Visualizing The Intervention - Mountain Division

Library

# Turn off scientific notation
options(scipen=999)

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

Functions

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

SVI Data

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

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

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

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

New Market Tax Credit (NMTC) & Low Income Housing Tax Credit (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
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12

Load 2020 Data

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1	RPL_THEME1	F_THEME1	SPL_THEME2	RPL_THEME2	F_THEME2	SPL_THEME3	RPL_THEME3	F_THEME3	SPL_THEME4	RPL_THEME4	F_THEME4	SPL_THEMES	RPL_THEMES	F_TOTAL
01001020100	01	001	020100	AL	Alabama	Autauga County	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
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10

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
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10

# 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

New Market Tax Credit Data Wrangling

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	Yes
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	Yes
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10	Yes
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	Yes
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12	Yes
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10	Yes

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility
01001020200	01	001	020200	AL	Alabama	Autauga County	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
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
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
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
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
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

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	Yes	0	0	\$0
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	Yes	0	0	\$0
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10	Yes	0	0	\$0
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	Yes	0	0	\$0
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12	Yes	1	9500000	\$9,500,000
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10	Yes	0	0	\$0

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted
01001020200	01	001	020200	AL	Alabama	Autauga County	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%")

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted	post10_nmtc_project_cnt	post10_nmtc_dollars	post10_nmtc_dollars_formatted	nmtc_flag
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.10874	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	Yes	0	0	\$0	0	0	\$0	0
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.96990	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	Yes	0	0	\$0	0	0	\$0	0
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.75235	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10	Yes	0	0	\$0	0	0	\$0	0
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.36798	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	Yes	0	0	\$0	0	0	\$0	0
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.07610	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10	Yes	0	0	\$0	0	0	\$0	0
04001944300	04	001	944300	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	6806	3308	1826	4099	6797	60.30602	0.9762	1	403	1777	22.678672	0.9858	1	154	1457	10.569664	0.02549	0	63	369	17.07317	0.08684	0	217	1826	11.88390	0.01536	0	1432	3367	42.53044	0.9623	1	2305	7092	32.50141	0.9160	1	746	10.960917	0.5176	0	2767	40.65530	0.9761	1	842	4361	19.307498	0.8041	1	357	1163	30.69647	0.8982	1	568	6178	9.193914	0.8423	1	6750	6806	99.17720	0.9944	1	3308	8	0.2418380	0.3113	0	440	13.30109	0.7638	1	404	1826	22.12486	0.9856	1	388	1826	21.24863	0.9627	1	139	6806	2.042316	0.8458	1	3.85566	0.8602	4	4.0383	0.9844	4	0.9944	0.9888	1	3.8692	0.9619	4	12.75756	0.9749	13	5922	2801	2026	3548	5916	59.97295	0.9854	1	67	1402	4.778887	0.5316	0	251	1664	15.084135	0.20570	0	46	362	12.70718	0.05498	0	297	2026	14.659427	0.056430	0	844	3696	22.83550	0.8792	1	2528	5916	42.73158	0.9987	1	793	13.39075	0.4401	0	1663	28.08173	0.7575	1	573	4258.743	13.454674	0.42530	0	301	1112.258	27.06206	0.8474	1	851	5568	15.283764	0.9575	1	5880	5922.449	99.28326	0.9964	1	2801	22	0.7854338	0.3369	0	521	18.60050	0.8557	1	267	2026	13.178677	0.9482	1	297	2025.690	14.66167	0.9158	1	11	5922	0.1857481	0.5222	0	3.451330	0.7773	3	3.42780	0.9008	3	0.9964	0.9922	1	3.5788	0.9040	3	11.45433	0.9088	10	Yes	0	0	\$0	0	0	\$0	0

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	nmtc_eligibility	pre10_nmtc_project_cnt	pre10_nmtc_dollars	pre10_nmtc_dollars_formatted	post10_nmtc_project_cnt	post10_nmtc_dollars	post10_nmtc_dollars_formatted	nmtc_flag
01001020200	01	001	020200	AL	Alabama	Autauga County	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	0	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	0	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	0	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	1	408000	\$408,000	1
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	0	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	1	8000000	\$8,000,000	1

svi_national_nmtc_county_sum <- summarize_county_nmtc(svi_national_nmtc)

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

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

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

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted
AZ	Apache County	Mountain Division	1	14	12544000	\$12,544,000
AZ	Cochise County	Mountain Division	0	16	0	\$0
AZ	Coconino County	Mountain Division	0	13	0	\$0
AZ	Gila County	Mountain Division	1	11	5390000	\$5,390,000
AZ	Graham County	Mountain Division	0	4	0	\$0
AZ	Greenlee County	Mountain Division	0	1	0	\$0

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

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

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

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

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

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

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

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

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
01001	01	001	AL	Alabama	Autauga County	3	South Region	6	East South Central Division	14	7982	0.0017539	0.6	0.8	18	8818	0.0020413	0.6	1.0
01003	01	003	AL	Alabama	Baldwin County	3	South Region	6	East South Central Division	34	38458	0.0008841	0.8	0.4	34	46255	0.0007351	0.8	0.2
01005	01	005	AL	Alabama	Barbour County	3	South Region	6	East South Central Division	43	21287	0.0020200	0.8	1.0	44	18811	0.0023391	0.8	1.0
01007	01	007	AL	Alabama	Bibb County	3	South Region	6	East South Central Division	11	17570	0.0006261	0.4	0.2	16	17663	0.0009058	0.6	0.4
01009	01	009	AL	Alabama	Blount County	3	South Region	6	East South Central Division	12	16995	0.0007061	0.4	0.2	8	16546	0.0004835	0.4	0.2
01011	01	011	AL	Alabama	Bullock County	3	South Region	6	East South Central Division	21	10923	0.0019225	0.6	1.0	18	10173	0.0017694	0.6	0.8

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

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

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

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

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

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

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

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

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

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

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

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

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

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
04001	04	001	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	133	62408	0.0021311	1.0	0.8	124	62852	0.0019729	1.0	0.8
04003	04	003	AZ	Arizona	Cochise County	4	West Region	8	Mountain Division	107	59079	0.0018111	1.0	0.8	101	55503	0.0018197	1.0	0.8
04005	04	005	AZ	Arizona	Coconino County	4	West Region	8	Mountain Division	104	63540	0.0016368	1.0	0.6	89	76227	0.0011676	1.0	0.4
04007	04	007	AZ	Arizona	Gila County	4	West Region	8	Mountain Division	64	31239	0.0020487	1.0	0.8	72	31645	0.0022752	1.0	1.0
04009	04	009	AZ	Arizona	Graham County	4	West Region	8	Mountain Division	24	16443	0.0014596	0.8	0.6	22	15777	0.0013944	0.8	0.6
04011	04	011	AZ	Arizona	Greenlee County	4	West Region	8	Mountain Division	4	2437	0.0016414	0.2	0.6	3	2709	0.0011074	0.2	0.4

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

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

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

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

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name
AZ	Apache County	Mountain Division	1	14	12544000	\$12,544,000	04001	04	001	Arizona	4	West Region	8	133	62408	0.0021311	1.0	0.8	124	62852	0.0019729	1.0	0.8	Apache County, AZ
AZ	Cochise County	Mountain Division	0	16	0	\$0	04003	04	003	Arizona	4	West Region	8	107	59079	0.0018111	1.0	0.8	101	55503	0.0018197	1.0	0.8	Cochise County, AZ
AZ	Coconino County	Mountain Division	0	13	0	\$0	04005	04	005	Arizona	4	West Region	8	104	63540	0.0016368	1.0	0.6	89	76227	0.0011676	1.0	0.4	Coconino County, AZ
AZ	Gila County	Mountain Division	1	11	5390000	\$5,390,000	04007	04	007	Arizona	4	West Region	8	64	31239	0.0020487	1.0	0.8	72	31645	0.0022752	1.0	1.0	Gila County, AZ
AZ	Graham County	Mountain Division	0	4	0	\$0	04009	04	009	Arizona	4	West Region	8	24	16443	0.0014596	0.8	0.6	22	15777	0.0013944	0.8	0.6	Graham County, AZ
AZ	Greenlee County	Mountain Division	0	1	0	\$0	04011	04	011	Arizona	4	West Region	8	4	2437	0.0016414	0.2	0.6	3	2709	0.0011074	0.2	0.4	Greenlee County, AZ

Low Income Housing Tax Credit (LIHTC) Data Wrangling

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

lihtc_eligible_flag %>% head() 

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

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

lihtc_projects10 %>% head() 

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

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

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

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

lihtc_dollars10 %>% head() 

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

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

lihtc_projects10 %>% head()

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

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

lihtc_projects20 %>% head() 

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

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

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

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

lihtc_dollars20 %>% head() 

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

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

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

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

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

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

GEOID_2010_trt	FIPS_st	FIPS_county	FIPS_tract	state	state_name	county	region_number	region	division_number	division	E_TOTPOP_10	E_HU_10	E_HH_10	E_POV150_10	ET_POVSTATUS_10	EP_POV150_10	EPL_POV150_10	F_POV150_10	E_UNEMP_10	ET_EMPSTATUS_10	EP_UNEMP_10	EPL_UNEMP_10	F_UNEMP_10	E_HBURD_OWN_10	ET_HOUSINGCOST_OWN_10	EP_HBURD_OWN_10	EPL_HBURD_OWN_10	F_HBURD_OWN_10	E_HBURD_RENT_10	ET_HOUSINGCOST_RENT_10	EP_HBURD_RENT_10	EPL_HBURD_RENT_10	F_HBURD_RENT_10	E_HBURD_10	ET_HOUSINGCOST_10	EP_HBURD_10	EPL_HBURD_10	F_HBURD_10	E_NOHSDP_10	ET_EDSTATUS_10	EP_NOHSDP_10	EPL_NOHSDP_10	F_NOHSDP_10	E_UNINSUR_12	ET_INSURSTATUS_12	EP_UNINSUR_12	EPL_UNINSUR_12	F_UNINSUR_12	E_AGE65_10	EP_AGE65_10	EPL_AGE65_10	F_AGE65_10	E_AGE17_10	EP_AGE17_10	EPL_AGE17_10	F_AGE17_10	E_DISABL_12	ET_DISABLSTATUS_12	EP_DISABL_12	EPL_DISABL_12	F_DISABL_12	E_SNGPNT_10	ET_FAMILIES_10	EP_SNGPNT_10	EPL_SNGPNT_10	F_SNGPNT_10	E_LIMENG_10	ET_POPAGE5UP_10	EP_LIMENG_10	EPL_LIMENG_10	F_LIMENG_10	E_MINRTY_10	ET_POPETHRACE_10	EP_MINRTY_10	EPL_MINRTY_10	F_MINRTY_10	E_STRHU_10	E_MUNIT_10	EP_MUNIT_10	EPL_MUNIT_10	F_MUNIT_10	E_MOBILE_10	EP_MOBILE_10	EPL_MOBILE_10	F_MOBILE_10	E_CROWD_10	ET_OCCUPANTS_10	EP_CROWD_10	EPL_CROWD_10	F_CROWD_10	E_NOVEH_10	ET_KNOWNVEH_10	EP_NOVEH_10	EPL_NOVEH_10	F_NOVEH_10	E_GROUPQ_10	ET_HHTYPE_10	EP_GROUPQ_10	EPL_GROUPQ_10	F_GROUPQ_10	SPL_THEME1_10	RPL_THEME1_10	F_THEME1_10	SPL_THEME2_10	RPL_THEME2_10	F_THEME2_10	SPL_THEME3_10	RPL_THEME3_10	F_THEME3_10	SPL_THEME4_10	RPL_THEME4_10	F_THEME4_10	SPL_THEMES_10	RPL_THEMES_10	F_TOTAL_10	E_TOTPOP_20	E_HU_20	E_HH_20	E_POV150_20	ET_POVSTATUS_20	EP_POV150_20	EPL_POV150_20	F_POV150_20	E_UNEMP_20	ET_EMPSTATUS_20	EP_UNEMP_20	EPL_UNEMP_20	F_UNEMP_20	E_HBURD_OWN_20	ET_HOUSINGCOST_OWN_20	EP_HBURD_OWN_20	EPL_HBURD_OWN_20	F_HBURD_OWN_20	E_HBURD_RENT_20	ET_HOUSINGCOST_RENT_20	EP_HBURD_RENT_20	EPL_HBURD_RENT_20	F_HBURD_RENT_20	E_HBURD_20	ET_HOUSINGCOST_20	EP_HBURD_20	EPL_HBURD_20	F_HBURD_20	E_NOHSDP_20	ET_EDSTATUS_20	EP_NOHSDP_20	EPL_NOHSDP_20	F_NOHSDP_20	E_UNINSUR_20	ET_INSURSTATUS_20	EP_UNINSUR_20	EPL_UNINSUR_20	F_UNINSUR_20	E_AGE65_20	EP_AGE65_20	EPL_AGE65_20	F_AGE65_20	E_AGE17_20	EP_AGE17_20	EPL_AGE17_20	F_AGE17_20	E_DISABL_20	ET_DISABLSTATUS_20	EP_DISABL_20	EPL_DISABL_20	F_DISABL_20	E_SNGPNT_20	ET_FAMILIES_20	EP_SNGPNT_20	EPL_SNGPNT_20	F_SNGPNT_20	E_LIMENG_20	ET_POPAGE5UP_20	EP_LIMENG_20	EPL_LIMENG_20	F_LIMENG_20	E_MINRTY_20	ET_POPETHRACE_20	EP_MINRTY_20	EPL_MINRTY_20	F_MINRTY_20	E_STRHU_20	E_MUNIT_20	EP_MUNIT_20	EPL_MUNIT_20	F_MUNIT_20	E_MOBILE_20	EP_MOBILE_20	EPL_MOBILE_20	F_MOBILE_20	E_CROWD_20	ET_OCCUPANTS_20	EP_CROWD_20	EPL_CROWD_20	F_CROWD_20	E_NOVEH_20	ET_KNOWNVEH_20	EP_NOVEH_20	EPL_NOVEH_20	F_NOVEH_20	E_GROUPQ_20	ET_HHTYPE_20	EP_GROUPQ_20	EPL_GROUPQ_20	F_GROUPQ_20	SPL_THEME1_20	RPL_THEME1_20	F_THEME1_20	SPL_THEME2_20	RPL_THEME2_20	F_THEME2_20	SPL_THEME3_20	RPL_THEME3_20	F_THEME3_20	SPL_THEME4_20	RPL_THEME4_20	F_THEME4_20	SPL_THEMES_20	RPL_THEMES_20	F_TOTAL_20	pre10_lihtc_project_cnt	pre10_lihtc_project_dollars
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	NA	NA
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	NA	NA
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10	NA	NA
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	NA	NA
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12	NA	NA
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10	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
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.4496	0	560	35.87444	0.9044	1	240	1054	22.770398	0.9006	1	107	332	32.22892	0.9163	1	168	1431	11.740042	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.46875	0.9979	1	33	384	8.59375	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.0540	0.9853	4	0.9989	0.9931	1	3.2390	0.8004	3	11.55631	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.39683	0.9056	1	686	1711	40.09351	0.9973	1	229	13.38399	0.4397	0	347	20.28054	0.3788	0	245	1363.979	17.962156	0.68240	0	49	304.000	16.11842	0.5859	0	155	1652	9.382567	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.00592	0.8736	1	83	469	17.697228	0.9774	1	99	469.000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.98190	0.7375	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	NA	NA	NA	NA
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.6870	0	1530	31.31396	0.7718	1	772	3514	21.969266	0.8839	1	246	939	26.19808	0.8308	1	592	4631	12.783416	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.59024	0.9756	1	188	1291	14.56235	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.0710	0.9870	4	0.9946	0.9890	1	3.1904	0.7848	3	11.95212	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.02321	0.9120	1	1856	5466	33.95536	0.9919	1	759	13.87822	0.4657	0	1555	28.43299	0.7739	1	706	3911.002	18.051640	0.68720	0	257	1035.000	24.83091	0.8039	1	396	5078	7.798346	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.00180	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.001	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.59310	0.9421	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	NA	NA	NA	NA
04001944000	04	001	944000	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	5958	2178	1275	3112	5958	52.23229	0.9399	1	107	1895	5.646438	0.4130	0	108	880	12.272727	0.03476	0	112	395	28.35443	0.19940	0	220	1275	17.25490	0.04955	0	1030	3376	30.50948	0.9015	1	2632	5821	45.21560	0.9873	1	472	7.922122	0.3301	0	1792	30.07721	0.7211	0	299	4027	7.424882	0.1343	0	272	979	27.78345	0.8590	1	153	5325	2.873239	0.6096	0	5846	5958	98.12017	0.9893	1	2178	0	0.0000000	0.1526	0	448	20.56933	0.8562	1	247	1275	19.37255	0.9798	1	135	1275	10.58824	0.8373	1	0	5958	0.000000	0.3955	0	3.29125	0.7314	3	2.6541	0.5792	1	0.9893	0.9836	1	3.2214	0.7946	3	10.15605	0.7714	8	6583	2464	1836	3270	6580	49.69605	0.9486	1	191	2029	9.413504	0.8663	1	89	1272	6.996855	0.01965	0	103	564	18.26241	0.09073	0	192	1836	10.457516	0.015550	0	753	4321	17.42652	0.8100	1	2993	6580	45.48632	0.9992	1	1034	15.70712	0.5561	0	1569	23.83412	0.5584	0	1069	5014.189	21.319499	0.81410	1	304	1237.278	24.57006	0.7989	1	141	6193	2.276764	0.6147	0	6436	6583.375	97.76141	0.9876	1	2464	20	0.8116883	0.3404	0	536	21.75325	0.8793	1	274	1836	14.923747	0.9643	1	326	1836.376	17.752353	0.9488	1	3	6583	0.0455719	0.4382	0	3.639650	0.8211	4	3.34220	0.8770	2	0.9876	0.9834	1	3.5710	0.9020	3	11.54045	0.9156	10	NA	NA	NA	NA
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.2701	0	1993	40.06030	0.9701	1	577	3087	18.691286	0.7799	1	278	893	31.13102	0.9038	1	308	4470	6.890380	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.34551	0.9843	1	212	1204	17.60797	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.7134	0.9528	4	0.9929	0.9872	1	3.5092	0.8926	3	11.90170	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.44983	0.9148	1	1320	6183	21.34886	0.9283	1	637	10.30244	0.2718	0	1869	30.22804	0.8396	1	626	3964.000	15.792129	0.57150	0	371	991.000	37.43693	0.9557	1	315	5717	5.509883	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.57924	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.44070	0.9070	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	NA	NA	NA	NA
04001944201	04	001	944201	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3751	1392	984	2202	3689	59.69097	0.9743	1	242	1082	22.365989	0.9848	1	99	409	24.205379	0.27880	0	92	575	16.00000	0.07805	0	191	984	19.41057	0.07144	0	566	2008	28.18725	0.8822	1	1055	3994	26.41462	0.8304	1	172	4.585444	0.1308	0	1420	37.85657	0.9429	1	229	2320	9.870690	0.2738	0	187	722	25.90028	0.8248	1	200	3509	5.699630	0.7542	1	3521	3751	93.86830	0.9778	1	1392	19	1.3649425	0.4136	0	284	20.40230	0.8539	1	114	984	11.58537	0.9345	1	121	984	12.29675	0.8677	1	266	3751	7.091442	0.9297	1	3.74314	0.8389	4	2.9265	0.7044	3	0.9778	0.9722	1	3.9994	0.9770	4	11.64684	0.9044	12	4540	1421	1193	3069	4456	68.87343	0.9946	1	53	702	7.549857	0.7756	1	83	660	12.575758	0.10750	0	193	533	36.21013	0.34830	0	276	1193	23.134954	0.313200	0	481	2222	21.64716	0.8674	1	2049	4473	45.80818	0.9994	1	523	11.51982	0.3373	0	1898	41.80617	0.9933	1	400	2575.000	15.533981	0.55850	0	260	809.000	32.13844	0.9110	1	351	4008	8.757485	0.8857	1	4377	4540.000	96.40969	0.9834	1	1421	8	0.5629838	0.3099	0	231	16.25616	0.8292	1	226	1193	18.943839	0.9804	1	102	1193.000	8.549874	0.7926	1	83	4540	1.8281938	0.8233	1	3.950200	0.8966	4	3.68580	0.9568	3	0.9834	0.9792	1	3.7354	0.9379	4	12.35480	0.9629	12	NA	NA	NA	NA
04001944202	04	001	944202	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	3330	1463	897	1814	3330	54.47447	0.9514	1	345	1024	33.691406	0.9983	1	58	745	7.785235	0.01352	0	38	152	25.00000	0.15680	0	96	897	10.70234	0.01191	0	742	2041	36.35473	0.9351	1	1201	3754	31.99254	0.9089	1	366	10.990991	0.5201	0	873	26.21622	0.5389	0	573	2986	19.189551	0.8002	1	151	550	27.45455	0.8540	1	173	3057	5.659143	0.7527	1	3306	3330	99.27928	0.9948	1	1463	0	0.0000000	0.1526	0	355	24.26521	0.8840	1	114	897	12.70903	0.9435	1	257	897	28.65106	0.9864	1	93	3330	2.792793	0.8680	1	3.80561	0.8512	4	3.4659	0.8981	3	0.9948	0.9891	1	3.8345	0.9589	4	12.10081	0.9410	12	3507	1508	1209	2113	3507	60.25093	0.9862	1	145	1041	13.928914	0.9605	1	81	1040	7.788462	0.02620	0	26	169	15.38462	0.07170	0	107	1209	8.850290	0.008637	0	403	2250	17.91111	0.8195	1	1457	3507	41.54548	0.9985	1	390	11.12062	0.3153	0	974	27.77303	0.7446	0	114	2533.000	4.500592	0.01399	0	189	717.000	26.35983	0.8350	1	389	3265	11.914242	0.9273	1	3499	3507.000	99.77188	0.9983	1	1508	26	1.7241379	0.4052	0	434	28.77984	0.9188	1	98	1209	8.105873	0.8737	1	146	1209.000	12.076096	0.8761	1	0	3507	0.0000000	0.2155	0	3.773337	0.8552	4	2.83619	0.6678	2	0.9983	0.9941	1	3.2893	0.8112	3	10.89713	0.8589	10	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
04003000901	NA	NA	1	537485
04003001602	NA	NA	1	233539
04007940400	NA	NA	1	547218
04013093001	NA	NA	1	1344402
04013103306	NA	NA	1	202839
04013103612	NA	NA	1	2283858

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
04001942600	04	001	942600	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	1561	762	384	1150	1561	73.67072	0.9944	1	26	300	8.666667	0.6866	0	65	366	17.759563	0.10180	0	5	18	27.77778	0.19090	0	70	384	18.22917	0.05781	0	303	839	36.11442	0.9335	1	282	1578	17.87072	0.5921	0	153	9.801409	0.449600	0	560	35.874440	0.90440	1	240	1054	22.770398	0.90060	1	107	332	32.22892	0.9163	1	168	1431	11.7400419	0.8831	1	1561	1561	100.00000	0.9989	1	762	0	0.0000000	0.1526	0	215	28.21522	0.9088	1	117	384	30.468750	0.9979	1	33	384	8.593750	0.7842	1	0	1561	0.000000	0.3955	0	3.26441	0.7248	2	4.054000	0.98530	4	0.9989	0.9931	1	3.2390	0.8004	3	11.556310	0.8966	10	1711	676	469	930	1711	54.35418	0.9708	1	44	484	9.090909	0.8539	1	32	456	7.017544	0.02013	0	4	13	30.76923	0.24630	0	36	469	7.675906	0.005758	0	304	1197	25.396825	0.9056	1	686	1711	40.093513	0.9973	1	229	13.3839860	0.439700	0	347	20.280538	0.37880	0	245	1363.979	17.962156	0.6824	0	49	304.0000	16.11842	0.5859	0	155	1652	9.3825666	0.8951	1	1711	1710.980	100.00115	1.0000	1	676	0	0.0000000	0.1276	0	142	21.0059172	0.8736	1	83	469	17.697228	0.9774	1	99	469.0000	21.108742	0.9655	1	0	1711	0.0000000	0.2155	0	3.733358	0.8474	4	2.981900	0.73750	1	1.0000	0.9958	1	3.1596	0.7653	3	10.87486	0.8573	9	0	0	0	0	0	Yes
04001942700	04	001	942700	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4886	2757	1291	2616	4871	53.70560	0.9480	1	163	1398	11.659514	0.8577	1	102	1113	9.164421	0.01757	0	54	178	30.33708	0.22790	0	156	1291	12.08366	0.01652	0	1039	2931	35.44865	0.9303	1	1873	5249	35.68299	0.9436	1	688	14.081048	0.687000	0	1530	31.313958	0.77180	1	772	3514	21.969266	0.88390	1	246	939	26.19808	0.8308	1	592	4631	12.7834161	0.8975	1	4846	4886	99.18133	0.9946	1	2757	0	0.0000000	0.1526	0	369	13.38411	0.7652	1	240	1291	18.590240	0.9756	1	188	1291	14.562355	0.9015	1	0	4886	0.000000	0.3955	0	3.69612	0.8288	4	4.071000	0.98700	4	0.9946	0.9890	1	3.1904	0.7848	3	11.952120	0.9295	12	5469	2222	1462	2784	5469	50.90510	0.9557	1	358	1642	21.802680	0.9925	1	114	1151	9.904431	0.04797	0	58	311	18.64952	0.09477	0	172	1462	11.764706	0.023990	0	852	3274	26.023213	0.9120	1	1856	5466	33.955360	0.9919	1	759	13.8782227	0.465700	0	1555	28.432986	0.77390	1	706	3911.002	18.051640	0.6872	0	257	1035.0004	24.83091	0.8039	1	396	5078	7.7983458	0.8624	1	5420	5469.002	99.10401	0.9946	1	2222	0	0.0000000	0.1276	0	400	18.0018002	0.8488	1	238	1462	16.279070	0.9710	1	175	1462.0007	11.969898	0.8742	1	26	5469	0.4754068	0.6430	0	3.876090	0.8796	4	3.593100	0.94210	3	0.9946	0.9905	1	3.4646	0.8721	3	11.92839	0.9425	11	0	0	0	0	0	Yes
04001944100	04	001	944100	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	4975	2485	1204	3251	4968	65.43881	0.9846	1	210	1254	16.746412	0.9576	1	122	905	13.480663	0.04383	0	91	299	30.43478	0.22960	0	213	1204	17.69103	0.05320	0	779	2325	33.50538	0.9203	1	1293	5511	23.46217	0.7705	1	344	6.914573	0.270100	0	1993	40.060302	0.97010	1	577	3087	18.691286	0.77990	1	278	893	31.13102	0.9038	1	308	4470	6.8903803	0.7895	1	4915	4975	98.79397	0.9929	1	2485	21	0.8450704	0.3700	0	428	17.22334	0.8203	1	257	1204	21.345515	0.9843	1	212	1204	17.607973	0.9391	1	0	4975	0.000000	0.3955	0	3.68620	0.8261	4	3.713400	0.95280	4	0.9929	0.9872	1	3.5092	0.8926	3	11.901700	0.9244	12	6183	2379	1424	3704	5789	63.98342	0.9912	1	425	1608	26.430348	0.9954	1	132	1163	11.349957	0.07802	0	38	261	14.55939	0.06498	0	170	1424	11.938202	0.026300	0	862	3259	26.449831	0.9148	1	1320	6183	21.348860	0.9283	1	637	10.3024422	0.271800	0	1869	30.228045	0.83960	1	626	3964.000	15.792129	0.5715	0	371	991.0000	37.43693	0.9557	1	315	5717	5.5098828	0.8021	1	5981	6182.998	96.73300	0.9841	1	2379	0	0.0000000	0.1276	0	442	18.5792350	0.8550	1	379	1424	26.615168	0.9969	1	347	1424.0000	24.367977	0.9758	1	394	6183	6.3723112	0.9380	1	3.856000	0.8749	4	3.440700	0.90700	3	0.9841	0.9800	1	3.8933	0.9609	4	12.17410	0.9549	12	0	0	0	0	0	Yes
04001944300	04	001	944300	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	6806	3308	1826	4099	6797	60.30602	0.9762	1	403	1777	22.678672	0.9858	1	154	1457	10.569664	0.02549	0	63	369	17.07317	0.08684	0	217	1826	11.88390	0.01536	0	1432	3367	42.53044	0.9623	1	2305	7092	32.50141	0.9160	1	746	10.960917	0.517600	0	2767	40.655304	0.97610	1	842	4361	19.307498	0.80410	1	357	1163	30.69647	0.8982	1	568	6178	9.1939139	0.8423	1	6750	6806	99.17720	0.9944	1	3308	8	0.2418380	0.3113	0	440	13.30109	0.7638	1	404	1826	22.124863	0.9856	1	388	1826	21.248631	0.9627	1	139	6806	2.042316	0.8458	1	3.85566	0.8602	4	4.038300	0.98440	4	0.9944	0.9888	1	3.8692	0.9619	4	12.757560	0.9749	13	5922	2801	2026	3548	5916	59.97295	0.9854	1	67	1402	4.778887	0.5316	0	251	1664	15.084135	0.20570	0	46	362	12.70718	0.05498	0	297	2026	14.659427	0.056430	0	844	3696	22.835498	0.8792	1	2528	5916	42.731575	0.9987	1	793	13.3907464	0.440100	0	1663	28.081729	0.75750	1	573	4258.743	13.454674	0.4253	0	301	1112.2581	27.06206	0.8474	1	851	5568	15.2837644	0.9575	1	5880	5922.449	99.28326	0.9964	1	2801	22	0.7854338	0.3369	0	521	18.6004998	0.8557	1	267	2026	13.178677	0.9482	1	297	2025.6898	14.661672	0.9158	1	11	5922	0.1857481	0.5222	0	3.451330	0.7773	3	3.427800	0.90080	3	0.9964	0.9922	1	3.5788	0.9040	3	11.45433	0.9088	10	0	0	0	0	0	Yes
04005000800	04	005	000800	AZ	Arizona	Coconino County	4	West Region	8	Mountain Division	3912	1200	1057	1511	2859	52.85065	0.9430	1	54	1952	2.766393	0.1150	0	71	192	36.979167	0.73370	0	509	865	58.84393	0.83080	1	580	1057	54.87228	0.96160	1	265	1897	13.96943	0.6489	0	995	3589	27.72360	0.8536	1	121	3.093047	0.062070	0	208	5.316973	0.02835	0	248	3170	7.823344	0.15510	0	53	311	17.04180	0.5919	0	26	3898	0.6670087	0.3063	0	1410	3912	36.04294	0.6285	0	1200	155	12.9166667	0.7329	0	3	0.25000	0.3706	0	31	1057	2.932829	0.6261	0	33	1057	3.122044	0.4682	0	1043	3912	26.661554	0.9826	1	3.52210	0.7887	3	1.143720	0.02019	0	0.6285	0.6250	0	3.1804	0.7810	1	8.474720	0.5850	4	6428	2343	2163	3238	5850	55.35043	0.9741	1	399	3753	10.631495	0.9047	1	43	312	13.782051	0.15050	0	1188	1850	64.21622	0.93540	1	1231	2162	56.938020	0.988900	1	364	2823	12.894084	0.7116	0	478	5900	8.101695	0.4937	0	262	4.0759179	0.030250	0	634	9.863099	0.06202	0	497	5227.333	9.507716	0.1782	0	112	544.6422	20.56396	0.7139	0	56	6207	0.9022072	0.4074	0	2862	6428.175	44.52274	0.6490	0	2343	838	35.7661118	0.9165	1	11	0.4694836	0.4053	0	116	2163	5.362922	0.7808	1	166	2162.6681	7.675704	0.7658	1	759	6428	11.8077162	0.9625	1	4.073000	0.9190	3	1.391770	0.04857	0	0.6490	0.6463	0	3.8309	0.9524	4	9.94467	0.7611	7	0	0	0	0	0	Yes
04005001000	04	005	001000	AZ	Arizona	Coconino County	4	West Region	8	Mountain Division	7519	863	763	1197	1744	68.63532	0.9894	1	1067	4202	25.392670	0.9925	1	17	25	68.000000	0.99610	1	484	738	65.58266	0.91810	1	501	763	65.66186	0.99650	1	47	886	5.30474	0.2676	0	1429	8331	17.15280	0.5641	0	0	0.000000	0.003736	0	310	4.122889	0.02165	0	54	1560	3.461539	0.01727	0	23	174	13.21839	0.4495	0	233	7411	3.1439752	0.6314	0	2495	7519	33.18260	0.5941	0	863	441	51.1008111	0.9666	1	35	4.05562	0.6079	0	14	763	1.834862	0.4856	0	119	763	15.596330	0.9127	1	5775	7519	76.805426	0.9946	1	3.81010	0.8520	3	1.123556	0.01848	0	0.5941	0.5907	0	3.9674	0.9733	3	9.495156	0.7036	6	13499	815	675	1056	1313	80.42650	0.9987	1	1353	6344	21.327238	0.9918	1	22	35	62.857143	0.99810	1	500	641	78.00312	0.99310	1	522	676	77.218935	0.999600	1	29	460	6.304348	0.4346	0	1051	13483	7.795001	0.4716	0	17	0.1259353	0.004211	0	221	1.637158	0.01474	0	125	1282.667	9.745322	0.1874	0	42	114.3578	36.72685	0.9505	1	207	13491	1.5343562	0.5203	0	4803	13498.825	35.58088	0.5539	0	815	550	67.4846626	0.9864	1	7	0.8588957	0.4653	0	62	675	9.185185	0.8933	1	134	675.3319	19.842095	0.9607	1	12185	13499	90.2659456	0.9960	1	3.896300	0.8850	3	1.677151	0.11070	1	0.5539	0.5516	0	4.3017	0.9882	4	10.42905	0.8107	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
AZ	Apache County	Mountain Division	0	4	0	\$0
AZ	Coconino County	Mountain Division	0	2	0	\$0
AZ	Gila County	Mountain Division	1	2	547218	\$547,218
AZ	Graham County	Mountain Division	0	1	0	\$0
AZ	Maricopa County	Mountain Division	14	48	13115292	\$13,115,292
AZ	Mohave County	Mountain Division	0	2	0	\$0

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

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

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

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

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

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

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

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

fips_county_st	FIPS_st	FIPS_county	state	state_name	county	region_number	region	division_number	division	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20
01005	01	005	AL	Alabama	Barbour County	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
04001	04	001	AZ	Arizona	Apache County	4	West Region	8	Mountain Division	47	18228	0.0025785	1.0	0.6	42	19285	0.0021779	1.0	0.6
04005	04	005	AZ	Arizona	Coconino County	4	West Region	8	Mountain Division	10	11431	0.0008748	0.4	0.2	15	19927	0.0007527	0.6	0.2
04007	04	007	AZ	Arizona	Gila County	4	West Region	8	Mountain Division	21	7245	0.0028986	0.8	0.8	18	8214	0.0021914	0.8	0.6
04009	04	009	AZ	Arizona	Graham County	4	West Region	8	Mountain Division	11	4838	0.0022737	0.4	0.4	9	4698	0.0019157	0.4	0.4
04013	04	013	AZ	Arizona	Maricopa County	4	West Region	8	Mountain Division	487	168865	0.0028840	1.0	0.8	447	185321	0.0024120	1.0	0.6
04015	04	015	AZ	Arizona	Mohave County	4	West Region	8	Mountain Division	15	9008	0.0016652	0.6	0.2	18	12190	0.0014766	0.8	0.4

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
AZ	Apache County	Mountain Division	0	4	0	\$0	04001	04	001	Arizona	4	West Region	8	47	18228	0.0025785	1.0	0.6	42	19285	0.0021779	1.0	0.6	Apache County, AZ
AZ	Coconino County	Mountain Division	0	2	0	\$0	04005	04	005	Arizona	4	West Region	8	10	11431	0.0008748	0.4	0.2	15	19927	0.0007527	0.6	0.2	Coconino County, AZ
AZ	Gila County	Mountain Division	1	2	547218	\$547,218	04007	04	007	Arizona	4	West Region	8	21	7245	0.0028986	0.8	0.8	18	8214	0.0021914	0.8	0.6	Gila County, AZ
AZ	Graham County	Mountain Division	0	1	0	\$0	04009	04	009	Arizona	4	West Region	8	11	4838	0.0022737	0.4	0.4	9	4698	0.0019157	0.4	0.4	Graham County, AZ
AZ	Maricopa County	Mountain Division	14	48	13115292	\$13,115,292	04013	04	013	Arizona	4	West Region	8	487	168865	0.0028840	1.0	0.8	447	185321	0.0024120	1.0	0.6	Maricopa County, AZ
AZ	Mohave County	Mountain Division	0	2	0	\$0	04015	04	015	Arizona	4	West Region	8	15	9008	0.0016652	0.6	0.2	18	12190	0.0014766	0.8	0.4	Mohave County, AZ

Mountain Division Exploratory Data Analysis

2010 NMTC in Mountain Division

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

Data Summary Statistics

summary(svi_divisional_county_nmtc_projects$flag_count10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    3.00   14.75   47.00  176.59  134.50 2558.00

summary(svi_divisional_county_nmtc_projects$post10_nmtc_project_dollars)

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
##    800000   7098250  12512000  25703730  22586125 225315967

There is a large spread within counties receiving NMTC in the Mountain division with SVI flag counts ranging from 5 - 2558, and the NMTC dollars ranging from $800,000 to $225,215,967. Here we can view this in a scatterplot:

# 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()) 

Here we can also see several outliers that are skewing the medians of our data.

Correlation between flag count and NMTC dollars spent within counties

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

## [1] 0.6174326

A Pearson’s R calculation of 0.62 suggests that there is a strong positive association between the dollar amount spent in NMTC from 2011-2020 and the flag count within the Mountain Division counties in 2010.

Let’s look at a box plot to examine this further:

boxplot(svi_divisional_county_nmtc_projects$flag_count10)

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

## [1] 2558 1569  771  473  444  390

The boxplot shows most of our data lies within the lower quadrant of flag counts. Additionally, there are 6 outliers identified. There are identified here:

svi_divisional_county_nmtc_projects %>% 
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) %>% 
  arrange(desc(flag_count10)) %>% 
  head(6) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")

county_name	flag_count10	post10_nmtc_dollars_formatted
Maricopa County, AZ	2558	\$84,923,464
Clark County, NV	1569	\$225,315,967
Pima County, AZ	771	\$36,122,128
Denver County, CO	473	\$78,905,000
Bernalillo County, NM	444	\$74,237,755
Adams County, CO	390	\$11,168,200

Let’s examine our major outlier, Maricopa County, AZ data point further:

svi_divisional_nmtc %>% filter(county == "Maricopa County") %>% select(GEOID_2010_trt, F_TOTAL_10, post10_nmtc_dollars) %>% summary()

##  GEOID_2010_trt       F_TOTAL_10     post10_nmtc_dollars
##  Length:322         Min.   : 1.000   Min.   :       0   
##  Class :character   1st Qu.: 5.000   1st Qu.:       0   
##  Mode  :character   Median : 9.000   Median :       0   
##                     Mean   : 7.944   Mean   :  263737   
##                     3rd Qu.:11.000   3rd Qu.:       0   
##                     Max.   :14.000   Max.   :22900000

There are 322 tracts in Maricopa County, with a median divisional flag count of 9 flags, so it makes sense for Maricopa County to have 2558 flags. This is lower than the average 47 flags in the Mountain Division. Interestingly, Maricopa County, while having the highest number of flag counts in the Mountain Division, has not received the highest amount of NMTC dollars.

K-Means Clustering

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
## Apache County, AZ                    -0.3541120   -0.1073628
## Gila County, AZ                      -0.5466172   -0.2773136
## Maricopa County, AZ                   1.5935295    5.8655464
## Navajo County, AZ                     0.5497734    0.0182530
## Pima County, AZ                       0.2803462    1.4640665

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)

In visually inspecting our plots, it appears that k=3 has the best grouping to the eye, with no overlap in the groups.

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

In looking at our elbow plot, it appears that there is not much variation between point 3 and 4. This aligns well with our visual observation.

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

p_k3_nmtc_div

Here we will assign these 3 clusters to our county data set:

svi_divisional_nmtc_cluster_label <- as.data.frame(svi_divisional_nmtc_cluster) %>%
                                  rownames_to_column(var = "county_name") %>%
                                  as_tibble() %>%
                                  mutate(cluster = k3_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  3 
## 47  7  2

Cluster 1

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

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

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                  1.00000000                 -0.07984396
## post10_nmtc_project_dollars  -0.07984396                  1.00000000

This cluster contains the majority of our counties that received NMTC funding and shows a very weak negative, or no association correlation between flag counts from 2010 census data and money received the following decade from NMTC.

Here are the counties that fall into cluster 1:

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
Apache County, AZ	133	\$12,544,000
Gila County, AZ	64	\$5,390,000
Pinal County, AZ	220	\$37,224,559
Yuma County, AZ	288	\$1,454,000
Adams County, CO	390	\$11,168,200
Arapahoe County, CO	298	\$11,357,669
Archuleta County, CO	7	\$1,950,000
Boulder County, CO	115	\$1,500,000
Delta County, CO	8	\$1,009,700
Jefferson County, CO	120	\$5,880,000
Larimer County, CO	98	\$12,340,000
Mesa County, CO	55	\$800,000
Washington County, CO	4	\$9,640,000
Bannock County, ID	28	\$22,425,000
Madison County, ID	17	\$43,440,000
Valley County, ID	3	\$21,148,000
Big Horn County, MT	33	\$8,624,000
Cascade County, MT	45	\$10,189,000
Chouteau County, MT	4	\$7,663,000
Gallatin County, MT	11	\$6,960,000
Glacier County, MT	20	\$7,129,500
Hill County, MT	13	\$7,081,000
Lake County, MT	11	\$16,715,500
Lewis and Clark County, MT	9	\$23,069,500
Missoula County, MT	15	\$17,945,000
Roosevelt County, MT	14	\$7,104,000
Silver Bow County, MT	12	\$16,056,000
Yellowstone County, MT	39	\$43,880,900
Chaves County, NM	64	\$14,550,000
Dona Ana County, NM	243	\$18,187,500
Eddy County, NM	20	\$19,400,000
McKinley County, NM	139	\$18,460,000
San Juan County, NM	89	\$10,690,000
San Miguel County, NM	53	\$8,330,000
Sandoval County, NM	61	\$12,480,000
Santa Fe County, NM	110	\$16,045,000
Douglas County, NV	5	\$10,500,000
Elko County, NV	23	\$30,000,000
Lyon County, NV	30	\$2,520,000
Nye County, NV	32	\$2,000,000
Washoe County, NV	273	\$2,810,000
Grand County, UT	3	\$18,378,750
Iron County, UT	29	\$18,625,000
Utah County, UT	133	\$2,950,000
Albany County, WY	15	\$17,460,000
Fremont County, WY	18	\$10,874,750
Goshen County, WY	6	\$6,556,800

Cluster 2

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

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

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

Cluster 2

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                    1.000000                   -0.462471
## post10_nmtc_project_dollars    -0.462471                    1.000000

This cluster group contained only 7 data points, and shows a moderate negative correlation (Pearson’s R of -0.46) between flag count in 2010 and NMTC money received the following decade.

These are our Cluster 2 counties:

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 2) %>%
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) 

##             county_name flag_count10 post10_nmtc_dollars_formatted
## 1     Navajo County, AZ          184                   $46,134,750
## 2       Pima County, AZ          771                   $36,122,128
## 3     Denver County, CO          473                   $78,905,000
## 4     Canyon County, ID          111                   $76,432,000
## 5 Bernalillo County, NM          444                   $74,237,755
## 6     Cibola County, NM           49                   $91,548,630
## 7  Salt Lake County, UT          310                  $113,282,833

Cluster 3

# Cluster 3 Scatterplot
# y is our independent variable (NMTC Project Dollars),  
# x is our dependent variable (SVI flag count)

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 3) %>%
  ggplot2::ggplot(aes(x=flag_count10,
                    y=post10_nmtc_project_dollars)) +
        geom_point() +
        geom_smooth(method="lm") +
        scale_y_continuous(labels = scales::dollar_format()) 

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 3) %>%
  select(flag_count10,post10_nmtc_project_dollars) %>%
  cor(method = "pearson")

##                             flag_count10 post10_nmtc_project_dollars
## flag_count10                           1                          -1
## post10_nmtc_project_dollars           -1                           1

In looking at our correlation for cluster 3 which contain our outliers, a Pearson’s R score of -1 shows a high negative correlation within our cluster between flag count and money received in these 2 counties. However, we know that there are only 2 data points in this cluster.

These are the 2 counties in Cluster 3:

svi_divisional_county_nmtc_projects2 %>% 
  filter(cluster == 3) %>%
  select(county_name, flag_count10, post10_nmtc_dollars_formatted) 

##           county_name flag_count10 post10_nmtc_dollars_formatted
## 1 Maricopa County, AZ         2558                   $84,923,464
## 2    Clark County, NV         1569                  $225,315,967

Overall, if we look at cluster 1, we see that it contains the majority of our data. It also shows that for the majority of our data points, there is almost no correlation between the amount of money received in NMTC and the SVI vulnerability flag count.

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: -113.3542 ymin: 31.3325 xmax: -109.0452 ymax: 37.0032
## Geodetic CRS:  NAD83
##   COUNTYFP STATEFP                       geometry
## 1      001      04 MULTIPOLYGON (((-109.0464 3...
## 2      003      04 MULTIPOLYGON (((-110.0031 3...
## 3      005      04 MULTIPOLYGON (((-112.3754 3...
## 4      007      04 MULTIPOLYGON (((-111.2865 3...
## 5      009      04 MULTIPOLYGON (((-110.4486 3...

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

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

State	County	Division	post10_nmtc_project_cnt	tract_cnt	post10_nmtc_project_dollars	post10_nmtc_dollars_formatted	fips_county_st	FIPS_st	FIPS_county	state_name	region_number	region	division_number	flag_count10	pop10	flag_by_pop10	flag_count_quantile10	flag_pop_quantile10	flag_count20	pop20	flag_by_pop20	flag_count_quantile20	flag_pop_quantile20	county_name	geometry
AZ	Apache County	Mountain Division	1	14	12544000	\$12,544,000	04001	04	001	Arizona	4	West Region	8	133	62408	0.0021311	1	0.8	124	62852	0.0019729	1	0.8	Apache County, AZ	MULTIPOLYGON (((-109.0464 3…
AZ	Gila County	Mountain Division	1	11	5390000	\$5,390,000	04007	04	007	Arizona	4	West Region	8	64	31239	0.0020487	1	0.8	72	31645	0.0022752	1	1.0	Gila County, AZ	MULTIPOLYGON (((-111.2865 3…
AZ	Maricopa County	Mountain Division	15	322	84923464	\$84,923,464	04013	04	013	Arizona	4	West Region	8	2558	1355508	0.0018871	1	0.8	2457	1547710	0.0015875	1	0.6	Maricopa County, AZ	MULTIPOLYGON (((-112.9158 3…
AZ	Navajo County	Mountain Division	2	24	46134750	\$46,134,750	04017	04	017	Arizona	4	West Region	8	184	83885	0.0021935	1	1.0	200	87599	0.0022831	1	1.0	Navajo County, AZ	MULTIPOLYGON (((-110.7021 3…
AZ	Pima County	Mountain Division	7	104	36122128	\$36,122,128	04019	04	019	Arizona	4	West Region	8	771	433051	0.0017804	1	0.8	826	439374	0.0018799	1	0.8	Pima County, AZ	MULTIPOLYGON (((-112.3881 3…

# 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
AZ	Apache County	Mountain Division	1	14	12544000	\$12,544,000	04001	04	001	Arizona	4	West Region	8	133	62408	0.0021311	1	0.8	124	62852	0.0019729	1	0.8	Apache County, AZ	MULTIPOLYGON (((-109.0464 3…	3-2
AZ	Gila County	Mountain Division	1	11	5390000	\$5,390,000	04007	04	007	Arizona	4	West Region	8	64	31239	0.0020487	1	0.8	72	31645	0.0022752	1	1.0	Gila County, AZ	MULTIPOLYGON (((-111.2865 3…	2-1
AZ	Maricopa County	Mountain Division	15	322	84923464	\$84,923,464	04013	04	013	Arizona	4	West Region	8	2558	1355508	0.0018871	1	0.8	2457	1547710	0.0015875	1	0.6	Maricopa County, AZ	MULTIPOLYGON (((-112.9158 3…	3-3
AZ	Navajo County	Mountain Division	2	24	46134750	\$46,134,750	04017	04	017	Arizona	4	West Region	8	184	83885	0.0021935	1	1.0	200	87599	0.0022831	1	1.0	Navajo County, AZ	MULTIPOLYGON (((-110.7021 3…	3-3
AZ	Pima County	Mountain Division	7	104	36122128	\$36,122,128	04019	04	019	Arizona	4	West Region	8	771	433051	0.0017804	1	0.8	826	439374	0.0018799	1	0.8	Pima County, AZ	MULTIPOLYGON (((-112.3881 3…	3-3

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

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

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


# View map
svi_divisional_county_nmtc_bivarmap

Here we can see the distribution of SVI flag counts and NMTC dollars spent in each county receiving funds. Montana, Idaho, and Wyoming received high dollars compared to low flag counts, indicated by the blue color.

svi_divisional_county_nmtc_sf %>% filter(State %in% c("MT", "ID", "WY")) %>%
  arrange(desc(post10_nmtc_project_dollars), flag_count10) %>% select(State, County, flag_count10, post10_nmtc_dollars_formatted) %>% head(10) 

##    State                 County flag_count10 post10_nmtc_dollars_formatted
## 1     ID          Canyon County          111                   $76,432,000
## 2     MT     Yellowstone County           39                   $43,880,900
## 3     ID         Madison County           17                   $43,440,000
## 4     MT Lewis and Clark County            9                   $23,069,500
## 5     ID         Bannock County           28                   $22,425,000
## 6     ID          Valley County            3                   $21,148,000
## 7     MT        Missoula County           15                   $17,945,000
## 8     WY          Albany County           15                   $17,460,000
## 9     MT            Lake County           11                   $16,715,500
## 10    MT      Silver Bow County           12                   $16,056,000

Nevada received the most dollars in the highest need counties, indicated by the purple dark purple color.

svi_divisional_county_nmtc_sf %>% filter(State %in% c("NV", "NM")) %>% select(State, County, flag_count10, post10_nmtc_dollars_formatted) %>% arrange(desc(flag_count10)) %>% head(10) 

##    State            County flag_count10 post10_nmtc_dollars_formatted
## 1     NV      Clark County         1569                  $225,315,967
## 2     NM Bernalillo County          444                   $74,237,755
## 3     NV     Washoe County          273                    $2,810,000
## 4     NM   Dona Ana County          243                   $18,187,500
## 5     NM   McKinley County          139                   $18,460,000
## 6     NM   Santa Fe County          110                   $16,045,000
## 7     NM   San Juan County           89                   $10,690,000
## 8     NM     Chaves County           64                   $14,550,000
## 9     NM   Sandoval County           61                   $12,480,000
## 10    NM San Miguel County           53                    $8,330,000

2010 Low Income Housing Tax Credit Mountain Division

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

svi_divisional_county_lihtc_projects %>% select(Division) %>% unique()

##            Division
## 1 Mountain Division

Data Summary Statistics

summary(svi_divisional_county_lihtc_projects$flag_count10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    9.00   15.50   21.00   67.33   56.50  487.00

summary(svi_divisional_county_lihtc_projects$post10_lihtc_project_dollars)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##        0   674696  1721391  3350971  3203130 15437500

Filter out counties with LIHTC projects but did not receive any funding:

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

summary(svi_divisional_county_lihtc_projects$flag_count10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    9.00   14.75   21.00   64.64   33.75  487.00

summary(svi_divisional_county_lihtc_projects$post10_lihtc_project_dollars)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##   270127   817782  1836756  3590326  3380196 15437500

The Mountain division counties receiving LIHTC project funding between 2011-2020, had a range of 9 to 487 SVI flags in 2010. The funding amounts ranged from $270,127 and $15,437,500. There is a large range between counties in the number of SVI flags in 2010 and funding dollars spent between 2011 and 2020.

Let’s view this data visually in a scatterplot:

# 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()) 

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

Here we can see 1 outlier in dollars spent.

Pearson’s R Correlation between SVI flag count and LIHTC dollars spent

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

## [1] 0.5743274

Overall, within all the counties in the Mountain Division, there is a moderate positive correlation between SVI flags from 2010 and dollars spent on LIHTC in 2011-2020, with a Pearson’s score of 0.57.

Here is a boxplot of this data:

boxplot(svi_divisional_county_lihtc_projects$flag_count10)

Here we can see three outliers, with high flag counts:

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

## [1] 487 136  76

svi_divisional_county_lihtc_projects %>% filter(flag_count10 == 487) %>% select(county_name, flag_count10, post10_lihtc_dollars_formatted) %>% head() 

##           county_name flag_count10 post10_lihtc_dollars_formatted
## 1 Maricopa County, AZ          487                    $13,115,292

Again, we can see that Maricopa County is also an outlier in flag counts.

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
## Gila County, AZ                     -0.639463325  -0.34550646
## Maricopa County, AZ                  2.001527998   3.34366562
## Pima County, AZ                     -0.006948156   0.56491154
## Yuma County, AZ                     -0.572769441  -0.34550646
## Denver County, CO                    0.343739090   0.08991085

Let’s look at different cluster groupings:

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)

Visually, 2 clusters looks to capture our data points best, but we can check an elbow plot:

elbow_plot(svi_divisional_lihtc_cluster)

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

This elbow plot shows that 3 clusters makes sense, as the spacing does not decrease until after point 3. I will choose to use three clusters for the LIHTC data for the Mountain Division:

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

p_k3_lihtc_div

Let’s assign these clusters to our county data:

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 12  1

Again this was our scatterplot and Pearson’s R for the overall data:

# Overall Scatterplot
# y is our independent variable (LIHTC Project Dollars),  
# x is our dependent variable (SVI flag count)
ggplot2::ggplot(svi_divisional_county_lihtc_projects2,
                aes(x=flag_count10,
                    y=post10_lihtc_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_lihtc_projects2$flag_count10, svi_divisional_county_lihtc_projects2$post10_lihtc_project_dollars, method = "pearson")

## [1] 0.5743274

Cluster 1

# Cluster 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()) 

We only have 1 data point in cluster 1, so we cannot calculate correlation. Here is our county information:

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 1) %>%
  select(county_name, flag_count10, post10_lihtc_dollars_formatted) %>% 
  arrange(desc(flag_count10)) %>% head(10) 

##           county_name flag_count10 post10_lihtc_dollars_formatted
## 1 Maricopa County, AZ          487                    $13,115,292

Again, Maricopa County stands out as an outlier.

Cluster 2

# Cluster 2 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                    0.6788349
## post10_lihtc_project_dollars    0.6788349                    1.0000000

Cluster 2 contains all but 2 of our data points. With a Pearson’s R of 0.68, there is a strong correlation between LIHTC dollars and SVI need.

Here are the 12 counties in this cluster:

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 2) %>%
  select(county_name, flag_count10, post10_lihtc_dollars_formatted) %>% 
  arrange(desc(flag_count10)) %>% head(12) 

##             county_name flag_count10 post10_lihtc_dollars_formatted
## 1       Pima County, AZ          136                     $3,557,261
## 2     Denver County, CO           76                     $5,226,128
## 3       Utah County, UT           37                     $1,721,391
## 4   San Juan County, NM           24                       $802,175
## 5       Gila County, AZ           21                       $547,218
## 6       Yuma County, AZ           21                       $864,604
## 7    Larimer County, CO           21                     $2,609,648
## 8    El Paso County, CO           20                     $1,011,891
## 9   Big Horn County, MT           17                     $2,849,000
## 10 Salt Lake County, UT           14                     $1,952,122
## 11    Canyon County, ID            9                       $300,210
## 12   Fremont County, WY            9                       $270,127

Cluster 3

# Cluster 3 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()) 

Cluster 3 only contains 1 data point so there is no correlation information for this cluster. Here is the county information for this cluster:

svi_divisional_county_lihtc_projects2 %>% 
  filter(cluster == 3) %>%
  select(county_name, flag_count10, post10_lihtc_dollars_formatted) %>% 
  arrange(desc(flag_count10)) %>% head(10) 

##       county_name flag_count10 post10_lihtc_dollars_formatted
## 1 Mesa County, CO           13                    $15,437,500

**In summary, after clustering, we pulled out 1 county outlier with a high flag count (Maricopa County, AZ) and 1 county outlier with a high dollar amount (Mesa County, CO), and our correlation between LIHTC funding received in 2011-2020 is strongly correlated with the SVI vulnerability flag count in 2010.

Bivariate Mapping

# 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) 

##   State          County          Division post10_lihtc_project_cnt tract_cnt
## 1    AZ     Gila County Mountain Division                        1         2
## 2    AZ Maricopa County Mountain Division                       14        48
## 3    AZ     Pima County Mountain Division                        4        17
## 4    AZ     Yuma County Mountain Division                        1         2
## 5    CO   Denver County Mountain Division                        6         8
##   post10_lihtc_project_dollars post10_lihtc_dollars_formatted fips_county_st
## 1                       547218                       $547,218          04007
## 2                     13115292                    $13,115,292          04013
## 3                      3557261                     $3,557,261          04019
## 4                       864604                       $864,604          04027
## 5                      5226128                     $5,226,128          08031
##   FIPS_st FIPS_county state_name region_number      region division_number
## 1      04         007    Arizona             4 West Region               8
## 2      04         013    Arizona             4 West Region               8
## 3      04         019    Arizona             4 West Region               8
## 4      04         027    Arizona             4 West Region               8
## 5      08         031   Colorado             4 West Region               8
##   flag_count10  pop10 flag_by_pop10 flag_count_quantile10 flag_pop_quantile10
## 1           21   7245   0.002898551                   0.8                 0.8
## 2          487 168865   0.002883961                   1.0                 0.8
## 3          136  68218   0.001993609                   1.0                 0.4
## 4           21  10732   0.001956765                   0.8                 0.4
## 5           76  29499   0.002576359                   1.0                 0.6
##   flag_count20  pop20 flag_by_pop20 flag_count_quantile20 flag_pop_quantile20
## 1           18   8214   0.002191381                   0.8                 0.6
## 2          447 185321   0.002412031                   1.0                 0.6
## 3          158  73456   0.002150948                   1.0                 0.4
## 4           21  12232   0.001716808                   0.8                 0.4
## 5           41  33146   0.001236952                   1.0                 0.2
##           county_name                       geometry
## 1     Gila County, AZ MULTIPOLYGON (((-111.2865 3...
## 2 Maricopa County, AZ MULTIPOLYGON (((-112.9158 3...
## 3     Pima County, AZ MULTIPOLYGON (((-112.3881 3...
## 4     Yuma County, AZ MULTIPOLYGON (((-114.7546 3...
## 5   Denver County, CO MULTIPOLYGON (((-104.9341 3...

# 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) 

##   State          County          Division post10_lihtc_project_cnt tract_cnt
## 1    AZ     Gila County Mountain Division                        1         2
## 2    AZ Maricopa County Mountain Division                       14        48
## 3    AZ     Pima County Mountain Division                        4        17
## 4    AZ     Yuma County Mountain Division                        1         2
## 5    CO   Denver County Mountain Division                        6         8
##   post10_lihtc_project_dollars post10_lihtc_dollars_formatted fips_county_st
## 1                       547218                       $547,218          04007
## 2                     13115292                    $13,115,292          04013
## 3                      3557261                     $3,557,261          04019
## 4                       864604                       $864,604          04027
## 5                      5226128                     $5,226,128          08031
##   FIPS_st FIPS_county state_name region_number      region division_number
## 1      04         007    Arizona             4 West Region               8
## 2      04         013    Arizona             4 West Region               8
## 3      04         019    Arizona             4 West Region               8
## 4      04         027    Arizona             4 West Region               8
## 5      08         031   Colorado             4 West Region               8
##   flag_count10  pop10 flag_by_pop10 flag_count_quantile10 flag_pop_quantile10
## 1           21   7245   0.002898551                   0.8                 0.8
## 2          487 168865   0.002883961                   1.0                 0.8
## 3          136  68218   0.001993609                   1.0                 0.4
## 4           21  10732   0.001956765                   0.8                 0.4
## 5           76  29499   0.002576359                   1.0                 0.6
##   flag_count20  pop20 flag_by_pop20 flag_count_quantile20 flag_pop_quantile20
## 1           18   8214   0.002191381                   0.8                 0.6
## 2          447 185321   0.002412031                   1.0                 0.6
## 3          158  73456   0.002150948                   1.0                 0.4
## 4           21  12232   0.001716808                   0.8                 0.4
## 5           41  33146   0.001236952                   1.0                 0.2
##           county_name                       geometry bi_class
## 1     Gila County, AZ MULTIPOLYGON (((-111.2865 3...      2-1
## 2 Maricopa County, AZ MULTIPOLYGON (((-112.9158 3...      3-3
## 3     Pima County, AZ MULTIPOLYGON (((-112.3881 3...      3-3
## 4     Yuma County, AZ MULTIPOLYGON (((-114.7546 3...      2-1
## 5   Denver County, CO MULTIPOLYGON (((-104.9341 3...      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

Here we can see that Idaho and Nevada did not receive any LIHTC project funding in 2011-2020. Again, Arizona has the counties with the highest need and the highest amount of LIHTC funding.

svi_divisional_county_lihtc_sf %>% filter(State == "AZ") %>% select(State, County, flag_count10, post10_lihtc_dollars_formatted) %>% arrange(desc(flag_count10)) %>% head()

##   State          County flag_count10 post10_lihtc_dollars_formatted
## 1    AZ Maricopa County          487                    $13,115,292
## 2    AZ     Pima County          136                     $3,557,261
## 3    AZ     Gila County           21                       $547,218
## 4    AZ     Yuma County           21                       $864,604

Again, Montana and Colorado received high funding dollars for a low amount of need:

svi_divisional_county_lihtc_sf %>% filter(State %in% c("MT", "CO")) %>%
  arrange(desc(post10_lihtc_project_dollars), flag_count10) %>% select(State, County, flag_count10, post10_lihtc_dollars_formatted) %>% head(10)  

##   State          County flag_count10 post10_lihtc_dollars_formatted
## 1    CO     Mesa County           13                    $15,437,500
## 2    CO   Denver County           76                     $5,226,128
## 3    MT Big Horn County           17                     $2,849,000
## 4    CO  Larimer County           21                     $2,609,648
## 5    CO  El Paso County           20                     $1,011,891

#Save Data Sets

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")))

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