projects %>% 
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) %>% 
  arrange(desc(flag_count10)) %>% 
  head(7) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

county_name	flag_count10	post10_nmtc_dollars_formatted
Kings County, NY	3869	\$216,348,600
Bronx County, NY	2688	\$306,355,715
Queens County, NY	2347	\$85,225,100
Philadelphia County, PA	1961	\$550,969,964
Essex County, NJ	1019	\$81,662,084
New York County, NY	879	\$255,545,686
Hudson County, NJ	841	\$110,136,049

• DESCRIPTION

svi_divisional_nmtc_cluster <- svi_divisional_county_nmtc_projects %>% 
                            select(county_name, post10_nmtc_project_dollars, 
                                   flag_count10) %>% 
                            remove_rownames %>% 
                            column_to_rownames(var="county_name")

# Remove nulls, if in dataset
svi_divisional_nmtc_cluster <- na.omit(svi_divisional_nmtc_cluster)


# Scale numeric variables
svi_divisional_nmtc_cluster <- scale(svi_divisional_nmtc_cluster)


svi_divisional_nmtc_cluster %>% head(5)

##                       post10_nmtc_project_dollars flag_count10
## Bergen County, NJ                      -0.4296451   -0.3418568
## Camden County, NJ                       0.2835350   -0.0912361
## Cumberland County, NJ                  -0.1922645   -0.3526362
## Essex County, NJ                        0.3039882    0.8344437
## Hudson County, NJ                       0.5954875    0.5946023

K-Means Clustering

set.seed(123)
k2_nmtc_div <- kmeans(svi_divisional_nmtc_cluster, centers = 2, nstart = 25)
set.seed(123)
k3_nmtc_div <- kmeans(svi_divisional_nmtc_cluster, centers = 3, nstart = 25)
set.seed(123)
k4_nmtc_div <- kmeans(svi_divisional_nmtc_cluster, centers = 4, nstart = 25)
set.seed(123)
k5_nmtc_div <- kmeans(svi_divisional_nmtc_cluster, centers = 5, nstart = 25)

# plots to compare
p_k2_nmtc_div <- factoextra::fviz_cluster(k2_nmtc_div, geom = "point", data = svi_divisional_nmtc_cluster) + ggtitle("k = 2")

p_k3_nmtc_div <- factoextra::fviz_cluster(k3_nmtc_div, geom = "point", data = svi_divisional_nmtc_cluster) + ggtitle("k = 3")

p_k4_nmtc_div <- factoextra::fviz_cluster(k4_nmtc_div, geom = "point",  data = svi_divisional_nmtc_cluster) + ggtitle("k = 4")

p_k5_nmtc_div <- factoextra::fviz_cluster(k5_nmtc_div, geom = "point",  data = svi_divisional_nmtc_cluster) + ggtitle("k = 5")

grid.arrange(p_k2_nmtc_div, p_k3_nmtc_div, p_k4_nmtc_div, p_k5_nmtc_div, nrow = 2)

elbow_plot(svi_divisional_nmtc_cluster)

## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7
## [1] 8
## [1] 9
## [1] 10
## [1] 11
## [1] 12
## [1] 13
## [1] 14
## [1] 15

p_k2_nmtc_div <- factoextra::fviz_cluster(k2_nmtc_div, geom = "point", data = svi_divisional_nmtc_cluster) + ggtitle("k = 2")

p_k2_nmtc_div

• DESCRIPTION

svi_divisional_nmtc_cluster_label <- as.data.frame(svi_divisional_nmtc_cluster) %>%
                                  rownames_to_column(var = "county_name") %>%
                                  as_tibble() %>%
                                  mutate(cluster = k2_nmtc_div$cluster) %>%
                                  select(county_name, cluster)

svi_divisional_county_nmtc_projects2 <- left_join(svi_divisional_county_nmtc_projects, svi_divisional_nmtc_cluster_label, join_by(county_name == county_name))

# View county counts in each cluster
table(svi_divisional_county_nmtc_projects2$cluster)

## 
##  1  2 
##  6 46

# Cluster 1 Scatterplot
# y is our independent variable (NMTC Project Dollars),  
# x is our dependent variable (SVI flag count)

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 1) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_nmtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

## `geom_smooth()` using formula = 'y ~ x'

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 1) %>%
  select(flag_count10,post10_nmtc_project_dollars) %>%
  cor(method = "pearson")

##                             flag_count10 post10_nmtc_project_dollars
## flag_count10                    1.000000                   -0.114767
## post10_nmtc_project_dollars    -0.114767                    1.000000

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 1) %>%
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

county_name	flag_count10	post10_nmtc_dollars_formatted
Bronx County, NY	2688	\$306,355,715
Kings County, NY	3869	\$216,348,600
New York County, NY	879	\$255,545,686
Queens County, NY	2347	\$85,225,100
Allegheny County, PA	712	\$244,342,400
Philadelphia County, PA	1961	\$550,969,964

• DESCRIPTION

# Cluster 2 Scatterplot
# y is our independent variable (NMTC Project Dollars),  
# x is our dependent variable (SVI flag count)

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 2) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_nmtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

## `geom_smooth()` using formula = 'y ~ x'

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 2) %>%
  select(flag_count10,post10_nmtc_project_dollars) %>%
  cor(method = "pearson")

##                             flag_count10 post10_nmtc_project_dollars
## flag_count10                     1.00000                     0.72778
## post10_nmtc_project_dollars      0.72778                     1.00000

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 2) %>%
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

county_name	flag_count10	post10_nmtc_dollars_formatted
Bergen County, NJ	146	\$10,000,000
Camden County, NJ	332	\$79,664,200
Cumberland County, NJ	138	\$33,187,593
Essex County, NJ	1019	\$81,662,084
Hudson County, NJ	841	\$110,136,049
Mercer County, NJ	225	\$8,000,000
Middlesex County, NJ	226	\$48,700,000
Ocean County, NJ	163	\$1,900,000
Passaic County, NJ	447	\$49,154,956
Union County, NJ	344	\$20,700,000
Albany County, NY	85	\$9,625,000
Allegany County, NY	29	\$9,300,000
Broome County, NY	131	\$5,280,000
Cattaraugus County, NY	44	\$6,790,000
Cayuga County, NY	27	\$6,240,000
Chautauqua County, NY	76	\$39,360,000
Chenango County, NY	19	\$58,819,000
Columbia County, NY	14	\$9,700,000
Cortland County, NY	12	\$2,000,000
Erie County, NY	528	\$76,710,000
Monroe County, NY	574	\$19,998,000
Nassau County, NY	151	\$1,460,000
Onondaga County, NY	352	\$20,428,080
Rensselaer County, NY	78	\$7,020,000
Schenectady County, NY	68	\$11,595,000
St. Lawrence County, NY	75	\$1,920,000
Steuben County, NY	58	\$7,680,000
Tompkins County, NY	32	\$2,643,020
Westchester County, NY	424	\$39,580,000
Adams County, PA	5	\$14,161,000
Berks County, PA	219	\$7,840,000
Clearfield County, PA	44	\$26,360,000
Dauphin County, PA	140	\$32,123,500
Delaware County, PA	236	\$14,190,000
Erie County, PA	184	\$7,358,392
Jefferson County, PA	25	\$11,453,160
Lackawanna County, PA	107	\$19,075,000
Lancaster County, PA	114	\$12,514,500
Lebanon County, PA	38	\$5,335,000
Lycoming County, PA	55	\$25,440,000
Mercer County, PA	54	\$18,440,000
Mifflin County, PA	37	\$12,130,000
Northampton County, PA	86	\$18,260,000
Washington County, PA	76	\$12,760,000
Westmoreland County, PA	108	\$6,737,500
York County, PA	143	\$20,127,500

Here we can find that our correlation actually strengthened, indicating that the majority of our data points are in line with the trends of the overall data.

In addition, it seems the amount of money given to counties in the Middle Atlantic Division with 0 - 1,000 SVI flags is correlated with NMTC dollars from $0 to just over $90 million.

Thus, we can conclude here that for the majority of the counties in the Middle Atlantic Division, there’s a fairly strong positive correlation between more vulnerable counties receiving more NMTC money than less vulnerable counties.

Bivariate Mapping

divisional_county_sf <- svi_county_map2010 %>% select(COUNTYFP, STATEFP, geometry)

divisional_county_sf %>% head(5)

## Simple feature collection with 5 features and 2 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -75.14001 ymin: 38.92852 xmax: -73.89398 ymax: 41.13419
## Geodetic CRS:  NAD83
##   COUNTYFP STATEFP                       geometry
## 1      001      34 MULTIPOLYGON (((-74.42314 3...
## 2      003      34 MULTIPOLYGON (((-73.92676 4...
## 3      005      34 MULTIPOLYGON (((-74.99056 4...
## 4      007      34 MULTIPOLYGON (((-75.14001 3...
## 5      009      34 MULTIPOLYGON (((-74.94545 3...

# Join our NMTC projects data with our shapefile geocoordinates
svi_divisional_county_nmtc_sf <- left_join(svi_divisional_county_nmtc_projects, divisional_county_sf, join_by("FIPS_st" == "STATEFP", "FIPS_county" == "COUNTYFP"))

svi_divisional_county_nmtc_sf %>% head(5) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name	geometry
NJ	Bergen County	Middle Atlantic Division	1	30	10000000	\$10,000,000	34003	34	003	New Jersey	1	Northeast Region	2	146	143973	0.0010141	1.0	0.4	165	154365	0.0010689	1.0	0.4	Bergen County, NJ	MULTIPOLYGON (((-73.92676 4…
NJ	Camden County	Middle Atlantic Division	5	47	79664200	\$79,664,200	34007	34	007	New Jersey	1	Northeast Region	2	332	183630	0.0018080	1.0	1.0	315	180659	0.0017436	1.0	0.8	Camden County, NJ	MULTIPOLYGON (((-75.14001 3…
NJ	Cumberland County	Middle Atlantic Division	2	21	33187593	\$33,187,593	34011	34	011	New Jersey	1	Northeast Region	2	138	101151	0.0013643	0.8	0.6	135	97989	0.0013777	0.8	0.6	Cumberland County, NJ	MULTIPOLYGON (((-75.1145 39…
NJ	Essex County	Middle Atlantic Division	6	115	81662084	\$81,662,084	34013	34	013	New Jersey	1	Northeast Region	2	1019	385872	0.0026408	1.0	1.0	1039	385359	0.0026962	1.0	1.0	Essex County, NJ	MULTIPOLYGON (((-74.13892 4…
NJ	Hudson County	Middle Atlantic Division	5	100	110136049	\$110,136,049	34017	34	017	New Jersey	1	Northeast Region	2	841	385737	0.0021802	1.0	1.0	802	404100	0.0019847	1.0	1.0	Hudson County, NJ	MULTIPOLYGON (((-74.02039 4…

# Create classes for bivariate mapping 
svi_divisional_county_nmtc_sf <- bi_class(svi_divisional_county_nmtc_sf, x = flag_count10, y = post10_nmtc_project_dollars, style = "quantile", dim = 3)

# View data
svi_divisional_county_nmtc_sf %>% head(5) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name	geometry	bi_class
NJ	Bergen County	Middle Atlantic Division	1	30	10000000	\$10,000,000	34003	34	003	New Jersey	1	Northeast Region	2	146	143973	0.0010141	1.0	0.4	165	154365	0.0010689	1.0	0.4	Bergen County, NJ	MULTIPOLYGON (((-73.92676 4…	2-2
NJ	Camden County	Middle Atlantic Division	5	47	79664200	\$79,664,200	34007	34	007	New Jersey	1	Northeast Region	2	332	183630	0.0018080	1.0	1.0	315	180659	0.0017436	1.0	0.8	Camden County, NJ	MULTIPOLYGON (((-75.14001 3…	3-3
NJ	Cumberland County	Middle Atlantic Division	2	21	33187593	\$33,187,593	34011	34	011	New Jersey	1	Northeast Region	2	138	101151	0.0013643	0.8	0.6	135	97989	0.0013777	0.8	0.6	Cumberland County, NJ	MULTIPOLYGON (((-75.1145 39…	2-3
NJ	Essex County	Middle Atlantic Division	6	115	81662084	\$81,662,084	34013	34	013	New Jersey	1	Northeast Region	2	1019	385872	0.0026408	1.0	1.0	1039	385359	0.0026962	1.0	1.0	Essex County, NJ	MULTIPOLYGON (((-74.13892 4…	3-3
NJ	Hudson County	Middle Atlantic Division	5	100	110136049	\$110,136,049	34017	34	017	New Jersey	1	Northeast Region	2	841	385737	0.0021802	1.0	1.0	802	404100	0.0019847	1.0	1.0	Hudson County, NJ	MULTIPOLYGON (((-74.02039 4…	3-3

# Create map with ggplot
svi_divisional_county_nmtc_map <- ggplot() +
  # Map county shapefile, fill with bi_class categories
  geom_sf(data = svi_divisional_county_nmtc_sf, mapping = aes(geometry=geometry, fill = bi_class), color = "white", size = 0.1, show.legend = FALSE) +
  # Set to biscale palette
  bi_scale_fill(pal = "GrPink", dim = 3) +
  # Add state shapefiles for outline
  geom_sf(data=divisional_st_sf, color="black", fill=NA, linewidth=.5, aes(geometry=geometry)) +
  labs(
    title = paste0("Correlation of 2010 ", census_division, " SVI Flag Count \n and 2011 - 2020 NMTC Tax Dollars"),
  ) +
  # Set them to biscale
  bi_theme(base_size = 10)

# Create biscale legend
svi_divisional_county_nmtc_legend <- bi_legend(pal = "GrPink",
                    dim = 3,
                    xlab = "SVI Flag Count",
                    ylab = "NMTC Dollars",
                    size = 8)

# Combine map with legend using cowplot
svi_divisional_county_nmtc_bivarmap <- ggdraw() +
  draw_plot(svi_divisional_county_nmtc_map) +
  # Set legend location
  draw_plot(svi_divisional_county_nmtc_legend, x= -.02,  y = -.05,
 width=.20)


# View map
svi_divisional_county_nmtc_bivarmap

An analysis of the bivariate map above displays that our high NMTC dollars and high SVI flag counts are largely clustered in the NYC metro area across NY and NJ.

In contrast, on a divisional level PA has several counties with low SVI flag counts, but moderate-to-high NMTC dollars.

svi_divisional_county_nmtc_sf %>% filter(State %in% c("NY", "NJ")) %>% select(State, County, flag_count10, post10_nmtc_dollars_formatted) %>% arrange(desc(flag_count10)) %>% head(6) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	flag_count10	post10_nmtc_dollars_formatted
NY	Kings County	3869	\$216,348,600
NY	Bronx County	2688	\$306,355,715
NY	Queens County	2347	\$85,225,100
NJ	Essex County	1019	\$81,662,084
NY	New York County	879	\$255,545,686
NJ	Hudson County	841	\$110,136,049

[INCLUDE TEXT]

svi_divisional_county_nmtc_sf %>% filter(State == "PA") %>%
  arrange(desc(post10_nmtc_project_dollars), flag_count10) %>% select(State, County, flag_count10, post10_nmtc_dollars_formatted) %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

State	County	flag_count10	post10_nmtc_dollars_formatted
PA	Philadelphia County	1961	\$550,969,964
PA	Allegheny County	712	\$244,342,400
PA	Dauphin County	140	\$32,123,500
PA	Clearfield County	44	\$26,360,000
PA	Lycoming County	55	\$25,440,000
PA	York County	143	\$20,127,500
PA	Lackawanna County	107	\$19,075,000
PA	Mercer County	54	\$18,440,000
PA	Northampton County	86	\$18,260,000
PA	Delaware County	236	\$14,190,000

LIHTC in West South Central Division

• Complete LIHTC analysis same as NMTC above

Data Summary

• CONTENT

K-Means Clustering

• CONTENT

Bivariate Mapping

• CONTENT