Visualizing the Intervention

knitr::opts_chunk$set(echo=TRUE)

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

Fuctions

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_gregorio.R"),
             .character_only = TRUE)

census_division

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	3	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	3	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	3	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	3	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	3	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	3	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%")

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
19001960100	19	001	960100	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2884	1338	1236	539	2816	19.14062	0.4820	0	93	1401	6.638116	0.6255	0	224	936	23.93162	0.57760	0	73	300	24.33333	0.20520	0	297	1236	24.02913	0.3735	0	158	1907	8.285265	0.3951	0	186	2846	6.535488	0.2577	0	536	18.58530	0.7701	1	758	26.28294	0.67210	0	410	2145	19.11422	0.7762	1	42	724	5.801105	0.11950	0	13	2677	0.4856182	0.4788	0	96	2884	3.328710	0.187900	0	1338	16	1.195815	0.33640	0	84	6.278027	0.7024	0	8	1236	0.6472492	0.4057	0	65	1236	5.2588997	0.57460	0	0	2884	0.0000000	0.3161	0	2.1338	0.4110	0	2.81670	0.6738	2	0.187900	0.187100	0	2.33520	0.40420	0	7.473600	0.43770	2
19001960200	19	001	960200	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	1690	906	781	308	1687	18.25726	0.4539	0	24	765	3.137255	0.1987	0	128	612	20.91503	0.42150	0	20	169	11.83432	0.05249	0	148	781	18.95006	0.1440	0	113	1402	8.059914	0.3805	0	101	1657	6.095353	0.2238	0	504	29.82249	0.9861	1	227	13.43195	0.04009	0	181	1415	12.79152	0.3762	0	17	544	3.125000	0.03416	0	8	1619	0.4941322	0.4824	0	0	1690	0.000000	0.002375	0	906	0	0.000000	0.09728	0	15	1.655629	0.4939	0	0	781	0.0000000	0.1372	0	6	781	0.7682458	0.08454	0	0	1690	0.0000000	0.3161	0	1.4009	0.1820	0	1.91895	0.1953	1	0.002375	0.002365	0	1.12902	0.03538	0	4.451245	0.05014	1
19001960300	19	001	960300	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	3205	1523	1392	584	3190	18.30721	0.4554	0	62	1530	4.052288	0.3222	0	143	1035	13.81643	0.08324	0	121	357	33.89356	0.39390	0	264	1392	18.96552	0.1444	0	196	2137	9.171736	0.4529	0	185	2996	6.174900	0.2305	0	685	21.37285	0.8761	1	833	25.99064	0.64730	0	341	2244	15.19608	0.5466	0	122	898	13.585746	0.54670	0	28	3006	0.9314704	0.6354	0	88	3205	2.745710	0.141200	0	1523	39	2.560735	0.43990	0	21	1.378858	0.4757	0	35	1392	2.5143678	0.7801	1	64	1392	4.5977011	0.52110	0	1	3205	0.0312012	0.6321	0	1.6054	0.2392	0	3.25210	0.8582	1	0.141200	0.140600	0	2.84890	0.66750	1	7.847600	0.49570	2
19003950100	19	003	950100	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	1745	777	690	231	1745	13.23782	0.2822	0	21	911	2.305159	0.1070	0	162	611	26.51391	0.69260	0	7	79	8.86076	0.03499	0	169	690	24.49275	0.3946	0	58	1230	4.715447	0.1855	0	118	1754	6.727480	0.2748	0	325	18.62464	0.7720	1	391	22.40688	0.35680	0	182	1363	13.35290	0.4165	0	35	528	6.628788	0.16210	0	1	1630	0.0613497	0.2495	0	46	1745	2.636103	0.133600	0	777	0	0.000000	0.09728	0	9	1.158301	0.4544	0	14	690	2.0289855	0.7187	0	2	690	0.2898551	0.04336	0	0	1745	0.0000000	0.3161	0	1.2441	0.1398	0	1.95690	0.2121	1	0.133600	0.133000	0	1.62984	0.12170	0	4.964440	0.08609	1
19003950200	19	003	950200	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	2382	1214	1074	674	2324	29.00172	0.7484	0	43	1148	3.745645	0.2825	0	142	782	18.15857	0.26460	0	107	292	36.64384	0.45600	0	249	1074	23.18436	0.3296	0	276	1794	15.384615	0.7587	1	194	2184	8.882784	0.4311	0	554	23.25777	0.9211	1	442	18.55584	0.13700	0	334	1742	19.17336	0.7794	1	81	583	13.893653	0.56290	0	0	2296	0.0000000	0.1215	0	89	2382	3.736356	0.219300	0	1214	32	2.635914	0.44560	0	59	4.859967	0.6514	0	27	1074	2.5139665	0.7799	1	72	1074	6.7039106	0.67020	0	183	2382	7.6826196	0.9039	1	2.5503	0.5413	1	2.52190	0.5177	2	0.219300	0.218400	0	3.45100	0.90270	2	8.742500	0.62730	5
19005960100	19	005	960100	IA	Iowa	Allamakee County	2	Midwest Region	4	West North Central Division	1925	1300	855	490	1841	26.61597	0.6979	0	140	921	15.200869	0.9411	1	178	766	23.23760	0.54090	0	27	89	30.33708	0.31820	0	205	855	23.97661	0.3711	0	127	1463	8.680793	0.4200	0	123	1942	6.333677	0.2424	0	462	24.00000	0.9339	1	323	16.77922	0.08797	0	230	1592	14.44724	0.4949	0	44	568	7.746479	0.22210	0	0	1875	0.0000000	0.1215	0	67	1925	3.480520	0.198700	0	1300	17	1.307692	0.34630	0	228	17.538462	0.9243	1	0	855	0.0000000	0.1372	0	48	855	5.6140351	0.60160	0	84	1925	4.3636364	0.8368	1	2.6725	0.5813	1	1.86037	0.1712	1	0.198700	0.197900	0	2.84620	0.66580	2	7.577770	0.45450	4

Load 2020 SVI 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	3	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	3	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	3	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	3	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	3	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	3	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%")

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
19001960100	19	001	960100	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2696	1321	1147	446	2620	17.02290	0.4674	0	57	1327	4.295403	0.6347	0	82	805	10.18634	0.1094	0	91	342	26.60819	0.27250	0	173	1147	15.08282	0.1312	0	98	1915	5.117494	0.3416	0	96	2634	3.644647	0.2718	0	470	17.43323	0.5283	0	681	25.25964	0.67830	0	468	1953.000	23.96313	0.8975	1	108	802.0000	13.466334	0.5180	0	2	2480	0.0806452	0.2987	0	184	2696.000	6.824926	0.25140	0	1321	23	1.741105	0.3456	0	53	4.012112	0.6591	0	8	1147	0.6974717	0.36640	0	23	1147.0000	2.0052310	0.2452	0	70	2696	2.5964392	0.7626	1	1.8467	0.3101	0	2.92080	0.7307	1	0.25140	0.25050	0	2.37890	0.4180	1	7.39780	0.4108	2
19001960200	19	001	960200	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	1591	831	675	333	1586	20.99622	0.5984	0	73	880	8.295454	0.8994	1	61	552	11.05072	0.1443	0	23	123	18.69919	0.13460	0	84	675	12.44444	0.0521	0	55	1207	4.556752	0.2930	0	41	1591	2.576996	0.1604	0	397	24.95286	0.8937	1	323	20.30170	0.28690	0	209	1268.000	16.48265	0.6031	0	37	514.9999	7.184467	0.1910	0	0	1501	0.0000000	0.1327	0	70	1591.000	4.399749	0.12080	0	831	0	0.000000	0.0847	0	23	2.767750	0.5935	0	6	675	0.8888889	0.42290	0	20	674.9999	2.9629634	0.3631	0	0	1591	0.0000000	0.1414	0	2.0033	0.3589	1	2.10740	0.2795	1	0.12080	0.12030	0	1.60560	0.1332	0	5.83710	0.1811	2
19001960300	19	001	960300	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2761	1557	1395	609	2680	22.72388	0.6444	0	85	1424	5.969101	0.7924	1	149	893	16.68533	0.4990	0	100	502	19.92032	0.14970	0	249	1395	17.84946	0.2643	0	100	1979	5.053057	0.3352	0	178	2687	6.624488	0.5488	0	710	25.71532	0.9134	1	503	18.21804	0.17430	0	308	2184.000	14.10256	0.4324	0	119	701.0001	16.975747	0.6508	0	0	2665	0.0000000	0.1327	0	77	2761.000	2.788844	0.04330	0	1557	66	4.238921	0.4935	0	24	1.541426	0.5095	0	2	1395	0.1433692	0.21350	0	50	1395.0001	3.5842292	0.4306	0	74	2761	2.6801883	0.7695	1	2.5851	0.5487	1	2.30360	0.3833	1	0.04330	0.04314	0	2.41660	0.4361	1	7.34860	0.4009	3
19003950100	19	003	950100	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	1616	835	704	315	1616	19.49257	0.5546	0	20	799	2.503129	0.3503	0	123	607	20.26359	0.7262	0	22	97	22.68041	0.19570	0	145	704	20.59659	0.4132	0	54	1146	4.712042	0.3048	0	172	1616	10.643564	0.7664	1	344	21.28713	0.7518	1	348	21.53465	0.38090	0	234	1268.000	18.45426	0.7099	0	45	483.0000	9.316770	0.3080	0	0	1486	0.0000000	0.1327	0	36	1616.000	2.227723	0.02773	0	835	0	0.000000	0.0847	0	48	5.748503	0.7266	0	4	704	0.5681818	0.31830	0	6	704.0000	0.8522727	0.1052	0	5	1616	0.3094059	0.4088	0	2.3893	0.4890	1	2.28330	0.3701	1	0.02773	0.02763	0	1.64360	0.1455	0	6.34393	0.2477	2
19003950200	19	003	950200	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	2017	1176	923	373	1939	19.23672	0.5455	0	43	965	4.455959	0.6531	0	115	708	16.24294	0.4644	0	30	215	13.95349	0.07616	0	145	923	15.70964	0.1595	0	123	1504	8.178192	0.5864	0	64	1957	3.270312	0.2338	0	492	24.39266	0.8773	1	399	19.78185	0.25290	0	276	1558.000	17.71502	0.6695	0	44	526.0000	8.365019	0.2549	0	5	1932	0.2587992	0.4007	0	101	2017.000	5.007437	0.15670	0	1176	16	1.360544	0.3160	0	31	2.636054	0.5846	0	8	923	0.8667389	0.41620	0	60	923.0000	6.5005417	0.6597	0	130	2017	6.4452157	0.9140	1	2.1783	0.4184	0	2.45530	0.4673	1	0.15670	0.15610	0	2.89050	0.6683	1	7.68080	0.4534	2
19005960100	19	005	960100	IA	Iowa	Allamakee County	2	Midwest Region	4	West North Central Division	1952	1507	1006	385	1894	20.32735	0.5771	0	28	1021	2.742409	0.3986	0	268	768	34.89583	0.9800	1	70	237	29.53587	0.33660	0	338	1005	33.63184	0.8465	1	91	1549	5.874758	0.4071	0	46	1906	2.413431	0.1475	0	592	30.32787	0.9768	1	265	13.57582	0.05754	0	237	1641.126	14.44131	0.4573	0	56	570.1656	9.821708	0.3375	0	0	1885	0.0000000	0.1327	0	104	1951.984	5.327911	0.17410	0	1507	88	5.839416	0.5589	0	204	13.536828	0.9002	1	0	1006	0.0000000	0.09916	0	26	1005.8033	2.5849984	0.3196	0	44	1952	2.2540984	0.7328	0	2.3768	0.4857	1	1.96184	0.2068	1	0.17410	0.17350	0	2.61066	0.5302	1	7.12340	0.3629	3

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%")

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
19001960100	19	001	960100	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2884	1338	1236	539	2816	19.14062	0.4820	0	93	1401	6.638116	0.6255	0	224	936	23.93162	0.57760	0	73	300	24.33333	0.20520	0	297	1236	24.02913	0.3735	0	158	1907	8.285265	0.3951	0	186	2846	6.535488	0.2577	0	536	18.58530	0.7701	1	758	26.28294	0.67210	0	410	2145	19.11422	0.7762	1	42	724	5.801105	0.11950	0	13	2677	0.4856182	0.4788	0	96	2884	3.328710	0.187900	0	1338	16	1.195815	0.33640	0	84	6.278027	0.7024	0	8	1236	0.6472492	0.4057	0	65	1236	5.2588997	0.57460	0	0	2884	0.0000000	0.3161	0	2.1338	0.4110	0	2.81670	0.6738	2	0.187900	0.187100	0	2.33520	0.40420	0	7.473600	0.43770	2	2696	1321	1147	446	2620	17.02290	0.4674	0	57	1327	4.295403	0.6347	0	82	805	10.18634	0.1094	0	91	342	26.60819	0.27250	0	173	1147	15.08282	0.1312	0	98	1915	5.117494	0.3416	0	96	2634	3.644647	0.2718	0	470	17.43323	0.5283	0	681	25.25964	0.67830	0	468	1953.000	23.96313	0.8975	1	108	802.0000	13.466334	0.5180	0	2	2480	0.0806452	0.2987	0	184	2696.000	6.824926	0.25140	0	1321	23	1.741105	0.3456	0	53	4.012112	0.6591	0	8	1147	0.6974717	0.36640	0	23	1147.0000	2.0052310	0.2452	0	70	2696	2.5964392	0.7626	1	1.8467	0.3101	0	2.92080	0.7307	1	0.25140	0.25050	0	2.37890	0.4180	1	7.39780	0.4108	2
19001960200	19	001	960200	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	1690	906	781	308	1687	18.25726	0.4539	0	24	765	3.137255	0.1987	0	128	612	20.91503	0.42150	0	20	169	11.83432	0.05249	0	148	781	18.95006	0.1440	0	113	1402	8.059914	0.3805	0	101	1657	6.095353	0.2238	0	504	29.82249	0.9861	1	227	13.43195	0.04009	0	181	1415	12.79152	0.3762	0	17	544	3.125000	0.03416	0	8	1619	0.4941322	0.4824	0	0	1690	0.000000	0.002375	0	906	0	0.000000	0.09728	0	15	1.655629	0.4939	0	0	781	0.0000000	0.1372	0	6	781	0.7682458	0.08454	0	0	1690	0.0000000	0.3161	0	1.4009	0.1820	0	1.91895	0.1953	1	0.002375	0.002365	0	1.12902	0.03538	0	4.451245	0.05014	1	1591	831	675	333	1586	20.99622	0.5984	0	73	880	8.295454	0.8994	1	61	552	11.05072	0.1443	0	23	123	18.69919	0.13460	0	84	675	12.44444	0.0521	0	55	1207	4.556752	0.2930	0	41	1591	2.576996	0.1604	0	397	24.95286	0.8937	1	323	20.30170	0.28690	0	209	1268.000	16.48265	0.6031	0	37	514.9999	7.184467	0.1910	0	0	1501	0.0000000	0.1327	0	70	1591.000	4.399749	0.12080	0	831	0	0.000000	0.0847	0	23	2.767750	0.5935	0	6	675	0.8888889	0.42290	0	20	674.9999	2.9629634	0.3631	0	0	1591	0.0000000	0.1414	0	2.0033	0.3589	1	2.10740	0.2795	1	0.12080	0.12030	0	1.60560	0.1332	0	5.83710	0.1811	2
19001960300	19	001	960300	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	3205	1523	1392	584	3190	18.30721	0.4554	0	62	1530	4.052288	0.3222	0	143	1035	13.81643	0.08324	0	121	357	33.89356	0.39390	0	264	1392	18.96552	0.1444	0	196	2137	9.171736	0.4529	0	185	2996	6.174900	0.2305	0	685	21.37285	0.8761	1	833	25.99064	0.64730	0	341	2244	15.19608	0.5466	0	122	898	13.585746	0.54670	0	28	3006	0.9314704	0.6354	0	88	3205	2.745710	0.141200	0	1523	39	2.560735	0.43990	0	21	1.378858	0.4757	0	35	1392	2.5143678	0.7801	1	64	1392	4.5977011	0.52110	0	1	3205	0.0312012	0.6321	0	1.6054	0.2392	0	3.25210	0.8582	1	0.141200	0.140600	0	2.84890	0.66750	1	7.847600	0.49570	2	2761	1557	1395	609	2680	22.72388	0.6444	0	85	1424	5.969101	0.7924	1	149	893	16.68533	0.4990	0	100	502	19.92032	0.14970	0	249	1395	17.84946	0.2643	0	100	1979	5.053057	0.3352	0	178	2687	6.624488	0.5488	0	710	25.71532	0.9134	1	503	18.21804	0.17430	0	308	2184.000	14.10256	0.4324	0	119	701.0001	16.975747	0.6508	0	0	2665	0.0000000	0.1327	0	77	2761.000	2.788844	0.04330	0	1557	66	4.238921	0.4935	0	24	1.541426	0.5095	0	2	1395	0.1433692	0.21350	0	50	1395.0001	3.5842292	0.4306	0	74	2761	2.6801883	0.7695	1	2.5851	0.5487	1	2.30360	0.3833	1	0.04330	0.04314	0	2.41660	0.4361	1	7.34860	0.4009	3
19003950100	19	003	950100	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	1745	777	690	231	1745	13.23782	0.2822	0	21	911	2.305159	0.1070	0	162	611	26.51391	0.69260	0	7	79	8.86076	0.03499	0	169	690	24.49275	0.3946	0	58	1230	4.715447	0.1855	0	118	1754	6.727480	0.2748	0	325	18.62464	0.7720	1	391	22.40688	0.35680	0	182	1363	13.35290	0.4165	0	35	528	6.628788	0.16210	0	1	1630	0.0613497	0.2495	0	46	1745	2.636103	0.133600	0	777	0	0.000000	0.09728	0	9	1.158301	0.4544	0	14	690	2.0289855	0.7187	0	2	690	0.2898551	0.04336	0	0	1745	0.0000000	0.3161	0	1.2441	0.1398	0	1.95690	0.2121	1	0.133600	0.133000	0	1.62984	0.12170	0	4.964440	0.08609	1	1616	835	704	315	1616	19.49257	0.5546	0	20	799	2.503129	0.3503	0	123	607	20.26359	0.7262	0	22	97	22.68041	0.19570	0	145	704	20.59659	0.4132	0	54	1146	4.712042	0.3048	0	172	1616	10.643564	0.7664	1	344	21.28713	0.7518	1	348	21.53465	0.38090	0	234	1268.000	18.45426	0.7099	0	45	483.0000	9.316770	0.3080	0	0	1486	0.0000000	0.1327	0	36	1616.000	2.227723	0.02773	0	835	0	0.000000	0.0847	0	48	5.748503	0.7266	0	4	704	0.5681818	0.31830	0	6	704.0000	0.8522727	0.1052	0	5	1616	0.3094059	0.4088	0	2.3893	0.4890	1	2.28330	0.3701	1	0.02773	0.02763	0	1.64360	0.1455	0	6.34393	0.2477	2
19003950200	19	003	950200	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	2382	1214	1074	674	2324	29.00172	0.7484	0	43	1148	3.745645	0.2825	0	142	782	18.15857	0.26460	0	107	292	36.64384	0.45600	0	249	1074	23.18436	0.3296	0	276	1794	15.384615	0.7587	1	194	2184	8.882784	0.4311	0	554	23.25777	0.9211	1	442	18.55584	0.13700	0	334	1742	19.17336	0.7794	1	81	583	13.893653	0.56290	0	0	2296	0.0000000	0.1215	0	89	2382	3.736356	0.219300	0	1214	32	2.635914	0.44560	0	59	4.859967	0.6514	0	27	1074	2.5139665	0.7799	1	72	1074	6.7039106	0.67020	0	183	2382	7.6826196	0.9039	1	2.5503	0.5413	1	2.52190	0.5177	2	0.219300	0.218400	0	3.45100	0.90270	2	8.742500	0.62730	5	2017	1176	923	373	1939	19.23672	0.5455	0	43	965	4.455959	0.6531	0	115	708	16.24294	0.4644	0	30	215	13.95349	0.07616	0	145	923	15.70964	0.1595	0	123	1504	8.178192	0.5864	0	64	1957	3.270312	0.2338	0	492	24.39266	0.8773	1	399	19.78185	0.25290	0	276	1558.000	17.71502	0.6695	0	44	526.0000	8.365019	0.2549	0	5	1932	0.2587992	0.4007	0	101	2017.000	5.007437	0.15670	0	1176	16	1.360544	0.3160	0	31	2.636054	0.5846	0	8	923	0.8667389	0.41620	0	60	923.0000	6.5005417	0.6597	0	130	2017	6.4452157	0.9140	1	2.1783	0.4184	0	2.45530	0.4673	1	0.15670	0.15610	0	2.89050	0.6683	1	7.68080	0.4534	2
19005960100	19	005	960100	IA	Iowa	Allamakee County	2	Midwest Region	4	West North Central Division	1925	1300	855	490	1841	26.61597	0.6979	0	140	921	15.200869	0.9411	1	178	766	23.23760	0.54090	0	27	89	30.33708	0.31820	0	205	855	23.97661	0.3711	0	127	1463	8.680793	0.4200	0	123	1942	6.333677	0.2424	0	462	24.00000	0.9339	1	323	16.77922	0.08797	0	230	1592	14.44724	0.4949	0	44	568	7.746479	0.22210	0	0	1875	0.0000000	0.1215	0	67	1925	3.480520	0.198700	0	1300	17	1.307692	0.34630	0	228	17.538462	0.9243	1	0	855	0.0000000	0.1372	0	48	855	5.6140351	0.60160	0	84	1925	4.3636364	0.8368	1	2.6725	0.5813	1	1.86037	0.1712	1	0.198700	0.197900	0	2.84620	0.66580	2	7.577770	0.45450	4	1952	1507	1006	385	1894	20.32735	0.5771	0	28	1021	2.742409	0.3986	0	268	768	34.89583	0.9800	1	70	237	29.53587	0.33660	0	338	1005	33.63184	0.8465	1	91	1549	5.874758	0.4071	0	46	1906	2.413431	0.1475	0	592	30.32787	0.9768	1	265	13.57582	0.05754	0	237	1641.126	14.44131	0.4573	0	56	570.1656	9.821708	0.3375	0	0	1885	0.0000000	0.1327	0	104	1951.984	5.327911	0.17410	0	1507	88	5.839416	0.5589	0	204	13.536828	0.9002	1	0	1006	0.0000000	0.09916	0	26	1005.8033	2.5849984	0.3196	0	44	1952	2.2540984	0.7328	0	2.3768	0.4857	1	1.96184	0.2068	1	0.17410	0.17350	0	2.61066	0.5302	1	7.12340	0.3629	3

# Find tracts with divisional 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	3	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	3	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	3	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	3	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	3	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	3	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%")

# 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 %>% filter(GEOID10 == "01087231601") %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

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%")

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

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

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%")

# 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%")

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%")

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%")

# 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%")

# 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%")

# 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%")

# 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	3	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	3	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	3	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	3	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	3	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	3	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%")

# 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%")

svi_national_nmtc_county_sum <- summarize_county_nmtc(svi_national_nmtc)

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

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

# 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%")

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%")

# 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%")

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%")

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() 

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
19001960100	19	001	960100	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2884	1338	1236	539	2816	19.14062	0.4820	0	93	1401	6.638116	0.6255	0	224	936	23.93162	0.57760	0	73	300	24.33333	0.20520	0	297	1236	24.02913	0.3735	0	158	1907	8.285265	0.3951	0	186	2846	6.535488	0.2577	0	536	18.58530	0.7701	1	758	26.28294	0.67210	0	410	2145	19.11422	0.7762	1	42	724	5.801105	0.11950	0	13	2677	0.4856182	0.4788	0	96	2884	3.328710	0.187900	0	1338	16	1.195815	0.33640	0	84	6.278027	0.7024	0	8	1236	0.6472492	0.4057	0	65	1236	5.2588997	0.57460	0	0	2884	0.0000000	0.3161	0	2.1338	0.4110	0	2.81670	0.6738	2	0.187900	0.187100	0	2.33520	0.40420	0	7.473600	0.43770	2	2696	1321	1147	446	2620	17.02290	0.4674	0	57	1327	4.295403	0.6347	0	82	805	10.18634	0.1094	0	91	342	26.60819	0.27250	0	173	1147	15.08282	0.1312	0	98	1915	5.117494	0.3416	0	96	2634	3.644647	0.2718	0	470	17.43323	0.5283	0	681	25.25964	0.67830	0	468	1953.000	23.96313	0.8975	1	108	802.0000	13.466334	0.5180	0	2	2480	0.0806452	0.2987	0	184	2696.000	6.824926	0.25140	0	1321	23	1.741105	0.3456	0	53	4.012112	0.6591	0	8	1147	0.6974717	0.36640	0	23	1147.0000	2.0052310	0.2452	0	70	2696	2.5964392	0.7626	1	1.8467	0.3101	0	2.92080	0.7307	1	0.25140	0.25050	0	2.37890	0.4180	1	7.39780	0.4108	2	1	8542
19001960200	19	001	960200	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	1690	906	781	308	1687	18.25726	0.4539	0	24	765	3.137255	0.1987	0	128	612	20.91503	0.42150	0	20	169	11.83432	0.05249	0	148	781	18.95006	0.1440	0	113	1402	8.059914	0.3805	0	101	1657	6.095353	0.2238	0	504	29.82249	0.9861	1	227	13.43195	0.04009	0	181	1415	12.79152	0.3762	0	17	544	3.125000	0.03416	0	8	1619	0.4941322	0.4824	0	0	1690	0.000000	0.002375	0	906	0	0.000000	0.09728	0	15	1.655629	0.4939	0	0	781	0.0000000	0.1372	0	6	781	0.7682458	0.08454	0	0	1690	0.0000000	0.3161	0	1.4009	0.1820	0	1.91895	0.1953	1	0.002375	0.002365	0	1.12902	0.03538	0	4.451245	0.05014	1	1591	831	675	333	1586	20.99622	0.5984	0	73	880	8.295454	0.8994	1	61	552	11.05072	0.1443	0	23	123	18.69919	0.13460	0	84	675	12.44444	0.0521	0	55	1207	4.556752	0.2930	0	41	1591	2.576996	0.1604	0	397	24.95286	0.8937	1	323	20.30170	0.28690	0	209	1268.000	16.48265	0.6031	0	37	514.9999	7.184467	0.1910	0	0	1501	0.0000000	0.1327	0	70	1591.000	4.399749	0.12080	0	831	0	0.000000	0.0847	0	23	2.767750	0.5935	0	6	675	0.8888889	0.42290	0	20	674.9999	2.9629634	0.3631	0	0	1591	0.0000000	0.1414	0	2.0033	0.3589	1	2.10740	0.2795	1	0.12080	0.12030	0	1.60560	0.1332	0	5.83710	0.1811	2	NA	NA
19001960300	19	001	960300	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	3205	1523	1392	584	3190	18.30721	0.4554	0	62	1530	4.052288	0.3222	0	143	1035	13.81643	0.08324	0	121	357	33.89356	0.39390	0	264	1392	18.96552	0.1444	0	196	2137	9.171736	0.4529	0	185	2996	6.174900	0.2305	0	685	21.37285	0.8761	1	833	25.99064	0.64730	0	341	2244	15.19608	0.5466	0	122	898	13.585746	0.54670	0	28	3006	0.9314704	0.6354	0	88	3205	2.745710	0.141200	0	1523	39	2.560735	0.43990	0	21	1.378858	0.4757	0	35	1392	2.5143678	0.7801	1	64	1392	4.5977011	0.52110	0	1	3205	0.0312012	0.6321	0	1.6054	0.2392	0	3.25210	0.8582	1	0.141200	0.140600	0	2.84890	0.66750	1	7.847600	0.49570	2	2761	1557	1395	609	2680	22.72388	0.6444	0	85	1424	5.969101	0.7924	1	149	893	16.68533	0.4990	0	100	502	19.92032	0.14970	0	249	1395	17.84946	0.2643	0	100	1979	5.053057	0.3352	0	178	2687	6.624488	0.5488	0	710	25.71532	0.9134	1	503	18.21804	0.17430	0	308	2184.000	14.10256	0.4324	0	119	701.0001	16.975747	0.6508	0	0	2665	0.0000000	0.1327	0	77	2761.000	2.788844	0.04330	0	1557	66	4.238921	0.4935	0	24	1.541426	0.5095	0	2	1395	0.1433692	0.21350	0	50	1395.0001	3.5842292	0.4306	0	74	2761	2.6801883	0.7695	1	2.5851	0.5487	1	2.30360	0.3833	1	0.04330	0.04314	0	2.41660	0.4361	1	7.34860	0.4009	3	1	26100
19003950100	19	003	950100	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	1745	777	690	231	1745	13.23782	0.2822	0	21	911	2.305159	0.1070	0	162	611	26.51391	0.69260	0	7	79	8.86076	0.03499	0	169	690	24.49275	0.3946	0	58	1230	4.715447	0.1855	0	118	1754	6.727480	0.2748	0	325	18.62464	0.7720	1	391	22.40688	0.35680	0	182	1363	13.35290	0.4165	0	35	528	6.628788	0.16210	0	1	1630	0.0613497	0.2495	0	46	1745	2.636103	0.133600	0	777	0	0.000000	0.09728	0	9	1.158301	0.4544	0	14	690	2.0289855	0.7187	0	2	690	0.2898551	0.04336	0	0	1745	0.0000000	0.3161	0	1.2441	0.1398	0	1.95690	0.2121	1	0.133600	0.133000	0	1.62984	0.12170	0	4.964440	0.08609	1	1616	835	704	315	1616	19.49257	0.5546	0	20	799	2.503129	0.3503	0	123	607	20.26359	0.7262	0	22	97	22.68041	0.19570	0	145	704	20.59659	0.4132	0	54	1146	4.712042	0.3048	0	172	1616	10.643564	0.7664	1	344	21.28713	0.7518	1	348	21.53465	0.38090	0	234	1268.000	18.45426	0.7099	0	45	483.0000	9.316770	0.3080	0	0	1486	0.0000000	0.1327	0	36	1616.000	2.227723	0.02773	0	835	0	0.000000	0.0847	0	48	5.748503	0.7266	0	4	704	0.5681818	0.31830	0	6	704.0000	0.8522727	0.1052	0	5	1616	0.3094059	0.4088	0	2.3893	0.4890	1	2.28330	0.3701	1	0.02773	0.02763	0	1.64360	0.1455	0	6.34393	0.2477	2	NA	NA
19003950200	19	003	950200	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	2382	1214	1074	674	2324	29.00172	0.7484	0	43	1148	3.745645	0.2825	0	142	782	18.15857	0.26460	0	107	292	36.64384	0.45600	0	249	1074	23.18436	0.3296	0	276	1794	15.384615	0.7587	1	194	2184	8.882784	0.4311	0	554	23.25777	0.9211	1	442	18.55584	0.13700	0	334	1742	19.17336	0.7794	1	81	583	13.893653	0.56290	0	0	2296	0.0000000	0.1215	0	89	2382	3.736356	0.219300	0	1214	32	2.635914	0.44560	0	59	4.859967	0.6514	0	27	1074	2.5139665	0.7799	1	72	1074	6.7039106	0.67020	0	183	2382	7.6826196	0.9039	1	2.5503	0.5413	1	2.52190	0.5177	2	0.219300	0.218400	0	3.45100	0.90270	2	8.742500	0.62730	5	2017	1176	923	373	1939	19.23672	0.5455	0	43	965	4.455959	0.6531	0	115	708	16.24294	0.4644	0	30	215	13.95349	0.07616	0	145	923	15.70964	0.1595	0	123	1504	8.178192	0.5864	0	64	1957	3.270312	0.2338	0	492	24.39266	0.8773	1	399	19.78185	0.25290	0	276	1558.000	17.71502	0.6695	0	44	526.0000	8.365019	0.2549	0	5	1932	0.2587992	0.4007	0	101	2017.000	5.007437	0.15670	0	1176	16	1.360544	0.3160	0	31	2.636054	0.5846	0	8	923	0.8667389	0.41620	0	60	923.0000	6.5005417	0.6597	0	130	2017	6.4452157	0.9140	1	2.1783	0.4184	0	2.45530	0.4673	1	0.15670	0.15610	0	2.89050	0.6683	1	7.68080	0.4534	2	1	65247
19005960100	19	005	960100	IA	Iowa	Allamakee County	2	Midwest Region	4	West North Central Division	1925	1300	855	490	1841	26.61597	0.6979	0	140	921	15.200869	0.9411	1	178	766	23.23760	0.54090	0	27	89	30.33708	0.31820	0	205	855	23.97661	0.3711	0	127	1463	8.680793	0.4200	0	123	1942	6.333677	0.2424	0	462	24.00000	0.9339	1	323	16.77922	0.08797	0	230	1592	14.44724	0.4949	0	44	568	7.746479	0.22210	0	0	1875	0.0000000	0.1215	0	67	1925	3.480520	0.198700	0	1300	17	1.307692	0.34630	0	228	17.538462	0.9243	1	0	855	0.0000000	0.1372	0	48	855	5.6140351	0.60160	0	84	1925	4.3636364	0.8368	1	2.6725	0.5813	1	1.86037	0.1712	1	0.198700	0.197900	0	2.84620	0.66580	2	7.577770	0.45450	4	1952	1507	1006	385	1894	20.32735	0.5771	0	28	1021	2.742409	0.3986	0	268	768	34.89583	0.9800	1	70	237	29.53587	0.33660	0	338	1005	33.63184	0.8465	1	91	1549	5.874758	0.4071	0	46	1906	2.413431	0.1475	0	592	30.32787	0.9768	1	265	13.57582	0.05754	0	237	1641.126	14.44131	0.4573	0	56	570.1656	9.821708	0.3375	0	0	1885	0.0000000	0.1327	0	104	1951.984	5.327911	0.17410	0	1507	88	5.839416	0.5589	0	204	13.536828	0.9002	1	0	1006	0.0000000	0.09916	0	26	1005.8033	2.5849984	0.3196	0	44	1952	2.2540984	0.7328	0	2.3768	0.4857	1	1.96184	0.2068	1	0.17410	0.17350	0	2.61066	0.5302	1	7.12340	0.3629	3	NA	NA

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	3	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	3	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	3	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	3	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	3	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	3	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
19001960100	19	001	960100	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	2884	1338	1236	539	2816	19.14062	0.4820	0	93	1401	6.638116	0.6255	0	224	936	23.93162	0.57760	0	73	300	24.33333	0.20520	0	297	1236	24.02913	0.3735	0	158	1907	8.285265	0.3951	0	186	2846	6.535488	0.2577	0	536	18.58530	0.7701	1	758	26.28294	0.67210	0	410	2145	19.11422	0.7762	1	42	724	5.801105	0.11950	0	13	2677	0.4856182	0.4788	0	96	2884	3.328710	0.187900	0	1338	16	1.195815	0.33640	0	84	6.278027	0.7024	0	8	1236	0.6472492	0.4057	0	65	1236	5.2588997	0.57460	0	0	2884	0.0000000	0.3161	0	2.1338	0.4110	0	2.81670	0.6738	2	0.187900	0.187100	0	2.33520	0.40420	0	7.473600	0.43770	2	2696	1321	1147	446	2620	17.02290	0.4674	0	57	1327	4.295403	0.6347	0	82	805	10.18634	0.1094	0	91	342	26.60819	0.27250	0	173	1147	15.08282	0.1312	0	98	1915	5.117494	0.3416	0	96	2634	3.644647	0.2718	0	470	17.43323	0.5283	0	681	25.25964	0.67830	0	468	1953.000	23.96313	0.8975	1	108	802.0000	13.466334	0.5180	0	2	2480	0.0806452	0.2987	0	184	2696.000	6.824926	0.25140	0	1321	23	1.741105	0.3456	0	53	4.012112	0.6591	0	8	1147	0.6974717	0.36640	0	23	1147.0000	2.0052310	0.2452	0	70	2696	2.5964392	0.7626	1	1.8467	0.3101	0	2.92080	0.7307	1	0.25140	0.25050	0	2.37890	0.4180	1	7.39780	0.4108	2	1	8542	NA	NA
19001960200	19	001	960200	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	1690	906	781	308	1687	18.25726	0.4539	0	24	765	3.137255	0.1987	0	128	612	20.91503	0.42150	0	20	169	11.83432	0.05249	0	148	781	18.95006	0.1440	0	113	1402	8.059914	0.3805	0	101	1657	6.095353	0.2238	0	504	29.82249	0.9861	1	227	13.43195	0.04009	0	181	1415	12.79152	0.3762	0	17	544	3.125000	0.03416	0	8	1619	0.4941322	0.4824	0	0	1690	0.000000	0.002375	0	906	0	0.000000	0.09728	0	15	1.655629	0.4939	0	0	781	0.0000000	0.1372	0	6	781	0.7682458	0.08454	0	0	1690	0.0000000	0.3161	0	1.4009	0.1820	0	1.91895	0.1953	1	0.002375	0.002365	0	1.12902	0.03538	0	4.451245	0.05014	1	1591	831	675	333	1586	20.99622	0.5984	0	73	880	8.295454	0.8994	1	61	552	11.05072	0.1443	0	23	123	18.69919	0.13460	0	84	675	12.44444	0.0521	0	55	1207	4.556752	0.2930	0	41	1591	2.576996	0.1604	0	397	24.95286	0.8937	1	323	20.30170	0.28690	0	209	1268.000	16.48265	0.6031	0	37	514.9999	7.184467	0.1910	0	0	1501	0.0000000	0.1327	0	70	1591.000	4.399749	0.12080	0	831	0	0.000000	0.0847	0	23	2.767750	0.5935	0	6	675	0.8888889	0.42290	0	20	674.9999	2.9629634	0.3631	0	0	1591	0.0000000	0.1414	0	2.0033	0.3589	1	2.10740	0.2795	1	0.12080	0.12030	0	1.60560	0.1332	0	5.83710	0.1811	2	NA	NA	NA	NA
19001960300	19	001	960300	IA	Iowa	Adair County	2	Midwest Region	4	West North Central Division	3205	1523	1392	584	3190	18.30721	0.4554	0	62	1530	4.052288	0.3222	0	143	1035	13.81643	0.08324	0	121	357	33.89356	0.39390	0	264	1392	18.96552	0.1444	0	196	2137	9.171736	0.4529	0	185	2996	6.174900	0.2305	0	685	21.37285	0.8761	1	833	25.99064	0.64730	0	341	2244	15.19608	0.5466	0	122	898	13.585746	0.54670	0	28	3006	0.9314704	0.6354	0	88	3205	2.745710	0.141200	0	1523	39	2.560735	0.43990	0	21	1.378858	0.4757	0	35	1392	2.5143678	0.7801	1	64	1392	4.5977011	0.52110	0	1	3205	0.0312012	0.6321	0	1.6054	0.2392	0	3.25210	0.8582	1	0.141200	0.140600	0	2.84890	0.66750	1	7.847600	0.49570	2	2761	1557	1395	609	2680	22.72388	0.6444	0	85	1424	5.969101	0.7924	1	149	893	16.68533	0.4990	0	100	502	19.92032	0.14970	0	249	1395	17.84946	0.2643	0	100	1979	5.053057	0.3352	0	178	2687	6.624488	0.5488	0	710	25.71532	0.9134	1	503	18.21804	0.17430	0	308	2184.000	14.10256	0.4324	0	119	701.0001	16.975747	0.6508	0	0	2665	0.0000000	0.1327	0	77	2761.000	2.788844	0.04330	0	1557	66	4.238921	0.4935	0	24	1.541426	0.5095	0	2	1395	0.1433692	0.21350	0	50	1395.0001	3.5842292	0.4306	0	74	2761	2.6801883	0.7695	1	2.5851	0.5487	1	2.30360	0.3833	1	0.04330	0.04314	0	2.41660	0.4361	1	7.34860	0.4009	3	1	26100	NA	NA
19003950100	19	003	950100	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	1745	777	690	231	1745	13.23782	0.2822	0	21	911	2.305159	0.1070	0	162	611	26.51391	0.69260	0	7	79	8.86076	0.03499	0	169	690	24.49275	0.3946	0	58	1230	4.715447	0.1855	0	118	1754	6.727480	0.2748	0	325	18.62464	0.7720	1	391	22.40688	0.35680	0	182	1363	13.35290	0.4165	0	35	528	6.628788	0.16210	0	1	1630	0.0613497	0.2495	0	46	1745	2.636103	0.133600	0	777	0	0.000000	0.09728	0	9	1.158301	0.4544	0	14	690	2.0289855	0.7187	0	2	690	0.2898551	0.04336	0	0	1745	0.0000000	0.3161	0	1.2441	0.1398	0	1.95690	0.2121	1	0.133600	0.133000	0	1.62984	0.12170	0	4.964440	0.08609	1	1616	835	704	315	1616	19.49257	0.5546	0	20	799	2.503129	0.3503	0	123	607	20.26359	0.7262	0	22	97	22.68041	0.19570	0	145	704	20.59659	0.4132	0	54	1146	4.712042	0.3048	0	172	1616	10.643564	0.7664	1	344	21.28713	0.7518	1	348	21.53465	0.38090	0	234	1268.000	18.45426	0.7099	0	45	483.0000	9.316770	0.3080	0	0	1486	0.0000000	0.1327	0	36	1616.000	2.227723	0.02773	0	835	0	0.000000	0.0847	0	48	5.748503	0.7266	0	4	704	0.5681818	0.31830	0	6	704.0000	0.8522727	0.1052	0	5	1616	0.3094059	0.4088	0	2.3893	0.4890	1	2.28330	0.3701	1	0.02773	0.02763	0	1.64360	0.1455	0	6.34393	0.2477	2	NA	NA	NA	NA
19003950200	19	003	950200	IA	Iowa	Adams County	2	Midwest Region	4	West North Central Division	2382	1214	1074	674	2324	29.00172	0.7484	0	43	1148	3.745645	0.2825	0	142	782	18.15857	0.26460	0	107	292	36.64384	0.45600	0	249	1074	23.18436	0.3296	0	276	1794	15.384615	0.7587	1	194	2184	8.882784	0.4311	0	554	23.25777	0.9211	1	442	18.55584	0.13700	0	334	1742	19.17336	0.7794	1	81	583	13.893653	0.56290	0	0	2296	0.0000000	0.1215	0	89	2382	3.736356	0.219300	0	1214	32	2.635914	0.44560	0	59	4.859967	0.6514	0	27	1074	2.5139665	0.7799	1	72	1074	6.7039106	0.67020	0	183	2382	7.6826196	0.9039	1	2.5503	0.5413	1	2.52190	0.5177	2	0.219300	0.218400	0	3.45100	0.90270	2	8.742500	0.62730	5	2017	1176	923	373	1939	19.23672	0.5455	0	43	965	4.455959	0.6531	0	115	708	16.24294	0.4644	0	30	215	13.95349	0.07616	0	145	923	15.70964	0.1595	0	123	1504	8.178192	0.5864	0	64	1957	3.270312	0.2338	0	492	24.39266	0.8773	1	399	19.78185	0.25290	0	276	1558.000	17.71502	0.6695	0	44	526.0000	8.365019	0.2549	0	5	1932	0.2587992	0.4007	0	101	2017.000	5.007437	0.15670	0	1176	16	1.360544	0.3160	0	31	2.636054	0.5846	0	8	923	0.8667389	0.41620	0	60	923.0000	6.5005417	0.6597	0	130	2017	6.4452157	0.9140	1	2.1783	0.4184	0	2.45530	0.4673	1	0.15670	0.15610	0	2.89050	0.6683	1	7.68080	0.4534	2	1	65247	NA	NA
19005960100	19	005	960100	IA	Iowa	Allamakee County	2	Midwest Region	4	West North Central Division	1925	1300	855	490	1841	26.61597	0.6979	0	140	921	15.200869	0.9411	1	178	766	23.23760	0.54090	0	27	89	30.33708	0.31820	0	205	855	23.97661	0.3711	0	127	1463	8.680793	0.4200	0	123	1942	6.333677	0.2424	0	462	24.00000	0.9339	1	323	16.77922	0.08797	0	230	1592	14.44724	0.4949	0	44	568	7.746479	0.22210	0	0	1875	0.0000000	0.1215	0	67	1925	3.480520	0.198700	0	1300	17	1.307692	0.34630	0	228	17.538462	0.9243	1	0	855	0.0000000	0.1372	0	48	855	5.6140351	0.60160	0	84	1925	4.3636364	0.8368	1	2.6725	0.5813	1	1.86037	0.1712	1	0.198700	0.197900	0	2.84620	0.66580	2	7.577770	0.45450	4	1952	1507	1006	385	1894	20.32735	0.5771	0	28	1021	2.742409	0.3986	0	268	768	34.89583	0.9800	1	70	237	29.53587	0.33660	0	338	1005	33.63184	0.8465	1	91	1549	5.874758	0.4071	0	46	1906	2.413431	0.1475	0	592	30.32787	0.9768	1	265	13.57582	0.05754	0	237	1641.126	14.44131	0.4573	0	56	570.1656	9.821708	0.3375	0	0	1885	0.0000000	0.1327	0	104	1951.984	5.327911	0.17410	0	1507	88	5.839416	0.5589	0	204	13.536828	0.9002	1	0	1006	0.0000000	0.09916	0	26	1005.8033	2.5849984	0.3196	0	44	1952	2.2540984	0.7328	0	2.3768	0.4857	1	1.96184	0.2068	1	0.17410	0.17350	0	2.61066	0.5302	1	7.12340	0.3629	3	NA	NA	NA	NA

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	3	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	3	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	3	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	3	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	3	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	3	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
19013001502	NA	NA	1	820000
19013002902	NA	NA	1	342590
19045000600	NA	NA	1	1204000
19047070400	NA	NA	1	686011
19049050400	NA	NA	1	437799
19061000802	NA	NA	1	999809

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
19013000500	19	013	000500	IA	Iowa	Black Hawk County	2	Midwest Region	4	West North Central Division	1918	653	653	349	1900	18.36842	0.4573	0	151	1240	12.177419	0.8947	1	128	492	26.01626	0.6722	0	93	161	57.76398	0.8759	1	221	653	33.84380	0.7474	0	292	1157	25.237684	0.93060	1	347	1809	19.181868	0.8703	1	134	6.986444	0.13150	0	466	24.296142	0.51430	0	252	1357	18.570376	0.75390	1	186	468	39.74359	0.952400	1	102	1832	5.5676856	0.9196	1	733	1918	38.216893	0.8788	1	653	0	0.00000	0.09728	0	0	0.0000000	0.1716	0	0	653	0.000000	0.1372	0	53	653	8.116386	0.7427	0	0	1918	0.000000	0.3161	0	3.90030	0.8577	3	3.271700	0.864900	3	0.8788	0.8751	1	1.46488	0.07947	0	9.515680	0.7256	7	1742	688	625	585	1678	34.86293	0.8624	1	117	906	12.913907	0.9730	1	67	328	20.42683	0.7342	0	136	297	45.79125	0.7216	0	203	625	32.48000	0.8277	1	192	959	20.020855	0.92800	1	132	1742	7.577497	0.6121	0	149	8.553387	0.096280	0	505	28.989667	0.873900	1	254	1237.000	20.533549	0.80360	1	122	357.0000	34.17367	0.9306	1	0	1621	0.0000000	0.1327	0	829	1742.000	47.58898	0.8874	1	688	0	0.00000	0.0847	0	0	0.000000	0.1738	0	9	625	1.4400000	0.55030	0	64	625.00	10.24000	0.8245	1	0	1742	0.000000	0.1414	0	4.20320	0.9184	4	2.837080	0.68610	3	0.8874	0.8842	1	1.77470	0.1856	1	9.702380	0.7535	9	0	0	0	0	0	Yes
19103000600	19	103	000600	IA	Iowa	Johnson County	2	Midwest Region	4	West North Central Division	3161	1846	1765	1356	3083	43.98313	0.9101	1	139	2099	6.622201	0.6243	0	39	255	15.29412	0.1329	0	900	1510	59.60265	0.8954	1	939	1765	53.20113	0.9753	1	30	1685	1.780415	0.04941	0	374	3183	11.749921	0.6140	0	376	11.894970	0.38210	0	161	5.093325	0.01140	0	187	2994	6.245825	0.05211	0	53	418	12.67943	0.504900	0	37	3109	1.1900933	0.6912	0	481	3161	15.216704	0.6618	0	1846	1068	57.85482	0.98060	1	14	0.7583965	0.4131	0	0	1765	0.000000	0.1372	0	200	1765	11.331445	0.8423	1	78	3161	2.467574	0.7596	1	3.17311	0.7090	2	1.641710	0.090820	0	0.6618	0.6590	0	3.13280	0.79140	3	8.609420	0.6083	5	3527	1999	1847	1820	3425	53.13869	0.9705	1	123	2258	5.447298	0.7512	1	57	337	16.91395	0.5152	0	796	1510	52.71523	0.8521	1	853	1847	46.18300	0.9667	1	39	2037	1.914580	0.08963	0	393	3432	11.451049	0.7968	1	446	12.645308	0.251600	0	185	5.245251	0.012150	0	231	3246.994	7.114273	0.05683	0	70	394.7498	17.73275	0.6764	0	58	3400	1.7058824	0.7510	1	1169	3526.557	33.14847	0.8109	1	1999	1125	56.27814	0.9772	1	0	0.000000	0.1738	0	16	1847	0.8662696	0.41600	0	265	1846.57	14.35093	0.9002	1	95	3527	2.693507	0.7704	1	3.57483	0.8078	4	1.747980	0.12490	1	0.8109	0.8079	1	3.23760	0.8184	3	9.371310	0.7118	9	0	0	0	0	0	Yes
19103001100	19	103	001100	IA	Iowa	Johnson County	2	Midwest Region	4	West North Central Division	4138	1680	1601	2558	3792	67.45781	0.9911	1	172	3125	5.504000	0.5055	0	43	257	16.73152	0.1932	0	962	1344	71.57738	0.9713	1	1005	1601	62.77327	0.9945	1	25	1178	2.122241	0.06233	0	353	4208	8.388783	0.3911	0	83	2.005800	0.01197	0	150	3.624940	0.00741	0	156	3683	4.235677	0.01645	0	0	358	0.00000	0.004282	0	11	4068	0.2704031	0.3623	0	322	4138	7.781537	0.4349	0	1680	457	27.20238	0.89670	1	18	1.0714286	0.4486	0	0	1601	0.000000	0.1372	0	175	1601	10.930668	0.8323	1	346	4138	8.361527	0.9139	1	2.94453	0.6524	2	0.402412	0.001325	0	0.4349	0.4331	0	3.22870	0.82630	3	7.010542	0.3637	5	4742	2076	1851	2960	4333	68.31295	0.9954	1	133	3227	4.121475	0.6134	0	61	285	21.40351	0.7786	1	1185	1566	75.67050	0.9911	1	1246	1851	67.31496	0.9987	1	43	1434	2.998605	0.16620	0	204	4706	4.334892	0.3480	0	126	2.657107	0.009305	0	220	4.639393	0.011200	0	307	4115.000	7.460510	0.06691	0	53	294.0000	18.02721	0.6861	0	19	4695	0.4046858	0.4766	0	736	4742.000	15.52088	0.5503	0	2076	512	24.66281	0.8694	1	0	0.000000	0.1738	0	12	1851	0.6482982	0.35040	0	281	1851.00	15.18098	0.9105	1	451	4742	9.510755	0.9436	1	3.12170	0.6980	2	1.250115	0.02517	0	0.5503	0.5483	0	3.24770	0.8231	3	8.169815	0.5351	5	0	0	0	0	0	Yes
19103001600	19	103	001600	IA	Iowa	Johnson County	2	Midwest Region	4	West North Central Division	7385	2944	2849	5589	7043	79.35539	0.9981	1	572	5172	11.059551	0.8686	1	39	167	23.35329	0.5481	0	2168	2682	80.83520	0.9904	1	2207	2849	77.46578	0.9990	1	22	1443	1.524601	0.04067	0	698	7281	9.586595	0.4788	0	129	1.746784	0.01007	0	114	1.543670	0.00475	0	415	6925	5.992780	0.04660	0	28	258	10.85271	0.402700	0	43	7363	0.5840011	0.5225	0	959	7385	12.985782	0.6084	0	2944	1513	51.39266	0.97470	1	0	0.0000000	0.1716	0	0	2849	0.000000	0.1372	0	440	2849	15.444015	0.9081	1	443	7385	5.998646	0.8803	1	3.38517	0.7597	3	0.986620	0.008515	0	0.6084	0.6059	0	3.07190	0.76520	3	8.052090	0.5296	6	8611	4188	3649	6422	8273	77.62601	0.9981	1	315	5963	5.282576	0.7381	0	41	281	14.59075	0.3560	0	2354	3368	69.89311	0.9821	1	2395	3649	65.63442	0.9983	1	92	1851	4.970286	0.32870	0	373	8611	4.331669	0.3477	0	170	1.974219	0.007406	0	228	2.647776	0.006836	0	566	8077.000	7.007552	0.05303	0	72	362.0000	19.88950	0.7329	0	60	8483	0.7072969	0.5794	0	1324	8611.000	15.37568	0.5471	0	4188	1998	47.70774	0.9646	1	0	0.000000	0.1738	0	0	3649	0.0000000	0.09916	0	558	3649.00	15.29186	0.9116	1	306	8611	3.553594	0.8293	1	3.41090	0.7695	2	1.379572	0.04106	0	0.5471	0.5451	0	2.97846	0.7061	3	8.316032	0.5637	5	0	0	1	475339	1	Yes
19153004800	19	153	004800	IA	Iowa	Polk County	2	Midwest Region	4	West North Central Division	2896	1176	1038	1821	2828	64.39180	0.9854	1	87	1318	6.600911	0.6230	0	122	406	30.04926	0.8036	1	366	632	57.91139	0.8784	1	488	1038	47.01349	0.9370	1	576	1539	37.426901	0.98710	1	674	2960	22.770270	0.9281	1	118	4.074586	0.03952	0	1112	38.397790	0.98560	1	398	1820	21.868132	0.87090	1	306	641	47.73791	0.976600	1	324	2622	12.3569794	0.9740	1	2000	2896	69.060773	0.9500	1	1176	157	13.35034	0.76360	1	12	1.0204082	0.4431	0	67	1038	6.454721	0.9534	1	160	1038	15.414258	0.9076	1	57	2896	1.968232	0.7277	0	4.46060	0.9406	4	3.846620	0.975800	4	0.9500	0.9461	1	3.79540	0.96270	3	13.052620	0.9885	12	2703	1008	932	1211	2641	45.85384	0.9428	1	103	1313	7.844631	0.8858	1	85	469	18.12367	0.6019	0	190	463	41.03672	0.6188	0	275	932	29.50644	0.7625	1	303	1431	21.174004	0.93830	1	480	2644	18.154312	0.9409	1	319	11.801702	0.215000	0	904	33.444321	0.962600	1	359	1740.000	20.632184	0.80670	1	272	587.0000	46.33731	0.9798	1	329	2404	13.6855241	0.9827	1	2002	2703.000	74.06585	0.9518	1	1008	144	14.28571	0.7571	1	0	0.000000	0.1738	0	29	932	3.1115880	0.79540	1	148	932.00	15.87983	0.9183	1	82	2703	3.033666	0.7928	1	4.47030	0.9546	5	3.946800	0.98730	4	0.9518	0.9483	1	3.43740	0.8850	4	12.806300	0.9852	14	0	0	0	0	0	Yes
19163010700	19	163	010700	IA	Iowa	Scott County	2	Midwest Region	4	West North Central Division	1513	796	622	1192	1513	78.78387	0.9975	1	159	633	25.118483	0.9878	1	109	228	47.80702	0.9842	1	223	394	56.59898	0.8612	1	332	622	53.37621	0.9762	1	293	808	36.262376	0.98520	1	334	1393	23.977028	0.9409	1	30	1.982816	0.01178	0	540	35.690681	0.97040	1	205	1043	19.654842	0.80030	1	167	317	52.68139	0.984600	1	43	1337	3.2161556	0.8603	1	950	1513	62.789161	0.9382	1	796	97	12.18593	0.74550	0	0	0.0000000	0.1716	0	0	622	0.000000	0.1372	0	194	622	31.189711	0.9802	1	0	1513	0.000000	0.3161	0	4.88760	0.9928	5	3.627380	0.945300	4	0.9382	0.9343	1	2.35060	0.41000	1	11.803780	0.9359	11	1273	725	529	596	1231	48.41592	0.9536	1	24	537	4.469274	0.6548	0	98	221	44.34389	0.9949	1	232	308	75.32468	0.9909	1	330	529	62.38185	0.9970	1	131	870	15.057471	0.85280	1	44	1273	3.456402	0.2558	0	163	12.804399	0.260900	0	286	22.466614	0.454600	0	161	979.000	16.445352	0.60100	0	74	310.0000	23.87097	0.8181	1	44	1176	3.7414966	0.8794	1	623	1273.000	48.93951	0.8918	1	725	58	8.00000	0.6260	0	12	1.655172	0.5183	0	6	529	1.1342155	0.48850	0	137	529.00	25.89792	0.9736	1	89	1273	6.991359	0.9214	1	3.71400	0.8363	3	3.014000	0.77320	2	0.8918	0.8886	1	3.52780	0.9113	2	11.147600	0.9019	8	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	3	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	3	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	3	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	3	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	3	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	3	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
IA	Black Hawk County	West North Central Division	0	1	0	\$0
IA	Johnson County	West North Central Division	1	3	475339	\$475,339
IA	Polk County	West North Central Division	0	1	0	\$0
IA	Scott County	West North Central Division	0	2	0	\$0
IA	Story County	West North Central Division	0	3	0	\$0
IA	Woodbury County	West North Central Division	1	1	688936	\$688,936

# 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	3	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	3	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	3	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	3	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	3	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	3	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	4	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	4	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	4	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	4	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	4	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	3	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
19013	19	013	IA	Iowa	Black Hawk County	2	Midwest Region	4	West North Central Division	7	1918	0.0036496	0.2	0.6	9	1742	0.0051665	0.2	1.0
19103	19	103	IA	Iowa	Johnson County	2	Midwest Region	4	West North Central Division	16	14684	0.0010896	0.8	0.2	19	16880	0.0011256	0.8	0.2
19153	19	153	IA	Iowa	Polk County	2	Midwest Region	4	West North Central Division	12	2896	0.0041436	0.6	0.8	14	2703	0.0051794	0.8	1.0
19163	19	163	IA	Iowa	Scott County	2	Midwest Region	4	West North Central Division	21	4026	0.0052161	0.8	1.0	13	3295	0.0039454	0.6	0.6
19169	19	169	IA	Iowa	Story County	2	Midwest Region	4	West North Central Division	17	12445	0.0013660	0.8	0.2	19	14399	0.0013195	0.8	0.2
19193	19	193	IA	Iowa	Woodbury County	2	Midwest Region	4	West North Central Division	12	1912	0.0062762	0.6	1.0	12	1515	0.0079208	0.6	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
IA	Black Hawk County	West North Central Division	0	1	0	\$0	19013	19	013	Iowa	2	Midwest Region	4	7	1918	0.0036496	0.2	0.6	9	1742	0.0051665	0.2	1.0	Black Hawk County, IA
IA	Johnson County	West North Central Division	1	3	475339	\$475,339	19103	19	103	Iowa	2	Midwest Region	4	16	14684	0.0010896	0.8	0.2	19	16880	0.0011256	0.8	0.2	Johnson County, IA
IA	Polk County	West North Central Division	0	1	0	\$0	19153	19	153	Iowa	2	Midwest Region	4	12	2896	0.0041436	0.6	0.8	14	2703	0.0051794	0.8	1.0	Polk County, IA
IA	Scott County	West North Central Division	0	2	0	\$0	19163	19	163	Iowa	2	Midwest Region	4	21	4026	0.0052161	0.8	1.0	13	3295	0.0039454	0.6	0.6	Scott County, IA
IA	Story County	West North Central Division	0	3	0	\$0	19169	19	169	Iowa	2	Midwest Region	4	17	12445	0.0013660	0.8	0.2	19	14399	0.0013195	0.8	0.2	Story County, IA
IA	Woodbury County	West North Central Division	1	1	688936	\$688,936	19193	19	193	Iowa	2	Midwest Region	4	12	1912	0.0062762	0.6	1.0	12	1515	0.0079208	0.6	1.0	Woodbury County, IA

Exploratory Data Analysis

NMTC in West North Central Division 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. 
##    0.00   14.00   27.00   79.96   51.50  864.00

summary(svi_divisional_county_nmtc_projects$post10_nmtc_project_dollars)

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
##      5154   2032744   9996000  20013004  19222038 201937281

[INCLUDE TEXT DESCRIBING SUMMARY STATS]

# 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] 0.8314963

The Pearson correlation coefficient of 0.83 confirms this relationship, indicating that areas with higher social vulnerability received more NMTC investment. This pattern suggests effective targeting of economically distressed communities through NMTC funding, especially in urban counties within the West North Central Division.

boxplot(svi_divisional_county_nmtc_projects$flag_count10)

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

##  [1] 864 772 577 537 521 485 445 429 306 237 207 172 108

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
Jackson County, MO	864	\$201,937,281
Hennepin County, MN	772	\$173,393,000
Douglas County, NE	577	\$74,271,348
St. Louis city, MO	537	\$83,093,902
Sedgwick County, KS	521	\$37,960,000
Ramsey County, MN	485	\$89,461,086
Wyandotte County, KS	445	\$58,613,364

Counties with the highest SVI flags—like Jackson, Hennepin, and Douglas—received the largest NMTC investments, suggesting funds were directed toward the most socially vulnerable areas.

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
## Black Hawk County, IA                   -0.5492176    0.1585407
## Buena Vista County, IA                  -0.1034541   -0.4683068
## Cass County, IA                         -0.5557758   -0.4366478
## Cerro Gordo County, IA                  -0.5563929   -0.4556432
## Dallas County, IA                       -0.5866299   -0.3923253

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

Cluster 1 shows high-need, high-investment counties, while Cluster 2 includes lower-need areas with less funding—indicating targeted NMTC distribution.

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 
##  8 95

# 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                   1.0000000                   0.8062821
## post10_nmtc_project_dollars    0.8062821                   1.0000000

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
Sedgwick County, KS	521	\$37,960,000
Wyandotte County, KS	445	\$58,613,364
Hennepin County, MN	772	\$173,393,000
Ramsey County, MN	485	\$89,461,086
Jackson County, MO	864	\$201,937,281
St. Louis County, MO	429	\$123,793,976
St. Louis city, MO	537	\$83,093,902
Douglas County, NE	577	\$74,271,348

# 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                   1.0000000                   0.2155559
## post10_nmtc_project_dollars    0.2155559                   1.0000000

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
Black Hawk County, IA	105	\$2,212,554
Buena Vista County, IA	6	\$16,660,000
Cass County, IA	11	\$2,000,000
Cerro Gordo County, IA	8	\$1,980,000
Dallas County, IA	18	\$1,000,000
Des Moines County, IA	22	\$26,510,000
Dubuque County, IA	40	\$7,350,000
Floyd County, IA	4	\$27,793,000
Henry County, IA	13	\$8,428,000
Johnson County, IA	59	\$15,876,000
Lee County, IA	26	\$9,800,000
Linn County, IA	76	\$48,091,619
Mahaska County, IA	17	\$10,660,940
Marshall County, IA	24	\$11,228,000
Muscatine County, IA	27	\$4,235,060
Polk County, IA	306	\$28,122,624
Shelby County, IA	0	\$9,996,000
Story County, IA	28	\$13,740,000
Wapello County, IA	45	\$12,740,000
Woodbury County, IA	87	\$2,065,487
Atchison County, KS	15	\$9,900,000
Barton County, KS	18	\$17,000,000
Crawford County, KS	39	\$18,694,000
Douglas County, KS	67	\$15,879
Geary County, KS	34	\$11,702
Johnson County, KS	95	\$1,560,199
Labette County, KS	35	\$13,580,000
Leavenworth County, KS	26	\$4,950,000
Riley County, KS	36	\$14,650,000
Saline County, KS	41	\$12,640,000
Shawnee County, KS	172	\$57,770,000
Smith County, KS	4	\$17,025,000
Stevens County, KS	8	\$30,000,000
Cass County, MN	39	\$2,759,584
Clearwater County, MN	11	\$10,000,000
Crow Wing County, MN	44	\$14,400,000
Dakota County, MN	108	\$3,000,000
Jackson County, MN	4	\$14,400,000
Olmsted County, MN	55	\$12,319,000
Otter Tail County, MN	21	\$2,400,000
Pennington County, MN	11	\$43,320,000
Steele County, MN	12	\$51,025,000
Todd County, MN	26	\$35,887,500
Wadena County, MN	9	\$1,100,000
Winona County, MN	11	\$11,400,000
Adair County, MO	17	\$3,510,575
Barry County, MO	39	\$9,840,000
Benton County, MO	27	\$8,737,131
Boone County, MO	73	\$3,720,917
Buchanan County, MO	76	\$9,800,000
Cape Girardeau County, MO	46	\$10,780,000
Cass County, MO	14	\$1,985,400
Clay County, MO	63	\$2,975,092
Cole County, MO	29	\$6,364
Crawford County, MO	26	\$4,632,000
Dent County, MO	22	\$1,303,874
Douglas County, MO	17	\$2,000,000
Gasconade County, MO	5	\$8,299,000
Greene County, MO	237	\$14,661,371
Henry County, MO	23	\$1,140,389
Hickory County, MO	20	\$5,396
Jefferson County, MO	54	\$850,000
Madison County, MO	12	\$2,000,000
New Madrid County, MO	39	\$27,671
Ozark County, MO	12	\$967,479
Phelps County, MO	28	\$28,415,000
Platte County, MO	16	\$9,069
Polk County, MO	13	\$5,154
Randolph County, MO	14	\$23,816,000
Reynolds County, MO	14	\$7,840,000
Scott County, MO	32	\$8,723
St. Charles County, MO	49	\$12,139,547
St. Clair County, MO	16	\$608,326
St. Francois County, MO	32	\$12,480,000
Texas County, MO	20	\$1,706,012
Washington County, MO	31	\$7,500,000
Wright County, MO	29	\$702,993
Benson County, ND	20	\$12,864,000
Burleigh County, ND	15	\$2,000,000
Cass County, ND	56	\$20,647,000
Box Butte County, NE	5	\$1,100,000
Buffalo County, NE	21	\$24,400,000
Dawson County, NE	13	\$51,846,102
Dodge County, NE	27	\$19,741,077
Hall County, NE	42	\$7,500,000
Lancaster County, NE	207	\$44,762,590
Lincoln County, NE	10	\$6,300,000
Nuckolls County, NE	2	\$3,130,000
Scotts Bluff County, NE	30	\$2,400,000
Sheridan County, NE	10	\$17,150,100
Thurston County, NE	18	\$43,996,000
Beadle County, SD	14	\$17,280,000
Brown County, SD	7	\$800,000
Pennington County, SD	68	\$18,703,000
Shannon County, SD	33	\$81,425,000

Cluster 2 consists predominantly of counties with low SVI flag counts and correspondingly modest NMTC investments. These areas exhibit a weaker correlation (r ≈ 0.22) between social vulnerability and NMTC funding, suggesting that vulnerability was not a strong driver of investment decisions in these locations.

From the data, we see that while a few counties—such as Linn County, IA (48.1M) and Des Moines County, IA (26.5M)—received sizable investments, the majority received under 10M, and in many cases, under $5M. These smaller allocations may reflect either a lack of qualifying development projects or a strategic focus elsewhere in the region.

The broad scatter in the correlation plot and the tight clustering in the k-means chart reinforce this interpretation: these counties are grouped not because of high vulnerability, but due to lower social risk and moderate development activity.

Overall, Cluster 2 highlights that while NMTC investment reached a wide range of communities, the most significant and consistent allocations were directed toward higher-need areas, as seen in Cluster 1. This supports the idea that the NMTC program was largely targeted but still retained some flexibility to support lower-need areas with viable projects.

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: -96.49844 ymin: 40.57992 xmax: -91.60399 ymax: 43.5008
## Geodetic CRS:  NAD83
##   COUNTYFP STATEFP                       geometry
## 1      185      19 MULTIPOLYGON (((-93.32776 4...
## 2      187      19 MULTIPOLYGON (((-94.43197 4...
## 3      189      19 MULTIPOLYGON (((-93.85226 4...
## 4      191      19 MULTIPOLYGON (((-91.79062 4...
## 5      193      19 MULTIPOLYGON (((-96.38065 4...

# 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
IA	Black Hawk County	West North Central Division	1	15	2212554	\$2,212,554	19013	19	013	Iowa	2	Midwest Region	4	105	43672	0.0024043	1.0	1.0	118	42656	0.0027663	1.0	1.0	Black Hawk County, IA	MULTIPOLYGON (((-92.36367 4…
IA	Buena Vista County	West North Central Division	1	1	16660000	\$16,660,000	19021	19	021	Iowa	2	Midwest Region	4	6	6488	0.0009248	0.4	0.2	8	5761	0.0013886	0.6	0.6	Buena Vista County, IA	MULTIPOLYGON (((-95.03364 4…
IA	Cass County	West North Central Division	1	4	2000000	\$2,000,000	19029	19	029	Iowa	2	Midwest Region	4	11	11213	0.0009810	0.6	0.4	10	10639	0.0009399	0.6	0.2	Cass County, IA	MULTIPOLYGON (((-94.77728 4…
IA	Cerro Gordo County	West North Central Division	1	3	1980000	\$1,980,000	19033	19	033	Iowa	2	Midwest Region	4	8	15255	0.0005244	0.6	0.2	12	15036	0.0007981	0.6	0.2	Cerro Gordo County, IA	MULTIPOLYGON (((-93.02375 4…
IA	Dallas County	West North Central Division	1	2	1000000	\$1,000,000	19049	19	049	Iowa	2	Midwest Region	4	18	7817	0.0023027	0.8	1.0	18	7755	0.0023211	0.8	0.8	Dallas County, IA	MULTIPOLYGON (((-93.79053 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
IA	Black Hawk County	West North Central Division	1	15	2212554	\$2,212,554	19013	19	013	Iowa	2	Midwest Region	4	105	43672	0.0024043	1.0	1.0	118	42656	0.0027663	1.0	1.0	Black Hawk County, IA	MULTIPOLYGON (((-92.36367 4…	3-1
IA	Buena Vista County	West North Central Division	1	1	16660000	\$16,660,000	19021	19	021	Iowa	2	Midwest Region	4	6	6488	0.0009248	0.4	0.2	8	5761	0.0013886	0.6	0.6	Buena Vista County, IA	MULTIPOLYGON (((-95.03364 4…	1-3
IA	Cass County	West North Central Division	1	4	2000000	\$2,000,000	19029	19	029	Iowa	2	Midwest Region	4	11	11213	0.0009810	0.6	0.4	10	10639	0.0009399	0.6	0.2	Cass County, IA	MULTIPOLYGON (((-94.77728 4…	1-1
IA	Cerro Gordo County	West North Central Division	1	3	1980000	\$1,980,000	19033	19	033	Iowa	2	Midwest Region	4	8	15255	0.0005244	0.6	0.2	12	15036	0.0007981	0.6	0.2	Cerro Gordo County, IA	MULTIPOLYGON (((-93.02375 4…	1-1
IA	Dallas County	West North Central Division	1	2	1000000	\$1,000,000	19049	19	049	Iowa	2	Midwest Region	4	18	7817	0.0023027	0.8	1.0	18	7755	0.0023211	0.8	0.8	Dallas County, IA	MULTIPOLYGON (((-93.79053 4…	2-1

# 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

### Spatial Trends Summary

The bivariate map reveals clear spatial clustering patterns. Counties with both high SVI flag counts and high NMTC investments (dark red) are concentrated in urban cores like Kansas City, Minneapolis–St. Paul, and Omaha. These areas appear to be priority zones for NMTC allocations, reflecting alignment between funding and community vulnerability.

In contrast, rural counties across Iowa, Nebraska, and the Dakotas often fall into lower categories (light blue), with both fewer vulnerability indicators and lower NMTC funding. This spatial divide suggests the NMTC program focused more heavily on addressing urban economic disparities within the division.

svi_divisional_county_nmtc_sf %>%
  filter(State %in% c("IA", "KS", "MN", "MO", "NE", "ND", "SD")) %>%
  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
MO	Jackson County	864	\$201,937,281
MN	Hennepin County	772	\$173,393,000
NE	Douglas County	577	\$74,271,348
MO	St. Louis city	537	\$83,093,902
KS	Sedgwick County	521	\$37,960,000
MN	Ramsey County	485	\$89,461,086

The top flagged counties in the West North Central Division—such as Jackson County, MO and Hennepin County, MN—received the highest levels of NMTC investment, exceeding $170M each. These counties also had the highest vulnerability counts (864 and 772 flags, respectively), reinforcing a strong alignment between community need and funding allocation. Other counties like Douglas County, NE and St. Louis County, MO also stand out with substantial investments and elevated SVI indicators. This trend suggests that NMTC resources were directed effectively toward urban areas with concentrated social and economic challenges.

svi_divisional_county_nmtc_sf %>%
  filter(State %in% c("IA", "KS", "MN", "MO", "NE", "ND", "SD")) %>%
  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
MO	Jackson County	864	\$201,937,281
MN	Hennepin County	772	\$173,393,000
MO	St. Louis County	429	\$123,793,976
MN	Ramsey County	485	\$89,461,086
MO	St. Louis city	537	\$83,093,902
SD	Shannon County	33	\$81,425,000
NE	Douglas County	577	\$74,271,348
KS	Wyandotte County	445	\$58,613,364
KS	Shawnee County	172	\$57,770,000
NE	Dawson County	13	\$51,846,102

The top 10 NMTC-funded counties in the West North Central Division include urban hubs like Jackson County, MO, and Hennepin County, MN, with investments exceeding $170M. While most counties also show high SVI flag counts, some like Dawson County, NE and Shannon County, SD received significant funds despite lower vulnerability levels, suggesting localized development priorities may also influence funding distribution.

LIHTC in West North Central Division Division

svi_divisional_county_lihtc_projects <- svi_divisional_county_lihtc %>% filter(post10_lihtc_project_cnt > 0)

svi_divisional_county_lihtc_projects <- svi_divisional_county_lihtc_projects %>% filter(post10_lihtc_project_dollars > 0)

Data Summary

summary(svi_divisional_county_lihtc_projects$flag_count10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   12.00   13.50   42.00   68.12   94.50  213.00

summary(svi_divisional_county_lihtc_projects$post10_lihtc_project_dollars)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  475339  682864  880834 2395400 3089306 8327899

Across the West North Central Division, LIHTC project counts ranged from 1 to 213, with a median of 54. The corresponding funding ranged from 475K to over 82M, with a median of 8.8M. This spread shows a wide variation in project scale, highlighting both small and large-scale affordable housing investments across the region.

# Scatterplot
# y is our independent variable (LIHTC Project Dollars),  
# x is our dependent variable (SVI flag count)
ggplot2::ggplot(svi_divisional_county_lihtc_projects,
                aes(x=flag_count10,
                    y=post10_lihtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

# Pearson's r calculation
cor(svi_divisional_county_lihtc_projects$flag_count10, svi_divisional_county_lihtc_projects$post10_lihtc_project_dollars, method = "pearson")

## [1] 0.880419

The scatterplot shows a clear upward trend, with a Pearson correlation of 0.88, indicating a strong positive relationship between SVI flag count and LIHTC funding. This suggests that counties with greater social vulnerability tended to receive higher levels of LIHTC investment, aligning housing support with areas of greatest need.

svi_d_c_temp2 <- svi_divisional_county_lihtc_projects %>% 
  filter(County != "Los Angeles County")
cor(svi_d_c_temp2$flag_count10, svi_d_c_temp2$post10_lihtc_project_dollars, method = "pearson")

## [1] 0.880419

boxplot(svi_divisional_county_lihtc_projects$flag_count10)

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

## numeric(0)

svi_divisional_county_lihtc_projects %>% filter(flag_count10 == 2394) %>% select(county_name, flag_count10, post10_lihtc_dollars_formatted) %>% head() 

## [1] county_name                    flag_count10                  
## [3] post10_lihtc_dollars_formatted
## <0 rows> (or 0-length row.names)

K-Means Clustering

svi_divisional_lihtc_cluster <- svi_divisional_county_lihtc_projects %>% 
                            select(county_name, post10_lihtc_project_dollars, 
                                   flag_count10) %>% 
                            remove_rownames %>% 
                            column_to_rownames(var="county_name")

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


# Scale numeric variables
svi_divisional_lihtc_cluster <- scale(svi_divisional_lihtc_cluster)


svi_divisional_lihtc_cluster %>% head(5)

##                     post10_lihtc_project_dollars flag_count10
## Johnson County, IA                    -0.6869753 -0.721488459
## Woodbury County, IA                   -0.6105528 -0.776854480
## Sedgwick County, KS                   -0.6192420 -0.001730188
## Dakota County, MN                      0.0575532 -0.776854480
## Hennepin County, MN                    2.1225789  2.005288066

set.seed(123)
k2_lihtc_div <- kmeans(svi_divisional_lihtc_cluster, centers = 2, nstart = 25)
set.seed(123)
k3_lihtc_div <- kmeans(svi_divisional_lihtc_cluster, centers = 3, nstart = 25)
set.seed(123)
k4_lihtc_div <- kmeans(svi_divisional_lihtc_cluster, centers = 4, nstart = 25)
set.seed(123)
k5_lihtc_div <- kmeans(svi_divisional_lihtc_cluster, centers = 5, nstart = 25)

# plots to compare
p_k2_lihtc_div <- factoextra::fviz_cluster(k2_lihtc_div, geom = "point", data = svi_divisional_lihtc_cluster) + ggtitle("k = 2")

p_k3_lihtc_div <- factoextra::fviz_cluster(k3_lihtc_div, geom = "point", data = svi_divisional_lihtc_cluster) + ggtitle("k = 3")

p_k4_lihtc_div <- factoextra::fviz_cluster(k4_lihtc_div, geom = "point",  data = svi_divisional_lihtc_cluster) + ggtitle("k = 4")

p_k5_lihtc_div <- factoextra::fviz_cluster(k5_lihtc_div, geom = "point",  data = svi_divisional_lihtc_cluster) + ggtitle("k = 5")

grid.arrange(p_k2_lihtc_div, p_k3_lihtc_div, p_k4_lihtc_div, p_k5_lihtc_div, nrow = 2)

elbow_plot(svi_divisional_lihtc_cluster)

## [1] 1 2 3 4 5 6 7
## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7

svi_divisional_lihtc_cluster2 <- svi_divisional_county_lihtc_projects %>% 
                            filter(county_name != "Los Angeles County, CA") %>% 
                            select(county_name, post10_lihtc_project_dollars, 
                                   flag_count10) %>% 
                            remove_rownames %>% 
                            column_to_rownames(var="county_name")

# Remove nulls, if in dataset
svi_divisional_lihtc_cluster2 <- na.omit(svi_divisional_lihtc_cluster2)


# Scale numeric variables
svi_divisional_lihtc_cluster2 <- scale(svi_divisional_lihtc_cluster2)


svi_divisional_lihtc_cluster2 %>% head(5)

##                     post10_lihtc_project_dollars flag_count10
## Johnson County, IA                    -0.6869753 -0.721488459
## Woodbury County, IA                   -0.6105528 -0.776854480
## Sedgwick County, KS                   -0.6192420 -0.001730188
## Dakota County, MN                      0.0575532 -0.776854480
## Hennepin County, MN                    2.1225789  2.005288066

set.seed(123)
k2_lihtc_div2 <- kmeans(svi_divisional_lihtc_cluster2, centers = 2, nstart = 25)
set.seed(123)
k3_lihtc_div2 <- kmeans(svi_divisional_lihtc_cluster2, centers = 3, nstart = 25)
set.seed(123)
k4_lihtc_div2 <- kmeans(svi_divisional_lihtc_cluster2, centers = 4, nstart = 25)
set.seed(123)
k5_lihtc_div2 <- kmeans(svi_divisional_lihtc_cluster2, centers = 5, nstart = 25)

# plots to compare
p_k2_lihtc_div2 <- factoextra::fviz_cluster(k2_lihtc_div2, geom = "point", data = svi_divisional_lihtc_cluster2) + ggtitle("k = 2")

p_k3_lihtc_div2 <- factoextra::fviz_cluster(k3_lihtc_div2, geom = "point", data = svi_divisional_lihtc_cluster2) + ggtitle("k = 3")

p_k4_lihtc_div2 <- factoextra::fviz_cluster(k4_lihtc_div2, geom = "point",  data = svi_divisional_lihtc_cluster2) + ggtitle("k = 4")

p_k5_lihtc_div2 <- factoextra::fviz_cluster(k5_lihtc_div2, geom = "point",  data = svi_divisional_lihtc_cluster2) + ggtitle("k = 5")

grid.arrange(p_k2_lihtc_div2, p_k3_lihtc_div2, p_k4_lihtc_div2, p_k5_lihtc_div2, nrow = 2)

elbow_plot(svi_divisional_lihtc_cluster2)

## [1] 1 2 3 4 5 6 7
## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7

grid.arrange(p_k2_lihtc_div2, p_k3_lihtc_div, nrow = 1)

p_k3_lihtc_div

svi_divisional_lihtc_cluster_label <- as.data.frame(svi_divisional_lihtc_cluster) %>%
                                  rownames_to_column(var = "county_name") %>%
                                  as_tibble() %>%
                                  mutate(cluster = k3_lihtc_div$cluster) %>%
                                  select(county_name, cluster)

svi_divisional_county_lihtc_projects2 <- left_join(svi_divisional_county_lihtc_projects, svi_divisional_lihtc_cluster_label, join_by(county_name == county_name))

# View county counts in each cluster
table(svi_divisional_county_lihtc_projects2$cluster)

## 
## 1 2 3 
## 1 6 1

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

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 1) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_lihtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 1) %>%
  select(flag_count10,post10_lihtc_project_dollars) %>%
  cor(method = "pearson")

##                              flag_count10 post10_lihtc_project_dollars
## flag_count10                           NA                           NA
## post10_lihtc_project_dollars           NA                           NA

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

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 2) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_lihtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 2) %>%
  select(flag_count10,post10_lihtc_project_dollars) %>%
  cor(method = "pearson")

##                              flag_count10 post10_lihtc_project_dollars
## flag_count10                    1.0000000                   -0.2043979
## post10_lihtc_project_dollars   -0.2043979                    1.0000000

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

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 3) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_lihtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 3) %>%
  select(flag_count10,post10_lihtc_project_dollars) %>%
  cor(method = "pearson")

##                              flag_count10 post10_lihtc_project_dollars
## flag_count10                           NA                           NA
## post10_lihtc_project_dollars           NA                           NA

Bivariate Map

# Join our LIHTC projects data with our shapefile geocoordinates
svi_divisional_county_lihtc_sf <- left_join(svi_divisional_county_lihtc_projects, divisional_county_sf, join_by("FIPS_st" == "STATEFP", "FIPS_county" == "COUNTYFP"))

svi_divisional_county_lihtc_sf %>% head(5) %>% 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	geometry
IA	Johnson County	West North Central Division	1	3	475339	\$475,339	19103	19	103	Iowa	2	Midwest Region	4	16	14684	0.0010896	0.8	0.2	19	16880	0.0011256	0.8	0.2	Johnson County, IA	MULTIPOLYGON (((-91.52523 4…
IA	Woodbury County	West North Central Division	1	1	688936	\$688,936	19193	19	193	Iowa	2	Midwest Region	4	12	1912	0.0062762	0.6	1.0	12	1515	0.0079208	0.6	1.0	Woodbury County, IA	MULTIPOLYGON (((-96.38065 4…
KS	Sedgwick County	West North Central Division	1	6	664650	\$664,650	20173	20	173	Kansas	2	Midwest Region	4	68	14728	0.0046171	1.0	0.8	67	15150	0.0044224	1.0	0.8	Sedgwick County, KS	MULTIPOLYGON (((-97.70203 3…
MN	Dakota County	West North Central Division	2	1	2556258	\$2,556,258	27037	27	037	Minnesota	2	Midwest Region	4	12	5268	0.0022779	0.6	0.4	12	5153	0.0023287	0.6	0.4	Dakota County, MN	MULTIPOLYGON (((-92.80258 4…
MN	Hennepin County	West North Central Division	9	21	8327899	\$8,327,899	27053	27	053	Minnesota	2	Midwest Region	4	213	61014	0.0034910	1.0	0.6	184	69185	0.0026595	1.0	0.4	Hennepin County, MN	MULTIPOLYGON (((-93.19432 4…

# Create classes for bivariate mapping 
svi_divisional_county_lihtc_sf <- bi_class(svi_divisional_county_lihtc_sf, x = flag_count10, y = post10_lihtc_project_dollars, style = "quantile", dim = 3)

# View data
svi_divisional_county_lihtc_sf %>% head(5) %>% 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	geometry	bi_class
IA	Johnson County	West North Central Division	1	3	475339	\$475,339	19103	19	103	Iowa	2	Midwest Region	4	16	14684	0.0010896	0.8	0.2	19	16880	0.0011256	0.8	0.2	Johnson County, IA	MULTIPOLYGON (((-91.52523 4…	2-1
IA	Woodbury County	West North Central Division	1	1	688936	\$688,936	19193	19	193	Iowa	2	Midwest Region	4	12	1912	0.0062762	0.6	1.0	12	1515	0.0079208	0.6	1.0	Woodbury County, IA	MULTIPOLYGON (((-96.38065 4…	1-1
KS	Sedgwick County	West North Central Division	1	6	664650	\$664,650	20173	20	173	Kansas	2	Midwest Region	4	68	14728	0.0046171	1.0	0.8	67	15150	0.0044224	1.0	0.8	Sedgwick County, KS	MULTIPOLYGON (((-97.70203 3…	2-1
MN	Dakota County	West North Central Division	2	1	2556258	\$2,556,258	27037	27	037	Minnesota	2	Midwest Region	4	12	5268	0.0022779	0.6	0.4	12	5153	0.0023287	0.6	0.4	Dakota County, MN	MULTIPOLYGON (((-92.80258 4…	1-3
MN	Hennepin County	West North Central Division	9	21	8327899	\$8,327,899	27053	27	053	Minnesota	2	Midwest Region	4	213	61014	0.0034910	1.0	0.6	184	69185	0.0026595	1.0	0.4	Hennepin County, MN	MULTIPOLYGON (((-93.19432 4…	3-3

# Create map with ggplot
svi_divisional_county_lihtc_map <- ggplot() +
  # Map county shapefile, fill with bi_class categories
  geom_sf(data = svi_divisional_county_lihtc_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 LIHTC Tax Dollars")
  ) +
  # Set them to biscale
  bi_theme(base_size = 10)

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

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


# View map
svi_divisional_county_lihtc_bivarmap

saveRDS(svi_divisional_lihtc, file = here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_divisional_lihtc.rds")))

saveRDS(svi_national_lihtc, file = here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_national_lihtc.rds")))

saveRDS(svi_divisional_nmtc, file = here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_divisional_nmtc.rds")))

saveRDS(svi_national_nmtc, file = here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_national_nmtc.rds")))