DATA 205 Capstone: Impact of Community Design on Life Outcomes

Introduction: The places we call home are more than just buildings and streets. Community design, the intentional (and sometimes unintentional) structuring of our environments plays a profound role in shaping our life outcomes. THis extends far beyond aesthetics, encompassing factors like demographics, infrastructure age, and even internet accessibility.

This project aims to explore the relationship between two aspects of community design: energy burden and internet access and how they impact life outcome factors like: depression rates, mental health, english proficiency, and employment opportunities. These are all cornerstones of success, and soon the question arises: are individuals with limited internet access and a high energy burden disproportionately burdened by these challenges?

The motivation behind this investigation is equity. By understanding how community design impacts people, we can work to create more balanced environments and develop solutions that help everyone.

Load Libraries

library(ggridges)
library(tidyverse)
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.2     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.2     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(lubridate)
library(corrplot)
corrplot 0.92 loaded

Set working directory and load datasets

setwd("/Users/blossomanyanwu/Documents/Data 205 Project")
english<-read_csv("englishpercent.csv")
New names:
Rows: 1475 Columns: 8
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(3): State, Census Tract, Value dbl (3): StateFIPS, CensusTract, Year lgl (2):
Data Comment, ...8
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...8`
energyburden<-read_csv("percentenergyburden.csv")
New names:
Rows: 1406 Columns: 8
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(3): State, Census Tract, Value dbl (3): StateFIPS, CensusTract, Year lgl (2):
Data Comment, ...8
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...8`
internetlack<-read_csv("percentnointernetaccess.csv")
New names:
Rows: 1475 Columns: 9
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(3): State, Census Tract, Value dbl (4): StateFIPS, CensusTract, Start Year,
End Year lgl (2): Data Comment, ...9
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...9`
depressionrates<-read_csv("cruderatedepression.csv")
New names:
Rows: 1406 Columns: 11
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(6): State, Census Tract, Value, 95% Confidence Interval, Confidence Int... dbl
(3): StateFIPS, CensusTract, Year lgl (2): Data Comment, ...11
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...11`
wifi<-read_csv("mocowifi.csv")
Rows: 178 Columns: 5
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): Agency, Department, Name, Address, Location

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
mentalhealthdays<-read_csv("crudebadmentalhealth.csv")
New names:
Rows: 1406 Columns: 11
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(6): State, Census Tract, Value, 95% Confidence Interval, Confidence Int... dbl
(3): StateFIPS, CensusTract, Year lgl (2): Data Comment, ...11
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...11`
unemployment<-read_csv("16oroldernoemployment.csv")
New names:
Rows: 1475 Columns: 8
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(3): State, Census Tract, Value dbl (3): StateFIPS, CensusTract, Year lgl (2):
Data Comment, ...8
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...8`

General Cleaning

unemployment <- unemployment[, !(names(unemployment) %in% "Data Comment")]
unemployment <- unemployment[, !(names(unemployment) %in% "...8")] 

depressionrates <- depressionrates[, !(names(depressionrates) %in% "Data Comment")]
depressionrates <- depressionrates[, !(names(depressionrates) %in% "...11")] 

english <- english[, !(names(english) %in% "Data Comment")]
english <- english[, !(names(english) %in% "...8")] 

internetlack <- internetlack[, !(names(internetlack) %in% "Data Comment")]
internetlack <- internetlack[, !(names(internetlack) %in% "...9")] 

mentalhealthdays <- mentalhealthdays[, !(names(mentalhealthdays) %in% "Data Comment")]
mentalhealthdays <- mentalhealthdays[, !(names(mentalhealthdays) %in% "...11")] 


energyburden <- energyburden[, !(names(energyburden) %in% "Data Comment")]
energyburden <- energyburden[, !(names(energyburden) %in% "...8")] 
# Add Proper Year To Data
# Explanation: When data was querried it was collected from a range 2018 to 2020. However for the sake of the analysis all other data sets querried were from the year 2020. I believe this does not negatively impact the integrity of the data. 
energyburden <- energyburden %>%
  mutate(Year = 2020)  # Add Year Column
internetlack <- internetlack %>%
  mutate(Year = 2020)  # Add Year Column
# Change Column Names and Merge Data Columns (Currently as querried from CDC columns are labled 'ValueX' or 'ValueY')

depressionrates <- rename(depressionrates, depressrate = Value)
energyburden <- rename(energyburden, energyburdenrate = Value) 
english <- rename(english, englishrates = Value)
# Percent of adults who report not speaking English Good
internetlack <- rename(internetlack, internetlackrate = Value)
# Percent of census tract where there is no internet in home
mentalhealthdays <- rename(mentalhealthdays, badmental = Value)
# Percent of people in area reporting over 7 bad mental health days
unemployment <- rename(unemployment, percentunemployed = Value)
# Percent of people over 18 reported unemployed/Percent unemployment

Column Editing Continued

# Chunk Explanation: The CDC Quierried Data has a column for 'Data Comments' and columns titled '...8', '...9', '...11' and so on. These columns are empty in all of the data I have querried and for the sake of merging the 6 data sets removing them makes the process easier. 
internetlack <- select(internetlack, State, StateFIPS, CensusTract, `Census Tract`, internetlackrate, Year)

# Chunk Explanation: This code removes the confidence interval data from the depressionrates and the mentalhealthdays data frames. This data was provided to the CDC through surveys and the confidence intervals shows how confident they are in applying it to a substantial population. The condfidence intervals for this data is relatively high so I felt comfortable using this data without analyzing that part. 

mentalhealthdays <- select(mentalhealthdays, State, StateFIPS, CensusTract, `Census Tract`, badmental, Year)
depressionrates <- select(depressionrates, State, StateFIPS, CensusTract, `Census Tract`, depressrate, Year)

Data Set Merging

# Chunk Explanation: Here I will merge all 6 cleaned data sets so that EDA can be started
data_list <- list(depressionrates, energyburden, english, internetlack, mentalhealthdays, unemployment)

# Merge all datasets sequentially based on "id" (all.x = TRUE for keeping all rows)
merged_data <- reduce(data_list, function(x, y) merge(x, y, by = c("State", "CensusTract", "Census Tract", "Year", "StateFIPS"), all.x = TRUE))

# View the final merged data frame
print(merged_data)
        State CensusTract                             Census Tract Year
1    Maryland 24001000100        Allegany County, MD - 24001000100 2020
2    Maryland 24001000200        Allegany County, MD - 24001000200 2020
3    Maryland 24001000300        Allegany County, MD - 24001000300 2020
4    Maryland 24001000400        Allegany County, MD - 24001000400 2020
5    Maryland 24001000500        Allegany County, MD - 24001000500 2020
6    Maryland 24001000600        Allegany County, MD - 24001000600 2020
7    Maryland 24001000700        Allegany County, MD - 24001000700 2020
8    Maryland 24001000800        Allegany County, MD - 24001000800 2020
9    Maryland 24001001000        Allegany County, MD - 24001001000 2020
10   Maryland 24001001100        Allegany County, MD - 24001001100 2020
11   Maryland 24001001200        Allegany County, MD - 24001001200 2020
12   Maryland 24001001300        Allegany County, MD - 24001001300 2020
13   Maryland 24001001401        Allegany County, MD - 24001001401 2020
14   Maryland 24001001402        Allegany County, MD - 24001001402 2020
15   Maryland 24001001502        Allegany County, MD - 24001001502 2020
16   Maryland 24001001503        Allegany County, MD - 24001001503 2020
17   Maryland 24001001600        Allegany County, MD - 24001001600 2020
18   Maryland 24001001700        Allegany County, MD - 24001001700 2020
19   Maryland 24001001800        Allegany County, MD - 24001001800 2020
20   Maryland 24001001900        Allegany County, MD - 24001001900 2020
21   Maryland 24001002000        Allegany County, MD - 24001002000 2020
22   Maryland 24001002100        Allegany County, MD - 24001002100 2020
23   Maryland 24001002200        Allegany County, MD - 24001002200 2020
24   Maryland 24003701101    Anne Arundel County, MD - 24003701101 2020
25   Maryland 24003701102    Anne Arundel County, MD - 24003701102 2020
26   Maryland 24003701200    Anne Arundel County, MD - 24003701200 2020
27   Maryland 24003701300    Anne Arundel County, MD - 24003701300 2020
28   Maryland 24003701400    Anne Arundel County, MD - 24003701400 2020
29   Maryland 24003702100    Anne Arundel County, MD - 24003702100 2020
30   Maryland 24003702204    Anne Arundel County, MD - 24003702204 2020
31   Maryland 24003702205    Anne Arundel County, MD - 24003702205 2020
32   Maryland 24003702206    Anne Arundel County, MD - 24003702206 2020
33   Maryland 24003702208    Anne Arundel County, MD - 24003702208 2020
34   Maryland 24003702209    Anne Arundel County, MD - 24003702209 2020
35   Maryland 24003702300    Anne Arundel County, MD - 24003702300 2020
36   Maryland 24003702402    Anne Arundel County, MD - 24003702402 2020
37   Maryland 24003702500    Anne Arundel County, MD - 24003702500 2020
38   Maryland 24003702601    Anne Arundel County, MD - 24003702601 2020
39   Maryland 24003702602    Anne Arundel County, MD - 24003702602 2020
40   Maryland 24003702701    Anne Arundel County, MD - 24003702701 2020
41   Maryland 24003702702    Anne Arundel County, MD - 24003702702 2020
42   Maryland 24003706101    Anne Arundel County, MD - 24003706101 2020
43   Maryland 24003706301    Anne Arundel County, MD - 24003706301 2020
44   Maryland 24003706302    Anne Arundel County, MD - 24003706302 2020
45   Maryland 24003706401    Anne Arundel County, MD - 24003706401 2020
46   Maryland 24003706402    Anne Arundel County, MD - 24003706402 2020
47   Maryland 24003706500    Anne Arundel County, MD - 24003706500 2020
48   Maryland 24003706600    Anne Arundel County, MD - 24003706600 2020
49   Maryland 24003706700    Anne Arundel County, MD - 24003706700 2020
50   Maryland 24003707001    Anne Arundel County, MD - 24003707001 2020
51   Maryland 24003707002    Anne Arundel County, MD - 24003707002 2020
52   Maryland 24003708001    Anne Arundel County, MD - 24003708001 2020
53   Maryland 24003708004    Anne Arundel County, MD - 24003708004 2020
54   Maryland 24003730100    Anne Arundel County, MD - 24003730100 2020
55   Maryland 24003730203    Anne Arundel County, MD - 24003730203 2020
56   Maryland 24003730204    Anne Arundel County, MD - 24003730204 2020
57   Maryland 24003730300    Anne Arundel County, MD - 24003730300 2020
58   Maryland 24003730401    Anne Arundel County, MD - 24003730401 2020
59   Maryland 24003730402    Anne Arundel County, MD - 24003730402 2020
60   Maryland 24003730502    Anne Arundel County, MD - 24003730502 2020
61   Maryland 24003730504    Anne Arundel County, MD - 24003730504 2020
62   Maryland 24003730505    Anne Arundel County, MD - 24003730505 2020
63   Maryland 24003730506    Anne Arundel County, MD - 24003730506 2020
64   Maryland 24003730601    Anne Arundel County, MD - 24003730601 2020
65   Maryland 24003730603    Anne Arundel County, MD - 24003730603 2020
66   Maryland 24003730604    Anne Arundel County, MD - 24003730604 2020
67   Maryland 24003730700    Anne Arundel County, MD - 24003730700 2020
68   Maryland 24003730800    Anne Arundel County, MD - 24003730800 2020
69   Maryland 24003730901    Anne Arundel County, MD - 24003730901 2020
70   Maryland 24003730902    Anne Arundel County, MD - 24003730902 2020
71   Maryland 24003731002    Anne Arundel County, MD - 24003731002 2020
72   Maryland 24003731003    Anne Arundel County, MD - 24003731003 2020
73   Maryland 24003731004    Anne Arundel County, MD - 24003731004 2020
74   Maryland 24003731102    Anne Arundel County, MD - 24003731102 2020
75   Maryland 24003731103    Anne Arundel County, MD - 24003731103 2020
76   Maryland 24003731104    Anne Arundel County, MD - 24003731104 2020
77   Maryland 24003731105    Anne Arundel County, MD - 24003731105 2020
78   Maryland 24003731201    Anne Arundel County, MD - 24003731201 2020
79   Maryland 24003731202    Anne Arundel County, MD - 24003731202 2020
80   Maryland 24003731203    Anne Arundel County, MD - 24003731203 2020
81   Maryland 24003731204    Anne Arundel County, MD - 24003731204 2020
82   Maryland 24003731303    Anne Arundel County, MD - 24003731303 2020
83   Maryland 24003731306    Anne Arundel County, MD - 24003731306 2020
84   Maryland 24003731307    Anne Arundel County, MD - 24003731307 2020
85   Maryland 24003731308    Anne Arundel County, MD - 24003731308 2020
86   Maryland 24003731309    Anne Arundel County, MD - 24003731309 2020
87   Maryland 24003731310    Anne Arundel County, MD - 24003731310 2020
88   Maryland 24003731311    Anne Arundel County, MD - 24003731311 2020
89   Maryland 24003740102    Anne Arundel County, MD - 24003740102 2020
90   Maryland 24003740103    Anne Arundel County, MD - 24003740103 2020
91   Maryland 24003740104    Anne Arundel County, MD - 24003740104 2020
92   Maryland 24003740105    Anne Arundel County, MD - 24003740105 2020
93   Maryland 24003740201    Anne Arundel County, MD - 24003740201 2020
94   Maryland 24003740203    Anne Arundel County, MD - 24003740203 2020
95   Maryland 24003740303    Anne Arundel County, MD - 24003740303 2020
96   Maryland 24003740304    Anne Arundel County, MD - 24003740304 2020
97   Maryland 24003740305    Anne Arundel County, MD - 24003740305 2020
98   Maryland 24003740400    Anne Arundel County, MD - 24003740400 2020
99   Maryland 24003740500    Anne Arundel County, MD - 24003740500 2020
100  Maryland 24003740601    Anne Arundel County, MD - 24003740601 2020
101  Maryland 24003740602    Anne Arundel County, MD - 24003740602 2020
102  Maryland 24003740603    Anne Arundel County, MD - 24003740603 2020
103  Maryland 24003740701    Anne Arundel County, MD - 24003740701 2020
104  Maryland 24003740702    Anne Arundel County, MD - 24003740702 2020
105  Maryland 24003740800    Anne Arundel County, MD - 24003740800 2020
106  Maryland 24003740900    Anne Arundel County, MD - 24003740900 2020
107  Maryland 24003741000    Anne Arundel County, MD - 24003741000 2020
108  Maryland 24003750101    Anne Arundel County, MD - 24003750101 2020
109  Maryland 24003750102    Anne Arundel County, MD - 24003750102 2020
110  Maryland 24003750201    Anne Arundel County, MD - 24003750201 2020
111  Maryland 24003750202    Anne Arundel County, MD - 24003750202 2020
112  Maryland 24003750203    Anne Arundel County, MD - 24003750203 2020
113  Maryland 24003750300    Anne Arundel County, MD - 24003750300 2020
114  Maryland 24003750400    Anne Arundel County, MD - 24003750400 2020
115  Maryland 24003750801    Anne Arundel County, MD - 24003750801 2020
116  Maryland 24003750803    Anne Arundel County, MD - 24003750803 2020
117  Maryland 24003750804    Anne Arundel County, MD - 24003750804 2020
118  Maryland 24003750900    Anne Arundel County, MD - 24003750900 2020
119  Maryland 24003751000    Anne Arundel County, MD - 24003751000 2020
120  Maryland 24003751102    Anne Arundel County, MD - 24003751102 2020
121  Maryland 24003751103    Anne Arundel County, MD - 24003751103 2020
122  Maryland 24003751200    Anne Arundel County, MD - 24003751200 2020
123  Maryland 24003751400    Anne Arundel County, MD - 24003751400 2020
124  Maryland 24003751500    Anne Arundel County, MD - 24003751500 2020
125  Maryland 24003751600    Anne Arundel County, MD - 24003751600 2020
126  Maryland 24003751700    Anne Arundel County, MD - 24003751700 2020
127  Maryland 24003980000    Anne Arundel County, MD - 24003980000 2020
128  Maryland 24003990000    Anne Arundel County, MD - 24003990000 2020
129  Maryland 24005400100       Baltimore County, MD - 24005400100 2020
130  Maryland 24005400200       Baltimore County, MD - 24005400200 2020
131  Maryland 24005400400       Baltimore County, MD - 24005400400 2020
132  Maryland 24005400500       Baltimore County, MD - 24005400500 2020
133  Maryland 24005400600       Baltimore County, MD - 24005400600 2020
134  Maryland 24005400701       Baltimore County, MD - 24005400701 2020
135  Maryland 24005400702       Baltimore County, MD - 24005400702 2020
136  Maryland 24005400800       Baltimore County, MD - 24005400800 2020
137  Maryland 24005400900       Baltimore County, MD - 24005400900 2020
138  Maryland 24005401000       Baltimore County, MD - 24005401000 2020
139  Maryland 24005401101       Baltimore County, MD - 24005401101 2020
140  Maryland 24005401102       Baltimore County, MD - 24005401102 2020
141  Maryland 24005401200       Baltimore County, MD - 24005401200 2020
142  Maryland 24005401301       Baltimore County, MD - 24005401301 2020
143  Maryland 24005401302       Baltimore County, MD - 24005401302 2020
144  Maryland 24005401400       Baltimore County, MD - 24005401400 2020
145  Maryland 24005401503       Baltimore County, MD - 24005401503 2020
146  Maryland 24005401504       Baltimore County, MD - 24005401504 2020
147  Maryland 24005401505       Baltimore County, MD - 24005401505 2020
148  Maryland 24005401506       Baltimore County, MD - 24005401506 2020
149  Maryland 24005401507       Baltimore County, MD - 24005401507 2020
150  Maryland 24005402201       Baltimore County, MD - 24005402201 2020
151  Maryland 24005402202       Baltimore County, MD - 24005402202 2020
152  Maryland 24005402302       Baltimore County, MD - 24005402302 2020
153  Maryland 24005402303       Baltimore County, MD - 24005402303 2020
154  Maryland 24005402304       Baltimore County, MD - 24005402304 2020
155  Maryland 24005402305       Baltimore County, MD - 24005402305 2020
156  Maryland 24005402306       Baltimore County, MD - 24005402306 2020
157  Maryland 24005402307       Baltimore County, MD - 24005402307 2020
158  Maryland 24005402403       Baltimore County, MD - 24005402403 2020
159  Maryland 24005402404       Baltimore County, MD - 24005402404 2020
160  Maryland 24005402405       Baltimore County, MD - 24005402405 2020
161  Maryland 24005402406       Baltimore County, MD - 24005402406 2020
162  Maryland 24005402407       Baltimore County, MD - 24005402407 2020
163  Maryland 24005402503       Baltimore County, MD - 24005402503 2020
164  Maryland 24005402504       Baltimore County, MD - 24005402504 2020
165  Maryland 24005402505       Baltimore County, MD - 24005402505 2020
166  Maryland 24005402506       Baltimore County, MD - 24005402506 2020
167  Maryland 24005402509       Baltimore County, MD - 24005402509 2020
168  Maryland 24005402602       Baltimore County, MD - 24005402602 2020
169  Maryland 24005402603       Baltimore County, MD - 24005402603 2020
170  Maryland 24005402604       Baltimore County, MD - 24005402604 2020
171  Maryland 24005403100       Baltimore County, MD - 24005403100 2020
172  Maryland 24005403201       Baltimore County, MD - 24005403201 2020
173  Maryland 24005403202       Baltimore County, MD - 24005403202 2020
174  Maryland 24005403300       Baltimore County, MD - 24005403300 2020
175  Maryland 24005403401       Baltimore County, MD - 24005403401 2020
176  Maryland 24005403402       Baltimore County, MD - 24005403402 2020
177  Maryland 24005403500       Baltimore County, MD - 24005403500 2020
178  Maryland 24005403601       Baltimore County, MD - 24005403601 2020
179  Maryland 24005403602       Baltimore County, MD - 24005403602 2020
180  Maryland 24005403701       Baltimore County, MD - 24005403701 2020
181  Maryland 24005403702       Baltimore County, MD - 24005403702 2020
182  Maryland 24005403801       Baltimore County, MD - 24005403801 2020
183  Maryland 24005403802       Baltimore County, MD - 24005403802 2020
184  Maryland 24005403803       Baltimore County, MD - 24005403803 2020
185  Maryland 24005404101       Baltimore County, MD - 24005404101 2020
186  Maryland 24005404102       Baltimore County, MD - 24005404102 2020
187  Maryland 24005404201       Baltimore County, MD - 24005404201 2020
188  Maryland 24005404202       Baltimore County, MD - 24005404202 2020
189  Maryland 24005404402       Baltimore County, MD - 24005404402 2020
190  Maryland 24005404403       Baltimore County, MD - 24005404403 2020
191  Maryland 24005404404       Baltimore County, MD - 24005404404 2020
192  Maryland 24005404501       Baltimore County, MD - 24005404501 2020
193  Maryland 24005404502       Baltimore County, MD - 24005404502 2020
194  Maryland 24005404600       Baltimore County, MD - 24005404600 2020
195  Maryland 24005404800       Baltimore County, MD - 24005404800 2020
196  Maryland 24005404900       Baltimore County, MD - 24005404900 2020
197  Maryland 24005405000       Baltimore County, MD - 24005405000 2020
198  Maryland 24005406000       Baltimore County, MD - 24005406000 2020
199  Maryland 24005407001       Baltimore County, MD - 24005407001 2020
200  Maryland 24005407002       Baltimore County, MD - 24005407002 2020
201  Maryland 24005408100       Baltimore County, MD - 24005408100 2020
202  Maryland 24005408200       Baltimore County, MD - 24005408200 2020
203  Maryland 24005408302       Baltimore County, MD - 24005408302 2020
204  Maryland 24005408303       Baltimore County, MD - 24005408303 2020
205  Maryland 24005408304       Baltimore County, MD - 24005408304 2020
206  Maryland 24005408400       Baltimore County, MD - 24005408400 2020
207  Maryland 24005408502       Baltimore County, MD - 24005408502 2020
208  Maryland 24005408503       Baltimore County, MD - 24005408503 2020
209  Maryland 24005408505       Baltimore County, MD - 24005408505 2020
210  Maryland 24005408506       Baltimore County, MD - 24005408506 2020
211  Maryland 24005408507       Baltimore County, MD - 24005408507 2020
212  Maryland 24005408601       Baltimore County, MD - 24005408601 2020
213  Maryland 24005408602       Baltimore County, MD - 24005408602 2020
214  Maryland 24005408702       Baltimore County, MD - 24005408702 2020
215  Maryland 24005408703       Baltimore County, MD - 24005408703 2020
216  Maryland 24005408704       Baltimore County, MD - 24005408704 2020
217  Maryland 24005408800       Baltimore County, MD - 24005408800 2020
218  Maryland 24005408900       Baltimore County, MD - 24005408900 2020
219  Maryland 24005410100       Baltimore County, MD - 24005410100 2020
220  Maryland 24005410200       Baltimore County, MD - 24005410200 2020
221  Maryland 24005411101       Baltimore County, MD - 24005411101 2020
222  Maryland 24005411102       Baltimore County, MD - 24005411102 2020
223  Maryland 24005411201       Baltimore County, MD - 24005411201 2020
224  Maryland 24005411202       Baltimore County, MD - 24005411202 2020
225  Maryland 24005411302       Baltimore County, MD - 24005411302 2020
226  Maryland 24005411303       Baltimore County, MD - 24005411303 2020
227  Maryland 24005411306       Baltimore County, MD - 24005411306 2020
228  Maryland 24005411307       Baltimore County, MD - 24005411307 2020
229  Maryland 24005411308       Baltimore County, MD - 24005411308 2020
230  Maryland 24005411309       Baltimore County, MD - 24005411309 2020
231  Maryland 24005411404       Baltimore County, MD - 24005411404 2020
232  Maryland 24005411406       Baltimore County, MD - 24005411406 2020
233  Maryland 24005411407       Baltimore County, MD - 24005411407 2020
234  Maryland 24005411408       Baltimore County, MD - 24005411408 2020
235  Maryland 24005411409       Baltimore County, MD - 24005411409 2020
236  Maryland 24005411410       Baltimore County, MD - 24005411410 2020
237  Maryland 24005420100       Baltimore County, MD - 24005420100 2020
238  Maryland 24005420200       Baltimore County, MD - 24005420200 2020
239  Maryland 24005420301       Baltimore County, MD - 24005420301 2020
240  Maryland 24005420302       Baltimore County, MD - 24005420302 2020
241  Maryland 24005420303       Baltimore County, MD - 24005420303 2020
242  Maryland 24005420401       Baltimore County, MD - 24005420401 2020
243  Maryland 24005420402       Baltimore County, MD - 24005420402 2020
244  Maryland 24005420500       Baltimore County, MD - 24005420500 2020
245  Maryland 24005420600       Baltimore County, MD - 24005420600 2020
246  Maryland 24005420701       Baltimore County, MD - 24005420701 2020
247  Maryland 24005420702       Baltimore County, MD - 24005420702 2020
248  Maryland 24005420800       Baltimore County, MD - 24005420800 2020
249  Maryland 24005420900       Baltimore County, MD - 24005420900 2020
250  Maryland 24005421000       Baltimore County, MD - 24005421000 2020
251  Maryland 24005421101       Baltimore County, MD - 24005421101 2020
252  Maryland 24005421102       Baltimore County, MD - 24005421102 2020
253  Maryland 24005421200       Baltimore County, MD - 24005421200 2020
254  Maryland 24005421300       Baltimore County, MD - 24005421300 2020
255  Maryland 24005430101       Baltimore County, MD - 24005430101 2020
256  Maryland 24005430104       Baltimore County, MD - 24005430104 2020
257  Maryland 24005430200       Baltimore County, MD - 24005430200 2020
258  Maryland 24005430300       Baltimore County, MD - 24005430300 2020
259  Maryland 24005430400       Baltimore County, MD - 24005430400 2020
260  Maryland 24005430600       Baltimore County, MD - 24005430600 2020
261  Maryland 24005430700       Baltimore County, MD - 24005430700 2020
262  Maryland 24005430800       Baltimore County, MD - 24005430800 2020
263  Maryland 24005430900       Baltimore County, MD - 24005430900 2020
264  Maryland 24005440100       Baltimore County, MD - 24005440100 2020
265  Maryland 24005440200       Baltimore County, MD - 24005440200 2020
266  Maryland 24005440300       Baltimore County, MD - 24005440300 2020
267  Maryland 24005440400       Baltimore County, MD - 24005440400 2020
268  Maryland 24005440500       Baltimore County, MD - 24005440500 2020
269  Maryland 24005440600       Baltimore County, MD - 24005440600 2020
270  Maryland 24005440701       Baltimore County, MD - 24005440701 2020
271  Maryland 24005440702       Baltimore County, MD - 24005440702 2020
272  Maryland 24005440800       Baltimore County, MD - 24005440800 2020
273  Maryland 24005440900       Baltimore County, MD - 24005440900 2020
274  Maryland 24005441000       Baltimore County, MD - 24005441000 2020
275  Maryland 24005441101       Baltimore County, MD - 24005441101 2020
276  Maryland 24005441102       Baltimore County, MD - 24005441102 2020
277  Maryland 24005450100       Baltimore County, MD - 24005450100 2020
278  Maryland 24005450200       Baltimore County, MD - 24005450200 2020
279  Maryland 24005450300       Baltimore County, MD - 24005450300 2020
280  Maryland 24005450400       Baltimore County, MD - 24005450400 2020
281  Maryland 24005450501       Baltimore County, MD - 24005450501 2020
282  Maryland 24005450503       Baltimore County, MD - 24005450503 2020
283  Maryland 24005450504       Baltimore County, MD - 24005450504 2020
284  Maryland 24005450800       Baltimore County, MD - 24005450800 2020
285  Maryland 24005450900       Baltimore County, MD - 24005450900 2020
286  Maryland 24005451000       Baltimore County, MD - 24005451000 2020
287  Maryland 24005451100       Baltimore County, MD - 24005451100 2020
288  Maryland 24005451200       Baltimore County, MD - 24005451200 2020
289  Maryland 24005451300       Baltimore County, MD - 24005451300 2020
290  Maryland 24005451401       Baltimore County, MD - 24005451401 2020
291  Maryland 24005451402       Baltimore County, MD - 24005451402 2020
292  Maryland 24005451500       Baltimore County, MD - 24005451500 2020
293  Maryland 24005451600       Baltimore County, MD - 24005451600 2020
294  Maryland 24005451701       Baltimore County, MD - 24005451701 2020
295  Maryland 24005451702       Baltimore County, MD - 24005451702 2020
296  Maryland 24005451801       Baltimore County, MD - 24005451801 2020
297  Maryland 24005451802       Baltimore County, MD - 24005451802 2020
298  Maryland 24005451803       Baltimore County, MD - 24005451803 2020
299  Maryland 24005451900       Baltimore County, MD - 24005451900 2020
300  Maryland 24005452000       Baltimore County, MD - 24005452000 2020
301  Maryland 24005452100       Baltimore County, MD - 24005452100 2020
302  Maryland 24005452300       Baltimore County, MD - 24005452300 2020
303  Maryland 24005452400       Baltimore County, MD - 24005452400 2020
304  Maryland 24005452500       Baltimore County, MD - 24005452500 2020
305  Maryland 24005490100       Baltimore County, MD - 24005490100 2020
306  Maryland 24005490200       Baltimore County, MD - 24005490200 2020
307  Maryland 24005490301       Baltimore County, MD - 24005490301 2020
308  Maryland 24005490302       Baltimore County, MD - 24005490302 2020
309  Maryland 24005490400       Baltimore County, MD - 24005490400 2020
310  Maryland 24005490500       Baltimore County, MD - 24005490500 2020
311  Maryland 24005490601       Baltimore County, MD - 24005490601 2020
312  Maryland 24005490602       Baltimore County, MD - 24005490602 2020
313  Maryland 24005490603       Baltimore County, MD - 24005490603 2020
314  Maryland 24005490605       Baltimore County, MD - 24005490605 2020
315  Maryland 24005490701       Baltimore County, MD - 24005490701 2020
316  Maryland 24005490703       Baltimore County, MD - 24005490703 2020
317  Maryland 24005490800       Baltimore County, MD - 24005490800 2020
318  Maryland 24005490900       Baltimore County, MD - 24005490900 2020
319  Maryland 24005491000       Baltimore County, MD - 24005491000 2020
320  Maryland 24005491100       Baltimore County, MD - 24005491100 2020
321  Maryland 24005491201       Baltimore County, MD - 24005491201 2020
322  Maryland 24005491202       Baltimore County, MD - 24005491202 2020
323  Maryland 24005491300       Baltimore County, MD - 24005491300 2020
324  Maryland 24005491401       Baltimore County, MD - 24005491401 2020
325  Maryland 24005491402       Baltimore County, MD - 24005491402 2020
326  Maryland 24005491500       Baltimore County, MD - 24005491500 2020
327  Maryland 24005491600       Baltimore County, MD - 24005491600 2020
328  Maryland 24005491701       Baltimore County, MD - 24005491701 2020
329  Maryland 24005491900       Baltimore County, MD - 24005491900 2020
330  Maryland 24005492001       Baltimore County, MD - 24005492001 2020
331  Maryland 24005492002       Baltimore County, MD - 24005492002 2020
332  Maryland 24005492101       Baltimore County, MD - 24005492101 2020
333  Maryland 24005492102       Baltimore County, MD - 24005492102 2020
334  Maryland 24005492200       Baltimore County, MD - 24005492200 2020
335  Maryland 24005492300       Baltimore County, MD - 24005492300 2020
336  Maryland 24005492401       Baltimore County, MD - 24005492401 2020
337  Maryland 24005492402       Baltimore County, MD - 24005492402 2020
338  Maryland 24005492500       Baltimore County, MD - 24005492500 2020
339  Maryland 24005492600       Baltimore County, MD - 24005492600 2020
340  Maryland 24005980000       Baltimore County, MD - 24005980000 2020
341  Maryland 24005980100       Baltimore County, MD - 24005980100 2020
342  Maryland 24005980200       Baltimore County, MD - 24005980200 2020
343  Maryland 24009860101         Calvert County, MD - 24009860101 2020
344  Maryland 24009860102         Calvert County, MD - 24009860102 2020
345  Maryland 24009860200         Calvert County, MD - 24009860200 2020
346  Maryland 24009860300         Calvert County, MD - 24009860300 2020
347  Maryland 24009860401         Calvert County, MD - 24009860401 2020
348  Maryland 24009860402         Calvert County, MD - 24009860402 2020
349  Maryland 24009860501         Calvert County, MD - 24009860501 2020
350  Maryland 24009860502         Calvert County, MD - 24009860502 2020
351  Maryland 24009860600         Calvert County, MD - 24009860600 2020
352  Maryland 24009860701         Calvert County, MD - 24009860701 2020
353  Maryland 24009860702         Calvert County, MD - 24009860702 2020
354  Maryland 24009860703         Calvert County, MD - 24009860703 2020
355  Maryland 24009860801         Calvert County, MD - 24009860801 2020
356  Maryland 24009860802         Calvert County, MD - 24009860802 2020
357  Maryland 24009860900         Calvert County, MD - 24009860900 2020
358  Maryland 24009861001         Calvert County, MD - 24009861001 2020
359  Maryland 24009861003         Calvert County, MD - 24009861003 2020
360  Maryland 24009861004         Calvert County, MD - 24009861004 2020
361  Maryland 24009990100         Calvert County, MD - 24009990100 2020
362  Maryland 24011955000        Caroline County, MD - 24011955000 2020
363  Maryland 24011955100        Caroline County, MD - 24011955100 2020
364  Maryland 24011955201        Caroline County, MD - 24011955201 2020
365  Maryland 24011955202        Caroline County, MD - 24011955202 2020
366  Maryland 24011955301        Caroline County, MD - 24011955301 2020
367  Maryland 24011955302        Caroline County, MD - 24011955302 2020
368  Maryland 24011955400        Caroline County, MD - 24011955400 2020
369  Maryland 24011955500        Caroline County, MD - 24011955500 2020
370  Maryland 24011955600        Caroline County, MD - 24011955600 2020
371  Maryland 24013501001         Carroll County, MD - 24013501001 2020
372  Maryland 24013501002         Carroll County, MD - 24013501002 2020
373  Maryland 24013502000         Carroll County, MD - 24013502000 2020
374  Maryland 24013503000         Carroll County, MD - 24013503000 2020
375  Maryland 24013504100         Carroll County, MD - 24013504100 2020
376  Maryland 24013504201         Carroll County, MD - 24013504201 2020
377  Maryland 24013504202         Carroll County, MD - 24013504202 2020
378  Maryland 24013505101         Carroll County, MD - 24013505101 2020
379  Maryland 24013505102         Carroll County, MD - 24013505102 2020
380  Maryland 24013505203         Carroll County, MD - 24013505203 2020
381  Maryland 24013505205         Carroll County, MD - 24013505205 2020
382  Maryland 24013505206         Carroll County, MD - 24013505206 2020
383  Maryland 24013505207         Carroll County, MD - 24013505207 2020
384  Maryland 24013505208         Carroll County, MD - 24013505208 2020
385  Maryland 24013506101         Carroll County, MD - 24013506101 2020
386  Maryland 24013506102         Carroll County, MD - 24013506102 2020
387  Maryland 24013506200         Carroll County, MD - 24013506200 2020
388  Maryland 24013507500         Carroll County, MD - 24013507500 2020
389  Maryland 24013507601         Carroll County, MD - 24013507601 2020
390  Maryland 24013507602         Carroll County, MD - 24013507602 2020
391  Maryland 24013507702         Carroll County, MD - 24013507702 2020
392  Maryland 24013507703         Carroll County, MD - 24013507703 2020
393  Maryland 24013507704         Carroll County, MD - 24013507704 2020
394  Maryland 24013507801         Carroll County, MD - 24013507801 2020
395  Maryland 24013507802         Carroll County, MD - 24013507802 2020
396  Maryland 24013508101         Carroll County, MD - 24013508101 2020
397  Maryland 24013508102         Carroll County, MD - 24013508102 2020
398  Maryland 24013508200         Carroll County, MD - 24013508200 2020
399  Maryland 24013509001         Carroll County, MD - 24013509001 2020
400  Maryland 24013509002         Carroll County, MD - 24013509002 2020
401  Maryland 24013510000         Carroll County, MD - 24013510000 2020
402  Maryland 24013511000         Carroll County, MD - 24013511000 2020
403  Maryland 24013512000         Carroll County, MD - 24013512000 2020
404  Maryland 24013513001         Carroll County, MD - 24013513001 2020
405  Maryland 24013513002         Carroll County, MD - 24013513002 2020
406  Maryland 24013514100         Carroll County, MD - 24013514100 2020
407  Maryland 24013514201         Carroll County, MD - 24013514201 2020
408  Maryland 24013514202         Carroll County, MD - 24013514202 2020
409  Maryland 24015030100           Cecil County, MD - 24015030100 2020
410  Maryland 24015030200           Cecil County, MD - 24015030200 2020
411  Maryland 24015030400           Cecil County, MD - 24015030400 2020
412  Maryland 24015030501           Cecil County, MD - 24015030501 2020
413  Maryland 24015030503           Cecil County, MD - 24015030503 2020
414  Maryland 24015030505           Cecil County, MD - 24015030505 2020
415  Maryland 24015030506           Cecil County, MD - 24015030506 2020
416  Maryland 24015030601           Cecil County, MD - 24015030601 2020
417  Maryland 24015030602           Cecil County, MD - 24015030602 2020
418  Maryland 24015030700           Cecil County, MD - 24015030700 2020
419  Maryland 24015030903           Cecil County, MD - 24015030903 2020
420  Maryland 24015030904           Cecil County, MD - 24015030904 2020
421  Maryland 24015030905           Cecil County, MD - 24015030905 2020
422  Maryland 24015030906           Cecil County, MD - 24015030906 2020
423  Maryland 24015031201           Cecil County, MD - 24015031201 2020
424  Maryland 24015031202           Cecil County, MD - 24015031202 2020
425  Maryland 24015031301           Cecil County, MD - 24015031301 2020
426  Maryland 24015031302           Cecil County, MD - 24015031302 2020
427  Maryland 24015031400           Cecil County, MD - 24015031400 2020
428  Maryland 24017850101         Charles County, MD - 24017850101 2020
429  Maryland 24017850102         Charles County, MD - 24017850102 2020
430  Maryland 24017850201         Charles County, MD - 24017850201 2020
431  Maryland 24017850202         Charles County, MD - 24017850202 2020
432  Maryland 24017850300         Charles County, MD - 24017850300 2020
433  Maryland 24017850400         Charles County, MD - 24017850400 2020
434  Maryland 24017850500         Charles County, MD - 24017850500 2020
435  Maryland 24017850600         Charles County, MD - 24017850600 2020
436  Maryland 24017850706         Charles County, MD - 24017850706 2020
437  Maryland 24017850708         Charles County, MD - 24017850708 2020
438  Maryland 24017850709         Charles County, MD - 24017850709 2020
439  Maryland 24017850710         Charles County, MD - 24017850710 2020
440  Maryland 24017850711         Charles County, MD - 24017850711 2020
441  Maryland 24017850712         Charles County, MD - 24017850712 2020
442  Maryland 24017850713         Charles County, MD - 24017850713 2020
443  Maryland 24017850801         Charles County, MD - 24017850801 2020
444  Maryland 24017850802         Charles County, MD - 24017850802 2020
445  Maryland 24017850901         Charles County, MD - 24017850901 2020
446  Maryland 24017850902         Charles County, MD - 24017850902 2020
447  Maryland 24017850904         Charles County, MD - 24017850904 2020
448  Maryland 24017850905         Charles County, MD - 24017850905 2020
449  Maryland 24017850906         Charles County, MD - 24017850906 2020
450  Maryland 24017851001         Charles County, MD - 24017851001 2020
451  Maryland 24017851002         Charles County, MD - 24017851002 2020
452  Maryland 24017851100         Charles County, MD - 24017851100 2020
453  Maryland 24017851200         Charles County, MD - 24017851200 2020
454  Maryland 24017851301         Charles County, MD - 24017851301 2020
455  Maryland 24017851302         Charles County, MD - 24017851302 2020
456  Maryland 24017851400         Charles County, MD - 24017851400 2020
457  Maryland 24017851500         Charles County, MD - 24017851500 2020
458  Maryland 24017990000         Charles County, MD - 24017990000 2020
459  Maryland 24019970100      Dorchester County, MD - 24019970100 2020
460  Maryland 24019970200      Dorchester County, MD - 24019970200 2020
461  Maryland 24019970300      Dorchester County, MD - 24019970300 2020
462  Maryland 24019970400      Dorchester County, MD - 24019970400 2020
463  Maryland 24019970500      Dorchester County, MD - 24019970500 2020
464  Maryland 24019970600      Dorchester County, MD - 24019970600 2020
465  Maryland 24019970702      Dorchester County, MD - 24019970702 2020
466  Maryland 24019970804      Dorchester County, MD - 24019970804 2020
467  Maryland 24019970900      Dorchester County, MD - 24019970900 2020
468  Maryland 24019990000      Dorchester County, MD - 24019990000 2020
469  Maryland 24021740200       Frederick County, MD - 24021740200 2020
470  Maryland 24021750100       Frederick County, MD - 24021750100 2020
471  Maryland 24021750200       Frederick County, MD - 24021750200 2020
472  Maryland 24021750300       Frederick County, MD - 24021750300 2020
473  Maryland 24021750503       Frederick County, MD - 24021750503 2020
474  Maryland 24021750504       Frederick County, MD - 24021750504 2020
475  Maryland 24021750505       Frederick County, MD - 24021750505 2020
476  Maryland 24021750506       Frederick County, MD - 24021750506 2020
477  Maryland 24021750600       Frederick County, MD - 24021750600 2020
478  Maryland 24021750701       Frederick County, MD - 24021750701 2020
479  Maryland 24021750702       Frederick County, MD - 24021750702 2020
480  Maryland 24021750801       Frederick County, MD - 24021750801 2020
481  Maryland 24021750802       Frederick County, MD - 24021750802 2020
482  Maryland 24021750803       Frederick County, MD - 24021750803 2020
483  Maryland 24021751001       Frederick County, MD - 24021751001 2020
484  Maryland 24021751002       Frederick County, MD - 24021751002 2020
485  Maryland 24021751003       Frederick County, MD - 24021751003 2020
486  Maryland 24021751004       Frederick County, MD - 24021751004 2020
487  Maryland 24021751201       Frederick County, MD - 24021751201 2020
488  Maryland 24021751202       Frederick County, MD - 24021751202 2020
489  Maryland 24021751203       Frederick County, MD - 24021751203 2020
490  Maryland 24021751301       Frederick County, MD - 24021751301 2020
491  Maryland 24021751302       Frederick County, MD - 24021751302 2020
492  Maryland 24021751600       Frederick County, MD - 24021751600 2020
493  Maryland 24021751701       Frederick County, MD - 24021751701 2020
494  Maryland 24021751702       Frederick County, MD - 24021751702 2020
495  Maryland 24021751801       Frederick County, MD - 24021751801 2020
496  Maryland 24021751802       Frederick County, MD - 24021751802 2020
497  Maryland 24021751901       Frederick County, MD - 24021751901 2020
498  Maryland 24021751902       Frederick County, MD - 24021751902 2020
499  Maryland 24021751903       Frederick County, MD - 24021751903 2020
500  Maryland 24021751904       Frederick County, MD - 24021751904 2020
501  Maryland 24021752001       Frederick County, MD - 24021752001 2020
502  Maryland 24021752101       Frederick County, MD - 24021752101 2020
503  Maryland 24021752102       Frederick County, MD - 24021752102 2020
504  Maryland 24021752201       Frederick County, MD - 24021752201 2020
505  Maryland 24021752202       Frederick County, MD - 24021752202 2020
506  Maryland 24021752204       Frederick County, MD - 24021752204 2020
507  Maryland 24021752301       Frederick County, MD - 24021752301 2020
508  Maryland 24021752302       Frederick County, MD - 24021752302 2020
509  Maryland 24021752303       Frederick County, MD - 24021752303 2020
510  Maryland 24021752501       Frederick County, MD - 24021752501 2020
511  Maryland 24021752502       Frederick County, MD - 24021752502 2020
512  Maryland 24021752601       Frederick County, MD - 24021752601 2020
513  Maryland 24021752602       Frederick County, MD - 24021752602 2020
514  Maryland 24021752603       Frederick County, MD - 24021752603 2020
515  Maryland 24021752801       Frederick County, MD - 24021752801 2020
516  Maryland 24021752802       Frederick County, MD - 24021752802 2020
517  Maryland 24021752900       Frederick County, MD - 24021752900 2020
518  Maryland 24021753001       Frederick County, MD - 24021753001 2020
519  Maryland 24021753002       Frederick County, MD - 24021753002 2020
520  Maryland 24021765100       Frederick County, MD - 24021765100 2020
521  Maryland 24021766800       Frederick County, MD - 24021766800 2020
522  Maryland 24021767500       Frederick County, MD - 24021767500 2020
523  Maryland 24021767600       Frederick County, MD - 24021767600 2020
524  Maryland 24021770700       Frederick County, MD - 24021770700 2020
525  Maryland 24021772200       Frederick County, MD - 24021772200 2020
526  Maryland 24021773500       Frederick County, MD - 24021773500 2020
527  Maryland 24021775302       Frederick County, MD - 24021775302 2020
528  Maryland 24021775400       Frederick County, MD - 24021775400 2020
529  Maryland 24021775600       Frederick County, MD - 24021775600 2020
530  Maryland 24023000100         Garrett County, MD - 24023000100 2020
531  Maryland 24023000200         Garrett County, MD - 24023000200 2020
532  Maryland 24023000300         Garrett County, MD - 24023000300 2020
533  Maryland 24023000400         Garrett County, MD - 24023000400 2020
534  Maryland 24023000500         Garrett County, MD - 24023000500 2020
535  Maryland 24023000600         Garrett County, MD - 24023000600 2020
536  Maryland 24023000700         Garrett County, MD - 24023000700 2020
537  Maryland 24025301102         Harford County, MD - 24025301102 2020
538  Maryland 24025301105         Harford County, MD - 24025301105 2020
539  Maryland 24025301106         Harford County, MD - 24025301106 2020
540  Maryland 24025301107         Harford County, MD - 24025301107 2020
541  Maryland 24025301108         Harford County, MD - 24025301108 2020
542  Maryland 24025301201         Harford County, MD - 24025301201 2020
543  Maryland 24025301202         Harford County, MD - 24025301202 2020
544  Maryland 24025301204         Harford County, MD - 24025301204 2020
545  Maryland 24025301205         Harford County, MD - 24025301205 2020
546  Maryland 24025301301         Harford County, MD - 24025301301 2020
547  Maryland 24025301302         Harford County, MD - 24025301302 2020
548  Maryland 24025301401         Harford County, MD - 24025301401 2020
549  Maryland 24025301402         Harford County, MD - 24025301402 2020
550  Maryland 24025301601         Harford County, MD - 24025301601 2020
551  Maryland 24025301602         Harford County, MD - 24025301602 2020
552  Maryland 24025301702         Harford County, MD - 24025301702 2020
553  Maryland 24025301703         Harford County, MD - 24025301703 2020
554  Maryland 24025301704         Harford County, MD - 24025301704 2020
555  Maryland 24025302100         Harford County, MD - 24025302100 2020
556  Maryland 24025302200         Harford County, MD - 24025302200 2020
557  Maryland 24025302400         Harford County, MD - 24025302400 2020
558  Maryland 24025302801         Harford County, MD - 24025302801 2020
559  Maryland 24025302802         Harford County, MD - 24025302802 2020
560  Maryland 24025302901         Harford County, MD - 24025302901 2020
561  Maryland 24025302902         Harford County, MD - 24025302902 2020
562  Maryland 24025303101         Harford County, MD - 24025303101 2020
563  Maryland 24025303102         Harford County, MD - 24025303102 2020
564  Maryland 24025303201         Harford County, MD - 24025303201 2020
565  Maryland 24025303203         Harford County, MD - 24025303203 2020
566  Maryland 24025303204         Harford County, MD - 24025303204 2020
567  Maryland 24025303205         Harford County, MD - 24025303205 2020
568  Maryland 24025303206         Harford County, MD - 24025303206 2020
569  Maryland 24025303300         Harford County, MD - 24025303300 2020
570  Maryland 24025303400         Harford County, MD - 24025303400 2020
571  Maryland 24025303501         Harford County, MD - 24025303501 2020
572  Maryland 24025303502         Harford County, MD - 24025303502 2020
573  Maryland 24025303602         Harford County, MD - 24025303602 2020
574  Maryland 24025303603         Harford County, MD - 24025303603 2020
575  Maryland 24025303605         Harford County, MD - 24025303605 2020
576  Maryland 24025303606         Harford County, MD - 24025303606 2020
577  Maryland 24025303700         Harford County, MD - 24025303700 2020
578  Maryland 24025303801         Harford County, MD - 24025303801 2020
579  Maryland 24025303802         Harford County, MD - 24025303802 2020
580  Maryland 24025303803         Harford County, MD - 24025303803 2020
581  Maryland 24025303900         Harford County, MD - 24025303900 2020
582  Maryland 24025304101         Harford County, MD - 24025304101 2020
583  Maryland 24025304102         Harford County, MD - 24025304102 2020
584  Maryland 24025304201         Harford County, MD - 24025304201 2020
585  Maryland 24025304202         Harford County, MD - 24025304202 2020
586  Maryland 24025305100         Harford County, MD - 24025305100 2020
587  Maryland 24025305200         Harford County, MD - 24025305200 2020
588  Maryland 24025305300         Harford County, MD - 24025305300 2020
589  Maryland 24025306100         Harford County, MD - 24025306100 2020
590  Maryland 24025306200         Harford County, MD - 24025306200 2020
591  Maryland 24025306300         Harford County, MD - 24025306300 2020
592  Maryland 24025306400         Harford County, MD - 24025306400 2020
593  Maryland 24025306500         Harford County, MD - 24025306500 2020
594  Maryland 24027601103          Howard County, MD - 24027601103 2020
595  Maryland 24027601104          Howard County, MD - 24027601104 2020
596  Maryland 24027601105          Howard County, MD - 24027601105 2020
597  Maryland 24027601107          Howard County, MD - 24027601107 2020
598  Maryland 24027601108          Howard County, MD - 24027601108 2020
599  Maryland 24027601201          Howard County, MD - 24027601201 2020
600  Maryland 24027601203          Howard County, MD - 24027601203 2020
601  Maryland 24027601204          Howard County, MD - 24027601204 2020
602  Maryland 24027602100          Howard County, MD - 24027602100 2020
603  Maryland 24027602201          Howard County, MD - 24027602201 2020
604  Maryland 24027602202          Howard County, MD - 24027602202 2020
605  Maryland 24027602302          Howard County, MD - 24027602302 2020
606  Maryland 24027602303          Howard County, MD - 24027602303 2020
607  Maryland 24027602304          Howard County, MD - 24027602304 2020
608  Maryland 24027602305          Howard County, MD - 24027602305 2020
609  Maryland 24027602306          Howard County, MD - 24027602306 2020
610  Maryland 24027602600          Howard County, MD - 24027602600 2020
611  Maryland 24027602700          Howard County, MD - 24027602700 2020
612  Maryland 24027602800          Howard County, MD - 24027602800 2020
613  Maryland 24027602900          Howard County, MD - 24027602900 2020
614  Maryland 24027603001          Howard County, MD - 24027603001 2020
615  Maryland 24027603003          Howard County, MD - 24027603003 2020
616  Maryland 24027603004          Howard County, MD - 24027603004 2020
617  Maryland 24027604001          Howard County, MD - 24027604001 2020
618  Maryland 24027604002          Howard County, MD - 24027604002 2020
619  Maryland 24027605102          Howard County, MD - 24027605102 2020
620  Maryland 24027605103          Howard County, MD - 24027605103 2020
621  Maryland 24027605104          Howard County, MD - 24027605104 2020
622  Maryland 24027605401          Howard County, MD - 24027605401 2020
623  Maryland 24027605402          Howard County, MD - 24027605402 2020
624  Maryland 24027605502          Howard County, MD - 24027605502 2020
625  Maryland 24027605503          Howard County, MD - 24027605503 2020
626  Maryland 24027605504          Howard County, MD - 24027605504 2020
627  Maryland 24027605505          Howard County, MD - 24027605505 2020
628  Maryland 24027605601          Howard County, MD - 24027605601 2020
629  Maryland 24027605602          Howard County, MD - 24027605602 2020
630  Maryland 24027606601          Howard County, MD - 24027606601 2020
631  Maryland 24027606603          Howard County, MD - 24027606603 2020
632  Maryland 24027606604          Howard County, MD - 24027606604 2020
633  Maryland 24027606606          Howard County, MD - 24027606606 2020
634  Maryland 24027606607          Howard County, MD - 24027606607 2020
635  Maryland 24027606701          Howard County, MD - 24027606701 2020
636  Maryland 24027606704          Howard County, MD - 24027606704 2020
637  Maryland 24027606705          Howard County, MD - 24027606705 2020
638  Maryland 24027606706          Howard County, MD - 24027606706 2020
639  Maryland 24027606707          Howard County, MD - 24027606707 2020
640  Maryland 24027606803          Howard County, MD - 24027606803 2020
641  Maryland 24027606804          Howard County, MD - 24027606804 2020
642  Maryland 24027606805          Howard County, MD - 24027606805 2020
643  Maryland 24027606806          Howard County, MD - 24027606806 2020
644  Maryland 24027606901          Howard County, MD - 24027606901 2020
645  Maryland 24027606904          Howard County, MD - 24027606904 2020
646  Maryland 24027606905          Howard County, MD - 24027606905 2020
647  Maryland 24027606906          Howard County, MD - 24027606906 2020
648  Maryland 24027606907          Howard County, MD - 24027606907 2020
649  Maryland 24029950100            Kent County, MD - 24029950100 2020
650  Maryland 24029950200            Kent County, MD - 24029950200 2020
651  Maryland 24029950300            Kent County, MD - 24029950300 2020
652  Maryland 24029950400            Kent County, MD - 24029950400 2020
653  Maryland 24029950500            Kent County, MD - 24029950500 2020
654  Maryland 24029990000            Kent County, MD - 24029990000 2020
655  Maryland 24031700101      Montgomery County, MD - 24031700101 2020
656  Maryland 24031700103      Montgomery County, MD - 24031700103 2020
657  Maryland 24031700104      Montgomery County, MD - 24031700104 2020
658  Maryland 24031700105      Montgomery County, MD - 24031700105 2020
659  Maryland 24031700204      Montgomery County, MD - 24031700204 2020
660  Maryland 24031700205      Montgomery County, MD - 24031700205 2020
661  Maryland 24031700206      Montgomery County, MD - 24031700206 2020
662  Maryland 24031700207      Montgomery County, MD - 24031700207 2020
663  Maryland 24031700208      Montgomery County, MD - 24031700208 2020
664  Maryland 24031700304      Montgomery County, MD - 24031700304 2020
665  Maryland 24031700306      Montgomery County, MD - 24031700306 2020
666  Maryland 24031700308      Montgomery County, MD - 24031700308 2020
667  Maryland 24031700309      Montgomery County, MD - 24031700309 2020
668  Maryland 24031700310      Montgomery County, MD - 24031700310 2020
669  Maryland 24031700311      Montgomery County, MD - 24031700311 2020
670  Maryland 24031700312      Montgomery County, MD - 24031700312 2020
671  Maryland 24031700400      Montgomery County, MD - 24031700400 2020
672  Maryland 24031700500      Montgomery County, MD - 24031700500 2020
673  Maryland 24031700604      Montgomery County, MD - 24031700604 2020
674  Maryland 24031700606      Montgomery County, MD - 24031700606 2020
675  Maryland 24031700607      Montgomery County, MD - 24031700607 2020
676  Maryland 24031700608      Montgomery County, MD - 24031700608 2020
677  Maryland 24031700610      Montgomery County, MD - 24031700610 2020
678  Maryland 24031700611      Montgomery County, MD - 24031700611 2020
679  Maryland 24031700613      Montgomery County, MD - 24031700613 2020
680  Maryland 24031700614      Montgomery County, MD - 24031700614 2020
681  Maryland 24031700615      Montgomery County, MD - 24031700615 2020
682  Maryland 24031700616      Montgomery County, MD - 24031700616 2020
683  Maryland 24031700704      Montgomery County, MD - 24031700704 2020
684  Maryland 24031700706      Montgomery County, MD - 24031700706 2020
685  Maryland 24031700710      Montgomery County, MD - 24031700710 2020
686  Maryland 24031700711      Montgomery County, MD - 24031700711 2020
687  Maryland 24031700713      Montgomery County, MD - 24031700713 2020
688  Maryland 24031700715      Montgomery County, MD - 24031700715 2020
689  Maryland 24031700716      Montgomery County, MD - 24031700716 2020
690  Maryland 24031700717      Montgomery County, MD - 24031700717 2020
691  Maryland 24031700718      Montgomery County, MD - 24031700718 2020
692  Maryland 24031700719      Montgomery County, MD - 24031700719 2020
693  Maryland 24031700720      Montgomery County, MD - 24031700720 2020
694  Maryland 24031700721      Montgomery County, MD - 24031700721 2020
695  Maryland 24031700722      Montgomery County, MD - 24031700722 2020
696  Maryland 24031700723      Montgomery County, MD - 24031700723 2020
697  Maryland 24031700724      Montgomery County, MD - 24031700724 2020
698  Maryland 24031700810      Montgomery County, MD - 24031700810 2020
699  Maryland 24031700811      Montgomery County, MD - 24031700811 2020
700  Maryland 24031700812      Montgomery County, MD - 24031700812 2020
701  Maryland 24031700813      Montgomery County, MD - 24031700813 2020
702  Maryland 24031700815      Montgomery County, MD - 24031700815 2020
703  Maryland 24031700816      Montgomery County, MD - 24031700816 2020
704  Maryland 24031700817      Montgomery County, MD - 24031700817 2020
705  Maryland 24031700818      Montgomery County, MD - 24031700818 2020
706  Maryland 24031700819      Montgomery County, MD - 24031700819 2020
707  Maryland 24031700820      Montgomery County, MD - 24031700820 2020
708  Maryland 24031700822      Montgomery County, MD - 24031700822 2020
709  Maryland 24031700823      Montgomery County, MD - 24031700823 2020
710  Maryland 24031700824      Montgomery County, MD - 24031700824 2020
711  Maryland 24031700826      Montgomery County, MD - 24031700826 2020
712  Maryland 24031700828      Montgomery County, MD - 24031700828 2020
713  Maryland 24031700829      Montgomery County, MD - 24031700829 2020
714  Maryland 24031700830      Montgomery County, MD - 24031700830 2020
715  Maryland 24031700832      Montgomery County, MD - 24031700832 2020
716  Maryland 24031700833      Montgomery County, MD - 24031700833 2020
717  Maryland 24031700834      Montgomery County, MD - 24031700834 2020
718  Maryland 24031700835      Montgomery County, MD - 24031700835 2020
719  Maryland 24031700901      Montgomery County, MD - 24031700901 2020
720  Maryland 24031700902      Montgomery County, MD - 24031700902 2020
721  Maryland 24031700903      Montgomery County, MD - 24031700903 2020
722  Maryland 24031700904      Montgomery County, MD - 24031700904 2020
723  Maryland 24031700905      Montgomery County, MD - 24031700905 2020
724  Maryland 24031701001      Montgomery County, MD - 24031701001 2020
725  Maryland 24031701002      Montgomery County, MD - 24031701002 2020
726  Maryland 24031701004      Montgomery County, MD - 24031701004 2020
727  Maryland 24031701005      Montgomery County, MD - 24031701005 2020
728  Maryland 24031701006      Montgomery County, MD - 24031701006 2020
729  Maryland 24031701007      Montgomery County, MD - 24031701007 2020
730  Maryland 24031701101      Montgomery County, MD - 24031701101 2020
731  Maryland 24031701102      Montgomery County, MD - 24031701102 2020
732  Maryland 24031701201      Montgomery County, MD - 24031701201 2020
733  Maryland 24031701202      Montgomery County, MD - 24031701202 2020
734  Maryland 24031701205      Montgomery County, MD - 24031701205 2020
735  Maryland 24031701206      Montgomery County, MD - 24031701206 2020
736  Maryland 24031701210      Montgomery County, MD - 24031701210 2020
737  Maryland 24031701211      Montgomery County, MD - 24031701211 2020
738  Maryland 24031701212      Montgomery County, MD - 24031701212 2020
739  Maryland 24031701213      Montgomery County, MD - 24031701213 2020
740  Maryland 24031701214      Montgomery County, MD - 24031701214 2020
741  Maryland 24031701215      Montgomery County, MD - 24031701215 2020
742  Maryland 24031701216      Montgomery County, MD - 24031701216 2020
743  Maryland 24031701218      Montgomery County, MD - 24031701218 2020
744  Maryland 24031701219      Montgomery County, MD - 24031701219 2020
745  Maryland 24031701220      Montgomery County, MD - 24031701220 2020
746  Maryland 24031701221      Montgomery County, MD - 24031701221 2020
747  Maryland 24031701303      Montgomery County, MD - 24031701303 2020
748  Maryland 24031701304      Montgomery County, MD - 24031701304 2020
749  Maryland 24031701306      Montgomery County, MD - 24031701306 2020
750  Maryland 24031701307      Montgomery County, MD - 24031701307 2020
751  Maryland 24031701308      Montgomery County, MD - 24031701308 2020
752  Maryland 24031701312      Montgomery County, MD - 24031701312 2020
753  Maryland 24031701313      Montgomery County, MD - 24031701313 2020
754  Maryland 24031701314      Montgomery County, MD - 24031701314 2020
755  Maryland 24031701315      Montgomery County, MD - 24031701315 2020
756  Maryland 24031701316      Montgomery County, MD - 24031701316 2020
757  Maryland 24031701317      Montgomery County, MD - 24031701317 2020
758  Maryland 24031701407      Montgomery County, MD - 24031701407 2020
759  Maryland 24031701408      Montgomery County, MD - 24031701408 2020
760  Maryland 24031701409      Montgomery County, MD - 24031701409 2020
761  Maryland 24031701410      Montgomery County, MD - 24031701410 2020
762  Maryland 24031701414      Montgomery County, MD - 24031701414 2020
763  Maryland 24031701415      Montgomery County, MD - 24031701415 2020
764  Maryland 24031701417      Montgomery County, MD - 24031701417 2020
765  Maryland 24031701418      Montgomery County, MD - 24031701418 2020
766  Maryland 24031701420      Montgomery County, MD - 24031701420 2020
767  Maryland 24031701421      Montgomery County, MD - 24031701421 2020
768  Maryland 24031701422      Montgomery County, MD - 24031701422 2020
769  Maryland 24031701423      Montgomery County, MD - 24031701423 2020
770  Maryland 24031701503      Montgomery County, MD - 24031701503 2020
771  Maryland 24031701505      Montgomery County, MD - 24031701505 2020
772  Maryland 24031701506      Montgomery County, MD - 24031701506 2020
773  Maryland 24031701507      Montgomery County, MD - 24031701507 2020
774  Maryland 24031701508      Montgomery County, MD - 24031701508 2020
775  Maryland 24031701509      Montgomery County, MD - 24031701509 2020
776  Maryland 24031701601      Montgomery County, MD - 24031701601 2020
777  Maryland 24031701602      Montgomery County, MD - 24031701602 2020
778  Maryland 24031701701      Montgomery County, MD - 24031701701 2020
779  Maryland 24031701702      Montgomery County, MD - 24031701702 2020
780  Maryland 24031701703      Montgomery County, MD - 24031701703 2020
781  Maryland 24031701704      Montgomery County, MD - 24031701704 2020
782  Maryland 24031701800      Montgomery County, MD - 24031701800 2020
783  Maryland 24031701900      Montgomery County, MD - 24031701900 2020
784  Maryland 24031702000      Montgomery County, MD - 24031702000 2020
785  Maryland 24031702101      Montgomery County, MD - 24031702101 2020
786  Maryland 24031702102      Montgomery County, MD - 24031702102 2020
787  Maryland 24031702200      Montgomery County, MD - 24031702200 2020
788  Maryland 24031702301      Montgomery County, MD - 24031702301 2020
789  Maryland 24031702302      Montgomery County, MD - 24031702302 2020
790  Maryland 24031702401      Montgomery County, MD - 24031702401 2020
791  Maryland 24031702402      Montgomery County, MD - 24031702402 2020
792  Maryland 24031702500      Montgomery County, MD - 24031702500 2020
793  Maryland 24031702601      Montgomery County, MD - 24031702601 2020
794  Maryland 24031702602      Montgomery County, MD - 24031702602 2020
795  Maryland 24031702700      Montgomery County, MD - 24031702700 2020
796  Maryland 24031702800      Montgomery County, MD - 24031702800 2020
797  Maryland 24031702900      Montgomery County, MD - 24031702900 2020
798  Maryland 24031703000      Montgomery County, MD - 24031703000 2020
799  Maryland 24031703100      Montgomery County, MD - 24031703100 2020
800  Maryland 24031703201      Montgomery County, MD - 24031703201 2020
801  Maryland 24031703202      Montgomery County, MD - 24031703202 2020
802  Maryland 24031703206      Montgomery County, MD - 24031703206 2020
803  Maryland 24031703207      Montgomery County, MD - 24031703207 2020
804  Maryland 24031703208      Montgomery County, MD - 24031703208 2020
805  Maryland 24031703209      Montgomery County, MD - 24031703209 2020
806  Maryland 24031703210      Montgomery County, MD - 24031703210 2020
807  Maryland 24031703212      Montgomery County, MD - 24031703212 2020
808  Maryland 24031703213      Montgomery County, MD - 24031703213 2020
809  Maryland 24031703214      Montgomery County, MD - 24031703214 2020
810  Maryland 24031703215      Montgomery County, MD - 24031703215 2020
811  Maryland 24031703216      Montgomery County, MD - 24031703216 2020
812  Maryland 24031703218      Montgomery County, MD - 24031703218 2020
813  Maryland 24031703219      Montgomery County, MD - 24031703219 2020
814  Maryland 24031703220      Montgomery County, MD - 24031703220 2020
815  Maryland 24031703221      Montgomery County, MD - 24031703221 2020
816  Maryland 24031703301      Montgomery County, MD - 24031703301 2020
817  Maryland 24031703302      Montgomery County, MD - 24031703302 2020
818  Maryland 24031703401      Montgomery County, MD - 24031703401 2020
819  Maryland 24031703402      Montgomery County, MD - 24031703402 2020
820  Maryland 24031703403      Montgomery County, MD - 24031703403 2020
821  Maryland 24031703404      Montgomery County, MD - 24031703404 2020
822  Maryland 24031703501      Montgomery County, MD - 24031703501 2020
823  Maryland 24031703502      Montgomery County, MD - 24031703502 2020
824  Maryland 24031703601      Montgomery County, MD - 24031703601 2020
825  Maryland 24031703602      Montgomery County, MD - 24031703602 2020
826  Maryland 24031703701      Montgomery County, MD - 24031703701 2020
827  Maryland 24031703702      Montgomery County, MD - 24031703702 2020
828  Maryland 24031703800      Montgomery County, MD - 24031703800 2020
829  Maryland 24031703901      Montgomery County, MD - 24031703901 2020
830  Maryland 24031703902      Montgomery County, MD - 24031703902 2020
831  Maryland 24031704000      Montgomery County, MD - 24031704000 2020
832  Maryland 24031704100      Montgomery County, MD - 24031704100 2020
833  Maryland 24031704200      Montgomery County, MD - 24031704200 2020
834  Maryland 24031704300      Montgomery County, MD - 24031704300 2020
835  Maryland 24031704401      Montgomery County, MD - 24031704401 2020
836  Maryland 24031704403      Montgomery County, MD - 24031704403 2020
837  Maryland 24031704404      Montgomery County, MD - 24031704404 2020
838  Maryland 24031704501      Montgomery County, MD - 24031704501 2020
839  Maryland 24031704502      Montgomery County, MD - 24031704502 2020
840  Maryland 24031704503      Montgomery County, MD - 24031704503 2020
841  Maryland 24031704600      Montgomery County, MD - 24031704600 2020
842  Maryland 24031704700      Montgomery County, MD - 24031704700 2020
843  Maryland 24031704803      Montgomery County, MD - 24031704803 2020
844  Maryland 24031704804      Montgomery County, MD - 24031704804 2020
845  Maryland 24031704805      Montgomery County, MD - 24031704805 2020
846  Maryland 24031704806      Montgomery County, MD - 24031704806 2020
847  Maryland 24031705000      Montgomery County, MD - 24031705000 2020
848  Maryland 24031705100      Montgomery County, MD - 24031705100 2020
849  Maryland 24031705200      Montgomery County, MD - 24031705200 2020
850  Maryland 24031705300      Montgomery County, MD - 24031705300 2020
851  Maryland 24031705400      Montgomery County, MD - 24031705400 2020
852  Maryland 24031705501      Montgomery County, MD - 24031705501 2020
853  Maryland 24031705502      Montgomery County, MD - 24031705502 2020
854  Maryland 24031705601      Montgomery County, MD - 24031705601 2020
855  Maryland 24031705602      Montgomery County, MD - 24031705602 2020
856  Maryland 24031705701      Montgomery County, MD - 24031705701 2020
857  Maryland 24031705702      Montgomery County, MD - 24031705702 2020
858  Maryland 24031705800      Montgomery County, MD - 24031705800 2020
859  Maryland 24031705901      Montgomery County, MD - 24031705901 2020
860  Maryland 24031705902      Montgomery County, MD - 24031705902 2020
861  Maryland 24031705903      Montgomery County, MD - 24031705903 2020
862  Maryland 24031706005      Montgomery County, MD - 24031706005 2020
863  Maryland 24031706007      Montgomery County, MD - 24031706007 2020
864  Maryland 24031706008      Montgomery County, MD - 24031706008 2020
865  Maryland 24031706009      Montgomery County, MD - 24031706009 2020
866  Maryland 24031706010      Montgomery County, MD - 24031706010 2020
867  Maryland 24031706011      Montgomery County, MD - 24031706011 2020
868  Maryland 24031706012      Montgomery County, MD - 24031706012 2020
869  Maryland 24031706013      Montgomery County, MD - 24031706013 2020
870  Maryland 24033800102 Prince George's County, MD - 24033800102 2020
871  Maryland 24033800103 Prince George's County, MD - 24033800103 2020
872  Maryland 24033800105 Prince George's County, MD - 24033800105 2020
873  Maryland 24033800106 Prince George's County, MD - 24033800106 2020
874  Maryland 24033800108 Prince George's County, MD - 24033800108 2020
875  Maryland 24033800109 Prince George's County, MD - 24033800109 2020
876  Maryland 24033800203 Prince George's County, MD - 24033800203 2020
877  Maryland 24033800206 Prince George's County, MD - 24033800206 2020
878  Maryland 24033800208 Prince George's County, MD - 24033800208 2020
879  Maryland 24033800209 Prince George's County, MD - 24033800209 2020
880  Maryland 24033800210 Prince George's County, MD - 24033800210 2020
881  Maryland 24033800211 Prince George's County, MD - 24033800211 2020
882  Maryland 24033800212 Prince George's County, MD - 24033800212 2020
883  Maryland 24033800213 Prince George's County, MD - 24033800213 2020
884  Maryland 24033800214 Prince George's County, MD - 24033800214 2020
885  Maryland 24033800215 Prince George's County, MD - 24033800215 2020
886  Maryland 24033800401 Prince George's County, MD - 24033800401 2020
887  Maryland 24033800402 Prince George's County, MD - 24033800402 2020
888  Maryland 24033800403 Prince George's County, MD - 24033800403 2020
889  Maryland 24033800408 Prince George's County, MD - 24033800408 2020
890  Maryland 24033800409 Prince George's County, MD - 24033800409 2020
891  Maryland 24033800410 Prince George's County, MD - 24033800410 2020
892  Maryland 24033800411 Prince George's County, MD - 24033800411 2020
893  Maryland 24033800412 Prince George's County, MD - 24033800412 2020
894  Maryland 24033800413 Prince George's County, MD - 24033800413 2020
895  Maryland 24033800504 Prince George's County, MD - 24033800504 2020
896  Maryland 24033800505 Prince George's County, MD - 24033800505 2020
897  Maryland 24033800507 Prince George's County, MD - 24033800507 2020
898  Maryland 24033800509 Prince George's County, MD - 24033800509 2020
899  Maryland 24033800511 Prince George's County, MD - 24033800511 2020
900  Maryland 24033800513 Prince George's County, MD - 24033800513 2020
901  Maryland 24033800514 Prince George's County, MD - 24033800514 2020
902  Maryland 24033800515 Prince George's County, MD - 24033800515 2020
903  Maryland 24033800516 Prince George's County, MD - 24033800516 2020
904  Maryland 24033800517 Prince George's County, MD - 24033800517 2020
905  Maryland 24033800518 Prince George's County, MD - 24033800518 2020
906  Maryland 24033800519 Prince George's County, MD - 24033800519 2020
907  Maryland 24033800520 Prince George's County, MD - 24033800520 2020
908  Maryland 24033800601 Prince George's County, MD - 24033800601 2020
909  Maryland 24033800604 Prince George's County, MD - 24033800604 2020
910  Maryland 24033800605 Prince George's County, MD - 24033800605 2020
911  Maryland 24033800606 Prince George's County, MD - 24033800606 2020
912  Maryland 24033800607 Prince George's County, MD - 24033800607 2020
913  Maryland 24033800608 Prince George's County, MD - 24033800608 2020
914  Maryland 24033800701 Prince George's County, MD - 24033800701 2020
915  Maryland 24033800704 Prince George's County, MD - 24033800704 2020
916  Maryland 24033800705 Prince George's County, MD - 24033800705 2020
917  Maryland 24033800706 Prince George's County, MD - 24033800706 2020
918  Maryland 24033800707 Prince George's County, MD - 24033800707 2020
919  Maryland 24033800800 Prince George's County, MD - 24033800800 2020
920  Maryland 24033800900 Prince George's County, MD - 24033800900 2020
921  Maryland 24033801003 Prince George's County, MD - 24033801003 2020
922  Maryland 24033801004 Prince George's County, MD - 24033801004 2020
923  Maryland 24033801005 Prince George's County, MD - 24033801005 2020
924  Maryland 24033801006 Prince George's County, MD - 24033801006 2020
925  Maryland 24033801104 Prince George's County, MD - 24033801104 2020
926  Maryland 24033801207 Prince George's County, MD - 24033801207 2020
927  Maryland 24033801208 Prince George's County, MD - 24033801208 2020
928  Maryland 24033801209 Prince George's County, MD - 24033801209 2020
929  Maryland 24033801210 Prince George's County, MD - 24033801210 2020
930  Maryland 24033801211 Prince George's County, MD - 24033801211 2020
931  Maryland 24033801212 Prince George's County, MD - 24033801212 2020
932  Maryland 24033801213 Prince George's County, MD - 24033801213 2020
933  Maryland 24033801214 Prince George's County, MD - 24033801214 2020
934  Maryland 24033801215 Prince George's County, MD - 24033801215 2020
935  Maryland 24033801216 Prince George's County, MD - 24033801216 2020
936  Maryland 24033801217 Prince George's County, MD - 24033801217 2020
937  Maryland 24033801302 Prince George's County, MD - 24033801302 2020
938  Maryland 24033801305 Prince George's County, MD - 24033801305 2020
939  Maryland 24033801307 Prince George's County, MD - 24033801307 2020
940  Maryland 24033801308 Prince George's County, MD - 24033801308 2020
941  Maryland 24033801309 Prince George's County, MD - 24033801309 2020
942  Maryland 24033801310 Prince George's County, MD - 24033801310 2020
943  Maryland 24033801311 Prince George's County, MD - 24033801311 2020
944  Maryland 24033801312 Prince George's County, MD - 24033801312 2020
945  Maryland 24033801313 Prince George's County, MD - 24033801313 2020
946  Maryland 24033801404 Prince George's County, MD - 24033801404 2020
947  Maryland 24033801405 Prince George's County, MD - 24033801405 2020
948  Maryland 24033801406 Prince George's County, MD - 24033801406 2020
949  Maryland 24033801407 Prince George's County, MD - 24033801407 2020
950  Maryland 24033801408 Prince George's County, MD - 24033801408 2020
951  Maryland 24033801409 Prince George's County, MD - 24033801409 2020
952  Maryland 24033801410 Prince George's County, MD - 24033801410 2020
953  Maryland 24033801411 Prince George's County, MD - 24033801411 2020
954  Maryland 24033801500 Prince George's County, MD - 24033801500 2020
955  Maryland 24033801600 Prince George's County, MD - 24033801600 2020
956  Maryland 24033801701 Prince George's County, MD - 24033801701 2020
957  Maryland 24033801702 Prince George's County, MD - 24033801702 2020
958  Maryland 24033801704 Prince George's County, MD - 24033801704 2020
959  Maryland 24033801706 Prince George's County, MD - 24033801706 2020
960  Maryland 24033801707 Prince George's County, MD - 24033801707 2020
961  Maryland 24033801708 Prince George's County, MD - 24033801708 2020
962  Maryland 24033801801 Prince George's County, MD - 24033801801 2020
963  Maryland 24033801802 Prince George's County, MD - 24033801802 2020
964  Maryland 24033801804 Prince George's County, MD - 24033801804 2020
965  Maryland 24033801805 Prince George's County, MD - 24033801805 2020
966  Maryland 24033801807 Prince George's County, MD - 24033801807 2020
967  Maryland 24033801808 Prince George's County, MD - 24033801808 2020
968  Maryland 24033801901 Prince George's County, MD - 24033801901 2020
969  Maryland 24033801904 Prince George's County, MD - 24033801904 2020
970  Maryland 24033801905 Prince George's County, MD - 24033801905 2020
971  Maryland 24033801906 Prince George's County, MD - 24033801906 2020
972  Maryland 24033801907 Prince George's County, MD - 24033801907 2020
973  Maryland 24033801908 Prince George's County, MD - 24033801908 2020
974  Maryland 24033802001 Prince George's County, MD - 24033802001 2020
975  Maryland 24033802002 Prince George's County, MD - 24033802002 2020
976  Maryland 24033802103 Prince George's County, MD - 24033802103 2020
977  Maryland 24033802104 Prince George's County, MD - 24033802104 2020
978  Maryland 24033802106 Prince George's County, MD - 24033802106 2020
979  Maryland 24033802107 Prince George's County, MD - 24033802107 2020
980  Maryland 24033802201 Prince George's County, MD - 24033802201 2020
981  Maryland 24033802203 Prince George's County, MD - 24033802203 2020
982  Maryland 24033802204 Prince George's County, MD - 24033802204 2020
983  Maryland 24033802301 Prince George's County, MD - 24033802301 2020
984  Maryland 24033802404 Prince George's County, MD - 24033802404 2020
985  Maryland 24033802405 Prince George's County, MD - 24033802405 2020
986  Maryland 24033802406 Prince George's County, MD - 24033802406 2020
987  Maryland 24033802407 Prince George's County, MD - 24033802407 2020
988  Maryland 24033802408 Prince George's County, MD - 24033802408 2020
989  Maryland 24033802501 Prince George's County, MD - 24033802501 2020
990  Maryland 24033802502 Prince George's County, MD - 24033802502 2020
991  Maryland 24033802600 Prince George's County, MD - 24033802600 2020
992  Maryland 24033802700 Prince George's County, MD - 24033802700 2020
993  Maryland 24033802803 Prince George's County, MD - 24033802803 2020
994  Maryland 24033802804 Prince George's County, MD - 24033802804 2020
995  Maryland 24033802805 Prince George's County, MD - 24033802805 2020
996  Maryland 24033802901 Prince George's County, MD - 24033802901 2020
997  Maryland 24033803001 Prince George's County, MD - 24033803001 2020
998  Maryland 24033803002 Prince George's County, MD - 24033803002 2020
999  Maryland 24033803100 Prince George's County, MD - 24033803100 2020
1000 Maryland 24033803200 Prince George's County, MD - 24033803200 2020
1001 Maryland 24033803300 Prince George's County, MD - 24033803300 2020
1002 Maryland 24033803401 Prince George's County, MD - 24033803401 2020
1003 Maryland 24033803402 Prince George's County, MD - 24033803402 2020
1004 Maryland 24033803508 Prince George's County, MD - 24033803508 2020
1005 Maryland 24033803509 Prince George's County, MD - 24033803509 2020
1006 Maryland 24033803512 Prince George's County, MD - 24033803512 2020
1007 Maryland 24033803513 Prince George's County, MD - 24033803513 2020
1008 Maryland 24033803514 Prince George's County, MD - 24033803514 2020
1009 Maryland 24033803516 Prince George's County, MD - 24033803516 2020
1010 Maryland 24033803519 Prince George's County, MD - 24033803519 2020
1011 Maryland 24033803520 Prince George's County, MD - 24033803520 2020
1012 Maryland 24033803521 Prince George's County, MD - 24033803521 2020
1013 Maryland 24033803522 Prince George's County, MD - 24033803522 2020
1014 Maryland 24033803523 Prince George's County, MD - 24033803523 2020
1015 Maryland 24033803524 Prince George's County, MD - 24033803524 2020
1016 Maryland 24033803525 Prince George's County, MD - 24033803525 2020
1017 Maryland 24033803526 Prince George's County, MD - 24033803526 2020
1018 Maryland 24033803527 Prince George's County, MD - 24033803527 2020
1019 Maryland 24033803601 Prince George's County, MD - 24033803601 2020
1020 Maryland 24033803602 Prince George's County, MD - 24033803602 2020
1021 Maryland 24033803605 Prince George's County, MD - 24033803605 2020
1022 Maryland 24033803606 Prince George's County, MD - 24033803606 2020
1023 Maryland 24033803607 Prince George's County, MD - 24033803607 2020
1024 Maryland 24033803608 Prince George's County, MD - 24033803608 2020
1025 Maryland 24033803610 Prince George's County, MD - 24033803610 2020
1026 Maryland 24033803612 Prince George's County, MD - 24033803612 2020
1027 Maryland 24033803613 Prince George's County, MD - 24033803613 2020
1028 Maryland 24033803700 Prince George's County, MD - 24033803700 2020
1029 Maryland 24033803801 Prince George's County, MD - 24033803801 2020
1030 Maryland 24033803803 Prince George's County, MD - 24033803803 2020
1031 Maryland 24033803900 Prince George's County, MD - 24033803900 2020
1032 Maryland 24033804001 Prince George's County, MD - 24033804001 2020
1033 Maryland 24033804002 Prince George's County, MD - 24033804002 2020
1034 Maryland 24033804101 Prince George's County, MD - 24033804101 2020
1035 Maryland 24033804102 Prince George's County, MD - 24033804102 2020
1036 Maryland 24033804200 Prince George's County, MD - 24033804200 2020
1037 Maryland 24033804300 Prince George's County, MD - 24033804300 2020
1038 Maryland 24033804400 Prince George's County, MD - 24033804400 2020
1039 Maryland 24033804600 Prince George's County, MD - 24033804600 2020
1040 Maryland 24033804700 Prince George's County, MD - 24033804700 2020
1041 Maryland 24033804801 Prince George's County, MD - 24033804801 2020
1042 Maryland 24033804802 Prince George's County, MD - 24033804802 2020
1043 Maryland 24033804900 Prince George's County, MD - 24033804900 2020
1044 Maryland 24033805000 Prince George's County, MD - 24033805000 2020
1045 Maryland 24033805101 Prince George's County, MD - 24033805101 2020
1046 Maryland 24033805201 Prince George's County, MD - 24033805201 2020
1047 Maryland 24033805202 Prince George's County, MD - 24033805202 2020
1048 Maryland 24033805500 Prince George's County, MD - 24033805500 2020
1049 Maryland 24033805601 Prince George's County, MD - 24033805601 2020
1050 Maryland 24033805602 Prince George's County, MD - 24033805602 2020
1051 Maryland 24033805700 Prince George's County, MD - 24033805700 2020
1052 Maryland 24033805801 Prince George's County, MD - 24033805801 2020
1053 Maryland 24033805802 Prince George's County, MD - 24033805802 2020
1054 Maryland 24033805904 Prince George's County, MD - 24033805904 2020
1055 Maryland 24033805906 Prince George's County, MD - 24033805906 2020
1056 Maryland 24033805907 Prince George's County, MD - 24033805907 2020
1057 Maryland 24033805908 Prince George's County, MD - 24033805908 2020
1058 Maryland 24033805909 Prince George's County, MD - 24033805909 2020
1059 Maryland 24033806000 Prince George's County, MD - 24033806000 2020
1060 Maryland 24033806100 Prince George's County, MD - 24033806100 2020
1061 Maryland 24033806200 Prince George's County, MD - 24033806200 2020
1062 Maryland 24033806300 Prince George's County, MD - 24033806300 2020
1063 Maryland 24033806400 Prince George's County, MD - 24033806400 2020
1064 Maryland 24033806501 Prince George's County, MD - 24033806501 2020
1065 Maryland 24033806601 Prince George's County, MD - 24033806601 2020
1066 Maryland 24033806602 Prince George's County, MD - 24033806602 2020
1067 Maryland 24033806706 Prince George's County, MD - 24033806706 2020
1068 Maryland 24033806708 Prince George's County, MD - 24033806708 2020
1069 Maryland 24033806710 Prince George's County, MD - 24033806710 2020
1070 Maryland 24033806711 Prince George's County, MD - 24033806711 2020
1071 Maryland 24033806712 Prince George's County, MD - 24033806712 2020
1072 Maryland 24033806713 Prince George's County, MD - 24033806713 2020
1073 Maryland 24033806714 Prince George's County, MD - 24033806714 2020
1074 Maryland 24033806800 Prince George's County, MD - 24033806800 2020
1075 Maryland 24033806900 Prince George's County, MD - 24033806900 2020
1076 Maryland 24033807000 Prince George's County, MD - 24033807000 2020
1077 Maryland 24033807102 Prince George's County, MD - 24033807102 2020
1078 Maryland 24033807200 Prince George's County, MD - 24033807200 2020
1079 Maryland 24033807301 Prince George's County, MD - 24033807301 2020
1080 Maryland 24033807304 Prince George's County, MD - 24033807304 2020
1081 Maryland 24033807305 Prince George's County, MD - 24033807305 2020
1082 Maryland 24033807404 Prince George's County, MD - 24033807404 2020
1083 Maryland 24033807405 Prince George's County, MD - 24033807405 2020
1084 Maryland 24033807407 Prince George's County, MD - 24033807407 2020
1085 Maryland 24033807408 Prince George's County, MD - 24033807408 2020
1086 Maryland 24033807409 Prince George's County, MD - 24033807409 2020
1087 Maryland 24033807410 Prince George's County, MD - 24033807410 2020
1088 Maryland 24035810100    Queen Anne's County, MD - 24035810100 2020
1089 Maryland 24035810200    Queen Anne's County, MD - 24035810200 2020
1090 Maryland 24035810300    Queen Anne's County, MD - 24035810300 2020
1091 Maryland 24035810400    Queen Anne's County, MD - 24035810400 2020
1092 Maryland 24035810500    Queen Anne's County, MD - 24035810500 2020
1093 Maryland 24035810600    Queen Anne's County, MD - 24035810600 2020
1094 Maryland 24035810700    Queen Anne's County, MD - 24035810700 2020
1095 Maryland 24035810800    Queen Anne's County, MD - 24035810800 2020
1096 Maryland 24035810901    Queen Anne's County, MD - 24035810901 2020
1097 Maryland 24035810902    Queen Anne's County, MD - 24035810902 2020
1098 Maryland 24035811000    Queen Anne's County, MD - 24035811000 2020
1099 Maryland 24035990000    Queen Anne's County, MD - 24035990000 2020
1100 Maryland 24035990100    Queen Anne's County, MD - 24035990100 2020
1101 Maryland 24035990200    Queen Anne's County, MD - 24035990200 2020
1102 Maryland 24037875000      St. Mary's County, MD - 24037875000 2020
1103 Maryland 24037875100      St. Mary's County, MD - 24037875100 2020
1104 Maryland 24037875201      St. Mary's County, MD - 24037875201 2020
1105 Maryland 24037875202      St. Mary's County, MD - 24037875202 2020
1106 Maryland 24037875300      St. Mary's County, MD - 24037875300 2020
1107 Maryland 24037875400      St. Mary's County, MD - 24037875400 2020
1108 Maryland 24037875500      St. Mary's County, MD - 24037875500 2020
1109 Maryland 24037875600      St. Mary's County, MD - 24037875600 2020
1110 Maryland 24037875700      St. Mary's County, MD - 24037875700 2020
1111 Maryland 24037875801      St. Mary's County, MD - 24037875801 2020
1112 Maryland 24037875802      St. Mary's County, MD - 24037875802 2020
1113 Maryland 24037875901      St. Mary's County, MD - 24037875901 2020
1114 Maryland 24037875902      St. Mary's County, MD - 24037875902 2020
1115 Maryland 24037876001      St. Mary's County, MD - 24037876001 2020
1116 Maryland 24037876002      St. Mary's County, MD - 24037876002 2020
1117 Maryland 24037876100      St. Mary's County, MD - 24037876100 2020
1118 Maryland 24037876200      St. Mary's County, MD - 24037876200 2020
1119 Maryland 24037990000      St. Mary's County, MD - 24037990000 2020
1120 Maryland 24039930101        Somerset County, MD - 24039930101 2020
1121 Maryland 24039930102        Somerset County, MD - 24039930102 2020
1122 Maryland 24039930200        Somerset County, MD - 24039930200 2020
1123 Maryland 24039930300        Somerset County, MD - 24039930300 2020
1124 Maryland 24039930500        Somerset County, MD - 24039930500 2020
1125 Maryland 24039930600        Somerset County, MD - 24039930600 2020
1126 Maryland 24039980400        Somerset County, MD - 24039980400 2020
1127 Maryland 24039990100        Somerset County, MD - 24039990100 2020
1128 Maryland 24041960100          Talbot County, MD - 24041960100 2020
1129 Maryland 24041960201          Talbot County, MD - 24041960201 2020
1130 Maryland 24041960300          Talbot County, MD - 24041960300 2020
1131 Maryland 24041960400          Talbot County, MD - 24041960400 2020
1132 Maryland 24041960501          Talbot County, MD - 24041960501 2020
1133 Maryland 24041960502          Talbot County, MD - 24041960502 2020
1134 Maryland 24041960600          Talbot County, MD - 24041960600 2020
1135 Maryland 24041960700          Talbot County, MD - 24041960700 2020
1136 Maryland 24041960800          Talbot County, MD - 24041960800 2020
1137 Maryland 24041960900          Talbot County, MD - 24041960900 2020
1138 Maryland 24041990000          Talbot County, MD - 24041990000 2020
1139 Maryland 24043000100      Washington County, MD - 24043000100 2020
1140 Maryland 24043000200      Washington County, MD - 24043000200 2020
1141 Maryland 24043000301      Washington County, MD - 24043000301 2020
1142 Maryland 24043000302      Washington County, MD - 24043000302 2020
1143 Maryland 24043000400      Washington County, MD - 24043000400 2020
1144 Maryland 24043000500      Washington County, MD - 24043000500 2020
1145 Maryland 24043000601      Washington County, MD - 24043000601 2020
1146 Maryland 24043000602      Washington County, MD - 24043000602 2020
1147 Maryland 24043000700      Washington County, MD - 24043000700 2020
1148 Maryland 24043000800      Washington County, MD - 24043000800 2020
1149 Maryland 24043000900      Washington County, MD - 24043000900 2020
1150 Maryland 24043001001      Washington County, MD - 24043001001 2020
1151 Maryland 24043001002      Washington County, MD - 24043001002 2020
1152 Maryland 24043010100      Washington County, MD - 24043010100 2020
1153 Maryland 24043010200      Washington County, MD - 24043010200 2020
1154 Maryland 24043010300      Washington County, MD - 24043010300 2020
1155 Maryland 24043010400      Washington County, MD - 24043010400 2020
1156 Maryland 24043010500      Washington County, MD - 24043010500 2020
1157 Maryland 24043010600      Washington County, MD - 24043010600 2020
1158 Maryland 24043010700      Washington County, MD - 24043010700 2020
1159 Maryland 24043010801      Washington County, MD - 24043010801 2020
1160 Maryland 24043010802      Washington County, MD - 24043010802 2020
1161 Maryland 24043010900      Washington County, MD - 24043010900 2020
1162 Maryland 24043011000      Washington County, MD - 24043011000 2020
1163 Maryland 24043011100      Washington County, MD - 24043011100 2020
1164 Maryland 24043011201      Washington County, MD - 24043011201 2020
1165 Maryland 24043011202      Washington County, MD - 24043011202 2020
1166 Maryland 24043011301      Washington County, MD - 24043011301 2020
1167 Maryland 24043011302      Washington County, MD - 24043011302 2020
1168 Maryland 24043011400      Washington County, MD - 24043011400 2020
1169 Maryland 24043011500      Washington County, MD - 24043011500 2020
1170 Maryland 24043011600      Washington County, MD - 24043011600 2020
1171 Maryland 24045000100        Wicomico County, MD - 24045000100 2020
1172 Maryland 24045000200        Wicomico County, MD - 24045000200 2020
1173 Maryland 24045000300        Wicomico County, MD - 24045000300 2020
1174 Maryland 24045000400        Wicomico County, MD - 24045000400 2020
1175 Maryland 24045000500        Wicomico County, MD - 24045000500 2020
1176 Maryland 24045010101        Wicomico County, MD - 24045010101 2020
1177 Maryland 24045010102        Wicomico County, MD - 24045010102 2020
1178 Maryland 24045010200        Wicomico County, MD - 24045010200 2020
1179 Maryland 24045010300        Wicomico County, MD - 24045010300 2020
1180 Maryland 24045010400        Wicomico County, MD - 24045010400 2020
1181 Maryland 24045010501        Wicomico County, MD - 24045010501 2020
1182 Maryland 24045010502        Wicomico County, MD - 24045010502 2020
1183 Maryland 24045010603        Wicomico County, MD - 24045010603 2020
1184 Maryland 24045010604        Wicomico County, MD - 24045010604 2020
1185 Maryland 24045010605        Wicomico County, MD - 24045010605 2020
1186 Maryland 24045010606        Wicomico County, MD - 24045010606 2020
1187 Maryland 24045010701        Wicomico County, MD - 24045010701 2020
1188 Maryland 24045010702        Wicomico County, MD - 24045010702 2020
1189 Maryland 24045010800        Wicomico County, MD - 24045010800 2020
1190 Maryland 24047950000       Worcester County, MD - 24047950000 2020
1191 Maryland 24047950100       Worcester County, MD - 24047950100 2020
1192 Maryland 24047950300       Worcester County, MD - 24047950300 2020
1193 Maryland 24047950400       Worcester County, MD - 24047950400 2020
1194 Maryland 24047950600       Worcester County, MD - 24047950600 2020
1195 Maryland 24047950700       Worcester County, MD - 24047950700 2020
1196 Maryland 24047950800       Worcester County, MD - 24047950800 2020
1197 Maryland 24047950900       Worcester County, MD - 24047950900 2020
1198 Maryland 24047951000       Worcester County, MD - 24047951000 2020
1199 Maryland 24047951100       Worcester County, MD - 24047951100 2020
1200 Maryland 24047951200       Worcester County, MD - 24047951200 2020
1201 Maryland 24047951300       Worcester County, MD - 24047951300 2020
1202 Maryland 24047951400       Worcester County, MD - 24047951400 2020
1203 Maryland 24047951500       Worcester County, MD - 24047951500 2020
1204 Maryland 24047951700       Worcester County, MD - 24047951700 2020
1205 Maryland 24047980000       Worcester County, MD - 24047980000 2020
1206 Maryland 24047990000       Worcester County, MD - 24047990000 2020
1207 Maryland 24510010100         Baltimore city, MD - 24510010100 2020
1208 Maryland 24510010200         Baltimore city, MD - 24510010200 2020
1209 Maryland 24510010300         Baltimore city, MD - 24510010300 2020
1210 Maryland 24510010400         Baltimore city, MD - 24510010400 2020
1211 Maryland 24510010500         Baltimore city, MD - 24510010500 2020
1212 Maryland 24510020100         Baltimore city, MD - 24510020100 2020
1213 Maryland 24510020200         Baltimore city, MD - 24510020200 2020
1214 Maryland 24510020300         Baltimore city, MD - 24510020300 2020
1215 Maryland 24510030100         Baltimore city, MD - 24510030100 2020
1216 Maryland 24510030200         Baltimore city, MD - 24510030200 2020
1217 Maryland 24510040100         Baltimore city, MD - 24510040100 2020
1218 Maryland 24510040200         Baltimore city, MD - 24510040200 2020
1219 Maryland 24510060100         Baltimore city, MD - 24510060100 2020
1220 Maryland 24510060200         Baltimore city, MD - 24510060200 2020
1221 Maryland 24510060300         Baltimore city, MD - 24510060300 2020
1222 Maryland 24510060400         Baltimore city, MD - 24510060400 2020
1223 Maryland 24510070100         Baltimore city, MD - 24510070100 2020
1224 Maryland 24510070200         Baltimore city, MD - 24510070200 2020
1225 Maryland 24510070300         Baltimore city, MD - 24510070300 2020
1226 Maryland 24510070400         Baltimore city, MD - 24510070400 2020
1227 Maryland 24510080101         Baltimore city, MD - 24510080101 2020
1228 Maryland 24510080102         Baltimore city, MD - 24510080102 2020
1229 Maryland 24510080200         Baltimore city, MD - 24510080200 2020
1230 Maryland 24510080301         Baltimore city, MD - 24510080301 2020
1231 Maryland 24510080302         Baltimore city, MD - 24510080302 2020
1232 Maryland 24510080400         Baltimore city, MD - 24510080400 2020
1233 Maryland 24510080500         Baltimore city, MD - 24510080500 2020
1234 Maryland 24510080600         Baltimore city, MD - 24510080600 2020
1235 Maryland 24510080700         Baltimore city, MD - 24510080700 2020
1236 Maryland 24510080800         Baltimore city, MD - 24510080800 2020
1237 Maryland 24510090100         Baltimore city, MD - 24510090100 2020
1238 Maryland 24510090200         Baltimore city, MD - 24510090200 2020
1239 Maryland 24510090300         Baltimore city, MD - 24510090300 2020
1240 Maryland 24510090400         Baltimore city, MD - 24510090400 2020
1241 Maryland 24510090500         Baltimore city, MD - 24510090500 2020
1242 Maryland 24510090600         Baltimore city, MD - 24510090600 2020
1243 Maryland 24510090700         Baltimore city, MD - 24510090700 2020
1244 Maryland 24510090800         Baltimore city, MD - 24510090800 2020
1245 Maryland 24510090900         Baltimore city, MD - 24510090900 2020
1246 Maryland 24510100100         Baltimore city, MD - 24510100100 2020
1247 Maryland 24510100200         Baltimore city, MD - 24510100200 2020
1248 Maryland 24510100300         Baltimore city, MD - 24510100300 2020
1249 Maryland 24510110100         Baltimore city, MD - 24510110100 2020
1250 Maryland 24510110200         Baltimore city, MD - 24510110200 2020
1251 Maryland 24510120100         Baltimore city, MD - 24510120100 2020
1252 Maryland 24510120201         Baltimore city, MD - 24510120201 2020
1253 Maryland 24510120202         Baltimore city, MD - 24510120202 2020
1254 Maryland 24510120300         Baltimore city, MD - 24510120300 2020
1255 Maryland 24510120400         Baltimore city, MD - 24510120400 2020
1256 Maryland 24510120500         Baltimore city, MD - 24510120500 2020
1257 Maryland 24510120600         Baltimore city, MD - 24510120600 2020
1258 Maryland 24510120700         Baltimore city, MD - 24510120700 2020
1259 Maryland 24510130100         Baltimore city, MD - 24510130100 2020
1260 Maryland 24510130200         Baltimore city, MD - 24510130200 2020
1261 Maryland 24510130300         Baltimore city, MD - 24510130300 2020
1262 Maryland 24510130400         Baltimore city, MD - 24510130400 2020
1263 Maryland 24510130600         Baltimore city, MD - 24510130600 2020
1264 Maryland 24510130700         Baltimore city, MD - 24510130700 2020
1265 Maryland 24510130803         Baltimore city, MD - 24510130803 2020
1266 Maryland 24510130804         Baltimore city, MD - 24510130804 2020
1267 Maryland 24510130805         Baltimore city, MD - 24510130805 2020
1268 Maryland 24510130806         Baltimore city, MD - 24510130806 2020
1269 Maryland 24510140100         Baltimore city, MD - 24510140100 2020
1270 Maryland 24510140200         Baltimore city, MD - 24510140200 2020
1271 Maryland 24510140300         Baltimore city, MD - 24510140300 2020
1272 Maryland 24510150100         Baltimore city, MD - 24510150100 2020
1273 Maryland 24510150200         Baltimore city, MD - 24510150200 2020
1274 Maryland 24510150300         Baltimore city, MD - 24510150300 2020
1275 Maryland 24510150400         Baltimore city, MD - 24510150400 2020
1276 Maryland 24510150500         Baltimore city, MD - 24510150500 2020
1277 Maryland 24510150600         Baltimore city, MD - 24510150600 2020
1278 Maryland 24510150701         Baltimore city, MD - 24510150701 2020
1279 Maryland 24510150702         Baltimore city, MD - 24510150702 2020
1280 Maryland 24510150800         Baltimore city, MD - 24510150800 2020
1281 Maryland 24510150900         Baltimore city, MD - 24510150900 2020
1282 Maryland 24510151000         Baltimore city, MD - 24510151000 2020
1283 Maryland 24510151100         Baltimore city, MD - 24510151100 2020
1284 Maryland 24510151200         Baltimore city, MD - 24510151200 2020
1285 Maryland 24510151300         Baltimore city, MD - 24510151300 2020
1286 Maryland 24510160100         Baltimore city, MD - 24510160100 2020
1287 Maryland 24510160200         Baltimore city, MD - 24510160200 2020
1288 Maryland 24510160300         Baltimore city, MD - 24510160300 2020
1289 Maryland 24510160400         Baltimore city, MD - 24510160400 2020
1290 Maryland 24510160500         Baltimore city, MD - 24510160500 2020
1291 Maryland 24510160600         Baltimore city, MD - 24510160600 2020
1292 Maryland 24510160700         Baltimore city, MD - 24510160700 2020
1293 Maryland 24510160801         Baltimore city, MD - 24510160801 2020
1294 Maryland 24510160802         Baltimore city, MD - 24510160802 2020
1295 Maryland 24510170100         Baltimore city, MD - 24510170100 2020
1296 Maryland 24510170200         Baltimore city, MD - 24510170200 2020
1297 Maryland 24510170300         Baltimore city, MD - 24510170300 2020
1298 Maryland 24510180100         Baltimore city, MD - 24510180100 2020
1299 Maryland 24510180200         Baltimore city, MD - 24510180200 2020
1300 Maryland 24510180300         Baltimore city, MD - 24510180300 2020
1301 Maryland 24510190100         Baltimore city, MD - 24510190100 2020
1302 Maryland 24510190200         Baltimore city, MD - 24510190200 2020
1303 Maryland 24510190300         Baltimore city, MD - 24510190300 2020
1304 Maryland 24510200100         Baltimore city, MD - 24510200100 2020
1305 Maryland 24510200200         Baltimore city, MD - 24510200200 2020
1306 Maryland 24510200300         Baltimore city, MD - 24510200300 2020
1307 Maryland 24510200400         Baltimore city, MD - 24510200400 2020
1308 Maryland 24510200500         Baltimore city, MD - 24510200500 2020
1309 Maryland 24510200600         Baltimore city, MD - 24510200600 2020
1310 Maryland 24510200701         Baltimore city, MD - 24510200701 2020
1311 Maryland 24510200702         Baltimore city, MD - 24510200702 2020
1312 Maryland 24510200800         Baltimore city, MD - 24510200800 2020
1313 Maryland 24510210100         Baltimore city, MD - 24510210100 2020
1314 Maryland 24510210200         Baltimore city, MD - 24510210200 2020
1315 Maryland 24510220100         Baltimore city, MD - 24510220100 2020
1316 Maryland 24510230100         Baltimore city, MD - 24510230100 2020
1317 Maryland 24510230200         Baltimore city, MD - 24510230200 2020
1318 Maryland 24510230300         Baltimore city, MD - 24510230300 2020
1319 Maryland 24510240100         Baltimore city, MD - 24510240100 2020
1320 Maryland 24510240200         Baltimore city, MD - 24510240200 2020
1321 Maryland 24510240300         Baltimore city, MD - 24510240300 2020
1322 Maryland 24510240400         Baltimore city, MD - 24510240400 2020
1323 Maryland 24510250101         Baltimore city, MD - 24510250101 2020
1324 Maryland 24510250102         Baltimore city, MD - 24510250102 2020
1325 Maryland 24510250103         Baltimore city, MD - 24510250103 2020
1326 Maryland 24510250203         Baltimore city, MD - 24510250203 2020
1327 Maryland 24510250204         Baltimore city, MD - 24510250204 2020
1328 Maryland 24510250205         Baltimore city, MD - 24510250205 2020
1329 Maryland 24510250206         Baltimore city, MD - 24510250206 2020
1330 Maryland 24510250207         Baltimore city, MD - 24510250207 2020
1331 Maryland 24510250301         Baltimore city, MD - 24510250301 2020
1332 Maryland 24510250303         Baltimore city, MD - 24510250303 2020
1333 Maryland 24510250401         Baltimore city, MD - 24510250401 2020
1334 Maryland 24510250402         Baltimore city, MD - 24510250402 2020
1335 Maryland 24510250500         Baltimore city, MD - 24510250500 2020
1336 Maryland 24510250600         Baltimore city, MD - 24510250600 2020
1337 Maryland 24510260101         Baltimore city, MD - 24510260101 2020
1338 Maryland 24510260102         Baltimore city, MD - 24510260102 2020
1339 Maryland 24510260201         Baltimore city, MD - 24510260201 2020
1340 Maryland 24510260202         Baltimore city, MD - 24510260202 2020
1341 Maryland 24510260203         Baltimore city, MD - 24510260203 2020
1342 Maryland 24510260301         Baltimore city, MD - 24510260301 2020
1343 Maryland 24510260302         Baltimore city, MD - 24510260302 2020
1344 Maryland 24510260303         Baltimore city, MD - 24510260303 2020
1345 Maryland 24510260401         Baltimore city, MD - 24510260401 2020
1346 Maryland 24510260402         Baltimore city, MD - 24510260402 2020
1347 Maryland 24510260403         Baltimore city, MD - 24510260403 2020
1348 Maryland 24510260404         Baltimore city, MD - 24510260404 2020
1349 Maryland 24510260501         Baltimore city, MD - 24510260501 2020
1350 Maryland 24510260604         Baltimore city, MD - 24510260604 2020
1351 Maryland 24510260605         Baltimore city, MD - 24510260605 2020
1352 Maryland 24510260700         Baltimore city, MD - 24510260700 2020
1353 Maryland 24510260800         Baltimore city, MD - 24510260800 2020
1354 Maryland 24510260900         Baltimore city, MD - 24510260900 2020
1355 Maryland 24510261000         Baltimore city, MD - 24510261000 2020
1356 Maryland 24510261100         Baltimore city, MD - 24510261100 2020
1357 Maryland 24510270101         Baltimore city, MD - 24510270101 2020
1358 Maryland 24510270102         Baltimore city, MD - 24510270102 2020
1359 Maryland 24510270200         Baltimore city, MD - 24510270200 2020
1360 Maryland 24510270301         Baltimore city, MD - 24510270301 2020
1361 Maryland 24510270302         Baltimore city, MD - 24510270302 2020
1362 Maryland 24510270401         Baltimore city, MD - 24510270401 2020
1363 Maryland 24510270402         Baltimore city, MD - 24510270402 2020
1364 Maryland 24510270501         Baltimore city, MD - 24510270501 2020
1365 Maryland 24510270502         Baltimore city, MD - 24510270502 2020
1366 Maryland 24510270600         Baltimore city, MD - 24510270600 2020
1367 Maryland 24510270701         Baltimore city, MD - 24510270701 2020
1368 Maryland 24510270702         Baltimore city, MD - 24510270702 2020
1369 Maryland 24510270703         Baltimore city, MD - 24510270703 2020
1370 Maryland 24510270801         Baltimore city, MD - 24510270801 2020
1371 Maryland 24510270802         Baltimore city, MD - 24510270802 2020
1372 Maryland 24510270803         Baltimore city, MD - 24510270803 2020
1373 Maryland 24510270804         Baltimore city, MD - 24510270804 2020
1374 Maryland 24510270805         Baltimore city, MD - 24510270805 2020
1375 Maryland 24510270901         Baltimore city, MD - 24510270901 2020
1376 Maryland 24510270902         Baltimore city, MD - 24510270902 2020
1377 Maryland 24510270903         Baltimore city, MD - 24510270903 2020
1378 Maryland 24510271001         Baltimore city, MD - 24510271001 2020
1379 Maryland 24510271002         Baltimore city, MD - 24510271002 2020
1380 Maryland 24510271101         Baltimore city, MD - 24510271101 2020
1381 Maryland 24510271102         Baltimore city, MD - 24510271102 2020
1382 Maryland 24510271200         Baltimore city, MD - 24510271200 2020
1383 Maryland 24510271300         Baltimore city, MD - 24510271300 2020
1384 Maryland 24510271400         Baltimore city, MD - 24510271400 2020
1385 Maryland 24510271501         Baltimore city, MD - 24510271501 2020
1386 Maryland 24510271503         Baltimore city, MD - 24510271503 2020
1387 Maryland 24510271600         Baltimore city, MD - 24510271600 2020
1388 Maryland 24510271700         Baltimore city, MD - 24510271700 2020
1389 Maryland 24510271801         Baltimore city, MD - 24510271801 2020
1390 Maryland 24510271802         Baltimore city, MD - 24510271802 2020
1391 Maryland 24510271900         Baltimore city, MD - 24510271900 2020
1392 Maryland 24510272003         Baltimore city, MD - 24510272003 2020
1393 Maryland 24510272004         Baltimore city, MD - 24510272004 2020
1394 Maryland 24510272005         Baltimore city, MD - 24510272005 2020
1395 Maryland 24510272006         Baltimore city, MD - 24510272006 2020
1396 Maryland 24510272007         Baltimore city, MD - 24510272007 2020
1397 Maryland 24510280101         Baltimore city, MD - 24510280101 2020
1398 Maryland 24510280102         Baltimore city, MD - 24510280102 2020
1399 Maryland 24510280200         Baltimore city, MD - 24510280200 2020
1400 Maryland 24510280301         Baltimore city, MD - 24510280301 2020
1401 Maryland 24510280302         Baltimore city, MD - 24510280302 2020
1402 Maryland 24510280401         Baltimore city, MD - 24510280401 2020
1403 Maryland 24510280402         Baltimore city, MD - 24510280402 2020
1404 Maryland 24510280403         Baltimore city, MD - 24510280403 2020
1405 Maryland 24510280404         Baltimore city, MD - 24510280404 2020
1406 Maryland 24510280500         Baltimore city, MD - 24510280500 2020
     StateFIPS    depressrate energyburdenrate    englishrates internetlackrate
1           24          23.9%             5.0%            0.3%            22.5%
2           24          20.1%             4.4%            1.7%            27.3%
3           24          23.2%             3.9%            <NA>             <NA>
4           24          23.6%             3.4%            <NA>             <NA>
5           24          24.6%             5.2%            0.5%            29.3%
6           24          23.1%             4.3%            0.0%            18.7%
7           24          25.6%             5.3%            0.0%            16.4%
8           24          26.8%             5.7%            1.2%            17.8%
9           24          24.6%             5.0%            1.1%            31.9%
10          24          23.6%             3.7%            0.1%            12.3%
11          24          21.7%             2.7%            0.0%             6.9%
12          24          18.7%             3.6%            1.9%            12.5%
13          24          20.8%             2.6%            0.8%             9.6%
14          24          22.9%             3.0%            0.4%            10.9%
15          24          24.4%             3.9%            0.0%            25.1%
16          24          24.2%             4.0%            1.1%            25.9%
17          24          22.2%             3.4%            1.3%            11.5%
18          24          23.7%             3.8%            1.7%            15.0%
19          24          25.5%             3.9%            1.6%            12.7%
20          24          23.1%             3.6%            0.0%            19.9%
21          24          23.3%             3.8%            3.2%            10.1%
22          24          24.1%             4.0%            0.2%            18.8%
23          24          23.8%             4.4%            0.0%            21.4%
24          24          18.2%             2.0%            0.6%             5.3%
25          24          20.3%             1.9%            <NA>             <NA>
26          24          19.6%             2.0%            <NA>             <NA>
27          24          18.7%             1.8%            <NA>             <NA>
28          24          18.6%             1.9%            4.5%             6.6%
29          24          19.1%             2.0%            0.8%             4.3%
30          24          18.4%             1.6%            1.5%             2.3%
31          24          18.4%             1.5%            4.8%             1.7%
32          24          18.7%             1.6%            2.7%             1.2%
33          24          18.1%             1.6%            7.9%             0.4%
34          24          18.7%             1.4%            3.6%             1.0%
35          24          18.4%             1.8%            1.3%             4.9%
36          24          17.5%             1.6%            1.5%             5.9%
37          24          18.2%             1.9%            5.4%             9.5%
38          24          18.1%             2.0%            0.7%             0.9%
39          24          17.0%             1.7%            1.0%             2.7%
40          24          18.1%             1.4%            <NA>             <NA>
41          24          17.0%             1.7%            2.9%             3.1%
42          24          19.0%             1.6%            <NA>             <NA>
43          24          18.0%             1.6%            <NA>             <NA>
44          24          17.5%             1.7%            5.6%             4.4%
45          24          19.4%             2.0%            <NA>             <NA>
46          24          19.3%             1.9%            4.7%            14.1%
47          24          18.3%             1.6%           12.8%             7.6%
48          24          18.5%             1.8%            5.5%             7.7%
49          24          19.8%             1.0%            1.5%             5.2%
50          24          19.2%             2.1%            0.9%             2.9%
51          24          19.3%             2.1%            1.0%             8.3%
52          24          19.1%             2.1%            0.7%             6.2%
53          24          19.8%             3.4%            7.3%            14.0%
54          24          20.0%             1.6%            <NA>             <NA>
55          24          19.9%             2.4%            <NA>             <NA>
56          24          20.0%             2.4%            4.0%             3.6%
57          24          20.3%             2.6%            5.2%             8.4%
58          24          20.2%             2.3%            5.2%            12.7%
59          24          19.9%             2.5%            <NA>             <NA>
60          24          18.9%             2.1%            <NA>             <NA>
61          24          18.8%             1.9%            <NA>             <NA>
62          24          19.8%             2.3%            <NA>             <NA>
63          24          19.6%             2.3%            <NA>             <NA>
64          24          17.6%             1.5%            1.8%             2.9%
65          24          18.8%             1.8%            1.4%             7.8%
66          24          17.4%             1.5%            <NA>             <NA>
67          24          17.8%             1.7%            <NA>             <NA>
68          24          17.3%             1.6%            4.1%             4.1%
69          24          16.6%             1.6%            1.8%             0.0%
70          24          17.1%             1.4%            3.6%             0.0%
71          24          18.6%             1.6%            4.0%             2.8%
72          24          19.2%             1.8%            1.3%             4.7%
73          24          19.1%             1.7%            0.4%             1.9%
74          24          18.6%             1.5%            <NA>             <NA>
75          24          18.9%             1.7%            1.0%             0.4%
76          24          19.5%             1.7%            3.0%             2.0%
77          24          18.4%             1.9%            1.8%             3.2%
78          24          17.9%             1.7%            1.8%             0.9%
79          24          19.6%             1.9%            <NA>             <NA>
80          24          18.5%             1.8%            <NA>             <NA>
81          24          19.9%             1.9%            <NA>             <NA>
82          24          19.5%             2.1%            0.2%             4.5%
83          24          20.0%             2.0%            1.7%             3.0%
84          24          21.2%             1.9%            1.8%             6.7%
85          24          20.3%             2.5%            2.3%            11.1%
86          24          21.5%             2.1%            4.7%             5.5%
87          24          21.3%             2.2%            1.4%             3.2%
88          24          20.7%             2.2%            <NA>             <NA>
89          24          17.0%             1.7%            <NA>             <NA>
90          24          16.9%             1.9%            2.1%             1.0%
91          24          17.3%             1.8%            4.6%             0.7%
92          24          18.4%             2.4%            1.9%             3.1%
93          24          19.0%             2.1%            <NA>             <NA>
94          24          18.8%             1.8%            6.5%             6.6%
95          24          18.6%             2.1%            5.9%             4.6%
96          24          18.3%             1.6%            3.8%            10.9%
97          24          18.2%             1.7%            4.3%             1.0%
98          24          15.9%          No Data            2.0%             0.0%
99          24          16.3%             1.5%            <NA>             <NA>
100         24          20.1%             1.8%            7.4%             0.0%
101         24          21.3%             1.9%            5.4%             0.7%
102         24          19.1%             1.4%            2.2%             3.8%
103         24          18.2%             1.6%            3.4%             3.7%
104         24          18.2%             1.7%            <NA>             <NA>
105         24          18.4%             1.8%            2.0%             7.5%
106         24          19.4%             2.1%            8.8%             8.1%
107         24          19.0%             1.9%            1.2%             5.5%
108         24          21.3%             3.4%            7.5%            13.5%
109         24          21.9%             2.9%            3.3%            20.9%
110         24          19.9%             3.2%            8.9%            21.3%
111         24          20.8%             2.5%            <NA>             <NA>
112         24          20.4%             3.0%            <NA>             <NA>
113         24          19.4%             2.4%            2.2%             6.8%
114         24          18.1%             2.3%            1.1%            10.2%
115         24          20.0%             2.1%            1.6%            10.1%
116         24          20.9%             2.9%            5.4%            10.4%
117         24          20.2%             2.8%            6.0%            16.5%
118         24          20.2%             2.6%            4.8%            16.9%
119         24          20.7%             3.1%            3.7%             9.6%
120         24          19.2%             2.3%            4.5%            10.4%
121         24          20.4%             2.6%            0.0%            11.4%
122         24          18.8%             2.4%            2.9%             4.0%
123         24          17.6%             2.1%            3.3%             5.5%
124         24          19.4%             2.4%            9.0%            11.4%
125         24          15.5%             1.9%            0.6%             9.7%
126         24          17.9%             1.9%            0.0%             2.6%
127         24 Low Population          No Data            0.0%             0.0%
128         24 Low Population          No Data Zero Population             0.0%
129         24          14.1%             1.6%            6.4%            27.2%
130         24          19.8%             2.3%            4.3%             4.3%
131         24          17.6%             1.8%            3.6%             5.7%
132         24          17.3%             1.7%            1.5%             2.5%
133         24          18.7%             2.1%            8.0%             3.6%
134         24          18.3%             2.1%            1.8%             3.7%
135         24          17.7%             2.3%            4.8%             1.1%
136         24          18.5%             2.5%            4.3%             7.7%
137         24          17.1%             2.2%           17.8%            11.3%
138         24          17.2%             1.9%            3.9%             2.5%
139         24          17.5%             2.7%            4.6%            10.4%
140         24          16.4%             2.6%            7.1%            17.9%
141         24          17.5%             2.5%            2.9%             7.1%
142         24          17.7%             3.0%            4.0%             6.3%
143         24          16.5%             2.7%            4.0%            10.8%
144         24          18.2%             1.8%            1.4%             4.3%
145         24          18.3%             1.8%            0.4%             2.5%
146         24          15.7%             2.0%           15.2%             4.2%
147         24          16.4%             2.4%            5.9%            19.5%
148         24          16.2%             1.8%           10.3%             5.4%
149         24          16.3%             2.5%           17.0%             2.6%
150         24          17.6%             2.2%            1.9%             5.7%
151         24          17.3%             2.4%            2.3%             0.6%
152         24          15.7%             2.2%            2.9%             9.3%
153         24          16.2%             2.3%            6.2%            21.6%
154         24          15.3%             2.7%            2.6%            10.9%
155         24          16.5%             2.0%            8.8%             7.6%
156         24          16.6%             2.2%           10.0%            11.2%
157         24          16.9%             2.4%            3.8%             2.5%
158         24          15.5%             2.7%            1.8%            15.9%
159         24          17.0%             2.7%            8.6%             7.8%
160         24          17.5%             2.6%            1.5%            11.4%
161         24          17.7%             2.1%            <NA>             <NA>
162         24          17.7%             2.6%            1.8%             8.9%
163         24          17.0%             2.4%            7.1%            11.2%
164         24          15.7%             2.1%            3.6%             4.4%
165         24          16.4%             2.1%            2.5%             6.6%
166         24          15.4%             2.1%            2.1%             4.4%
167         24          15.8%             1.5%            <NA>             <NA>
168         24          16.3%             2.5%            2.6%             2.4%
169         24          15.1%             1.8%            0.7%             5.0%
170         24          15.7%             2.3%            2.3%             4.6%
171         24          14.8%             2.6%            3.4%            12.9%
172         24          15.4%             2.6%            4.1%             7.2%
173         24          15.1%             2.7%            0.1%             1.8%
174         24          16.7%             2.4%            1.0%            13.9%
175         24          15.7%             1.7%            4.5%            26.7%
176         24          16.5%             2.0%            8.2%            16.3%
177         24          16.7%             1.7%            4.0%            14.3%
178         24          18.2%             1.6%            9.0%             5.1%
179         24          17.7%             1.4%            8.0%             2.0%
180         24          16.7%             1.9%            <NA>             <NA>
181         24          18.4%             1.9%            1.9%             5.8%
182         24          16.2%             1.5%            3.5%             4.9%
183         24          16.3%             1.6%            1.4%             5.1%
184         24          15.9%             1.4%           10.3%             7.1%
185         24          17.9%             1.9%            4.0%             0.2%
186         24          17.9%             2.2%            9.4%             4.3%
187         24          18.5%             2.1%            9.5%             4.8%
188         24          20.5%             2.4%           12.2%            21.3%
189         24          18.4%             1.9%            3.1%             0.0%
190         24          18.3%             2.4%           11.1%             9.0%
191         24          18.3%             1.9%            4.1%             8.8%
192         24          19.4%             2.4%           14.9%             6.5%
193         24          20.4%             2.8%            7.5%             5.7%
194         24          18.8%             2.1%            1.5%             7.9%
195         24          18.4%             1.8%            1.6%             6.9%
196         24          17.7%             1.5%            5.2%            13.7%
197         24          19.0%             2.2%            1.0%            10.0%
198         24          19.1%             2.0%            0.8%             2.2%
199         24          18.7%             2.2%            0.6%             3.6%
200         24          19.4%             2.1%            0.4%             6.8%
201         24          17.3%             1.8%            1.8%             2.0%
202         24          17.3%             1.8%            0.4%             4.9%
203         24          16.2%             1.7%            5.7%             4.2%
204         24          16.9%             1.7%            1.7%             0.0%
205         24          15.7%             1.7%            2.8%             5.3%
206         24          16.1%             1.3%            3.1%            18.1%
207         24          15.7%             1.7%            3.5%            10.9%
208         24          17.2%             1.8%           14.1%             9.8%
209         24          16.9%             1.6%            7.2%             4.7%
210         24          18.8%             1.9%           11.0%             9.0%
211         24          19.2%             1.7%           12.4%             4.5%
212         24          17.2%             1.9%            4.4%             2.6%
213         24          16.6%             1.7%            2.4%             8.5%
214         24          16.9%             1.6%            2.7%             5.2%
215         24          17.3%             1.4%            4.7%             5.5%
216         24          16.7%             1.5%            8.0%             1.7%
217         24          17.9%             1.8%            4.3%            13.7%
218         24          17.6%             1.5%            0.0%             7.8%
219         24          17.8%             1.9%            0.8%             5.9%
220         24          17.4%             1.7%            1.8%             1.7%
221         24          18.8%             2.0%            0.6%            10.8%
222         24          18.5%             2.1%            0.0%             8.3%
223         24          18.2%             2.0%            0.4%             7.1%
224         24          17.3%             1.9%            1.2%             9.8%
225         24          18.9%             2.2%            5.9%             5.9%
226         24          18.9%             2.0%            3.0%             5.3%
227         24          19.0%             1.8%            5.7%             2.9%
228         24          19.5%             1.9%            6.7%             4.2%
229         24          18.3%             2.0%            3.1%             6.6%
230         24          18.0%             1.7%            2.8%            10.6%
231         24          18.8%             2.0%            7.1%             7.9%
232         24          18.8%             2.0%            4.6%            15.6%
233         24          16.0%             1.5%            <NA>             <NA>
234         24          21.0%             2.1%            4.4%             3.1%
235         24          19.1%             1.8%            4.1%             2.2%
236         24          18.8%             2.0%           12.1%             1.6%
237         24          20.5%             3.2%            2.4%            10.4%
238         24          20.4%             2.7%            4.9%            12.2%
239         24          22.3%             2.9%            4.0%            15.9%
240         24          22.8%             2.7%            4.7%             9.1%
241         24          21.1%             2.8%            0.4%            15.7%
242         24          21.8%             3.6%            3.6%            11.9%
243         24          21.5%             2.9%            2.7%            11.2%
244         24          21.2%             3.0%           17.1%             9.9%
245         24          22.2%             3.3%           11.0%            11.2%
246         24          21.9%             3.1%            6.5%            13.7%
247         24          21.5%             3.9%           12.9%            16.7%
248         24          21.8%             3.6%            3.4%            11.2%
249         24          22.0%             3.2%            6.3%            11.9%
250         24          22.8%             3.6%            4.5%            34.0%
251         24          21.6%             3.5%            0.0%            21.9%
252         24          21.1%             3.2%            1.8%            16.6%
253         24          22.1%             3.6%            5.2%            15.1%
254         24          18.8%             4.5%            <NA>             <NA>
255         24          21.1%             3.1%           18.7%            17.7%
256         24          21.0%             2.7%            5.0%             7.4%
257         24          21.5%             3.1%            3.1%            20.1%
258         24          22.7%             4.0%            7.2%            19.2%
259         24          20.2%             2.7%            2.9%             4.8%
260         24          19.0%             2.0%            1.2%             3.7%
261         24          20.5%             2.0%            3.0%             9.3%
262         24          19.6%             2.4%            2.1%            11.0%
263         24          19.1%             3.0%           25.8%            25.4%
264         24          19.9%             2.5%            1.4%            14.0%
265         24          19.2%             2.6%            1.9%            16.9%
266         24          19.0%             2.5%            3.9%            12.1%
267         24          19.5%             2.3%            9.9%             6.5%
268         24          19.2%             2.3%            2.0%             9.0%
269         24          17.4%             1.9%            2.9%             2.3%
270         24          18.4%             2.4%           17.9%             7.2%
271         24          18.7%             1.9%            7.1%             3.3%
272         24          18.0%             2.2%            5.6%             9.0%
273         24          17.9%             2.2%            5.4%             8.9%
274         24          17.2%             2.9%            3.3%             8.6%
275         24          19.0%             2.7%            4.1%             7.6%
276         24          18.4%             2.8%            7.9%            15.9%
277         24          20.3%             2.7%            4.1%            15.0%
278         24          21.0%             3.2%            0.6%            14.7%
279         24          20.4%             3.0%            2.3%            19.8%
280         24          20.9%             3.0%            0.4%             8.5%
281         24          21.0%             3.3%            0.4%            19.5%
282         24          20.7%             3.0%            3.1%            11.6%
283         24          20.2%             3.3%            4.9%            16.8%
284         24          21.0%             2.8%            4.2%            17.6%
285         24          20.1%             2.7%            1.3%             7.6%
286         24          19.6%             2.5%            0.4%             8.1%
287         24          19.6%             2.7%            3.9%             9.9%
288         24          21.1%             2.8%            2.7%             9.8%
289         24          21.5%             3.5%            6.8%            20.5%
290         24          18.2%             2.5%            8.6%             8.5%
291         24          20.2%             3.5%           16.3%             8.3%
292         24          22.0%             2.9%            5.4%            12.4%
293         24          20.2%             2.9%            3.1%            13.0%
294         24          18.9%             1.8%            1.3%             4.8%
295         24          20.2%             2.7%            1.9%             8.7%
296         24          20.8%             2.7%            1.5%             6.5%
297         24          20.1%             2.6%            2.3%             9.5%
298         24          20.9%             2.5%            2.9%             7.4%
299         24          20.5%             2.8%            0.6%             7.1%
300         24          20.2%             2.6%            1.9%            13.8%
301         24          20.6%             3.0%            1.9%             9.9%
302         24          23.4%             3.2%            8.1%            17.7%
303         24          20.5%             2.7%            3.9%             6.7%
304         24          22.8%             3.4%            2.4%             6.6%
305         24          16.0%             1.7%            2.1%             0.5%
306         24          17.1%             1.7%            7.8%             4.4%
307         24          20.1%             2.2%            <NA>             <NA>
308         24          18.7%             1.7%            1.7%             6.8%
309         24          15.9%             1.6%            1.5%             0.7%
310         24          16.6%             1.3%            0.5%             1.1%
311         24          18.2%             1.6%            0.9%             3.7%
312         24          18.7%             1.8%            7.7%             1.4%
313         24          16.5%             1.6%            7.1%             6.8%
314         24          31.4%             9.4%            1.0%            14.9%
315         24          12.9%             1.4%            1.1%             8.3%
316         24          17.0%             1.6%            1.3%             1.8%
317         24          18.7%             2.0%            2.2%             3.0%
318         24          18.4%             1.9%            3.4%            15.9%
319         24          17.1%             1.6%            0.5%             2.1%
320         24          18.2%             1.9%            8.5%             6.1%
321         24          18.6%             1.8%            3.5%             3.6%
322         24          19.1%             2.1%            9.9%             3.0%
323         24          18.1%             2.3%            8.1%             5.7%
324         24          18.2%             2.5%            3.4%             8.8%
325         24          17.9%             2.9%            3.4%            10.7%
326         24          19.3%             2.1%            3.8%             7.9%
327         24          20.5%             2.9%            5.0%            19.3%
328         24          17.9%             2.0%            3.8%             2.6%
329         24          17.9%             2.9%            6.3%            19.4%
330         24          19.2%             2.6%            4.0%             8.6%
331         24          19.0%             2.3%            1.1%             7.3%
332         24          19.3%             2.3%            0.4%             8.3%
333         24          19.5%             2.5%            2.5%             5.9%
334         24          19.4%             2.1%            3.3%             6.9%
335         24          22.4%             2.8%            1.7%             7.1%
336         24          16.3%             2.0%            3.3%             3.7%
337         24          17.0%             1.9%            3.5%             6.1%
338         24          24.3%             1.9%            1.5%            27.2%
339         24          19.9%             2.2%            3.6%             3.8%
340         24 Low Population          No Data            <NA>             <NA>
341         24 Low Population          No Data Zero Population             0.0%
342         24 Low Population          No Data Zero Population             0.0%
343         24          17.8%             2.1%            <NA>             <NA>
344         24          18.4%             2.2%            <NA>             <NA>
345         24          17.9%             1.9%            1.0%             5.9%
346         24          18.3%             1.9%            1.2%            11.8%
347         24          19.9%             1.9%            <NA>             <NA>
348         24          18.9%             2.3%            1.7%            13.8%
349         24          18.7%             2.0%            2.3%             3.6%
350         24          19.3%             2.4%            0.3%             2.7%
351         24          18.3%             2.1%            1.0%             5.9%
352         24          18.5%             2.1%            2.1%            16.2%
353         24          18.8%             2.4%            1.7%            11.2%
354         24          19.0%             2.4%            1.2%             8.3%
355         24          18.4%             2.3%            0.0%             9.3%
356         24          19.6%             2.8%            <NA>             <NA>
357         24          17.6%             2.3%            <NA>             <NA>
358         24          17.8%             2.2%            <NA>             <NA>
359         24          19.6%             2.7%            0.4%             9.8%
360         24          20.0%             2.5%            0.2%             5.3%
361         24 Low Population          No Data Zero Population             0.0%
362         24          22.7%             5.7%           17.6%            17.0%
363         24          22.5%             4.5%            5.1%            16.5%
364         24          22.0%             3.9%            2.1%            11.6%
365         24          20.9%             4.4%            0.0%            14.8%
366         24          20.7%             3.4%            0.7%             5.6%
367         24          21.4%             4.8%            2.8%             8.3%
368         24          20.3%             3.6%            0.2%            15.2%
369         24          20.4%             4.8%            3.1%             9.8%
370         24          22.3%             5.8%            2.8%            22.7%
371         24          20.3%             2.7%            1.0%            10.3%
372         24          19.3%             3.2%            0.0%            16.4%
373         24          19.0%             2.6%            1.4%            14.3%
374         24          19.0%             2.6%            0.6%             8.6%
375         24          17.9%             2.1%            2.4%            10.8%
376         24          17.6%             2.1%            1.6%             9.5%
377         24          17.8%             1.9%            1.3%             6.7%
378         24          17.7%             1.8%            0.3%             4.6%
379         24          17.6%             1.9%            1.7%             1.9%
380         24          17.5%             1.8%            3.2%             5.9%
381         24          18.3%             1.7%            2.5%             0.8%
382         24          16.9%             2.1%            2.0%             6.0%
383         24          18.3%             1.7%            4.1%             5.4%
384         24          17.1%             1.7%            0.3%             6.9%
385         24          18.4%             2.2%            0.3%             7.4%
386         24          18.7%             2.2%            0.8%            12.0%
387         24          19.2%             2.8%            0.7%            11.8%
388         24          19.4%             2.1%            1.2%             3.3%
389         24          19.0%             2.5%            4.7%             8.9%
390         24          18.8%             2.7%            3.0%            22.7%
391         24          18.3%             2.3%            2.4%            15.5%
392         24          16.4%             1.6%            2.4%            17.6%
393         24          19.4%             2.0%            3.6%             3.4%
394         24          19.6%             2.5%            0.6%            14.6%
395         24          17.9%             2.3%            1.4%            18.3%
396         24          18.4%             2.2%            <NA>             <NA>
397         24          19.9%             2.1%            <NA>             <NA>
398         24          18.5%             2.3%            1.1%             5.6%
399         24          18.7%             2.2%            0.2%             7.4%
400         24          18.2%             1.9%            0.0%             8.2%
401         24          19.5%             3.4%            0.0%             7.0%
402         24          18.9%             2.6%            0.1%             7.6%
403         24          19.3%             3.8%            1.0%            19.7%
404         24          17.8%             1.8%            2.3%             8.7%
405         24          18.1%             1.8%            2.5%             4.3%
406         24          17.9%             1.9%            0.2%             5.4%
407         24          18.4%             2.2%            1.1%             6.6%
408         24          18.1%             2.0%            1.2%             5.9%
409         24          19.4%             5.5%            0.5%            10.9%
410         24          20.0%             3.7%            6.1%             7.0%
411         24          22.8%             4.2%            4.6%            19.7%
412         24          20.7%             3.4%            1.3%            10.4%
413         24          21.6%             3.9%            3.1%            15.8%
414         24          19.9%             2.7%            1.1%            11.9%
415         24          21.5%             2.6%            <NA>             <NA>
416         24          19.6%             3.0%            0.2%             7.5%
417         24          19.6%             2.6%            2.0%             3.9%
418         24          19.7%             3.0%            1.4%             9.0%
419         24          22.9%             3.5%            1.9%            10.6%
420         24          19.8%             3.3%            0.7%             7.1%
421         24          21.9%             3.5%            0.2%             8.6%
422         24          21.5%             3.6%            <NA>             <NA>
423         24          20.7%             3.8%            0.2%             8.8%
424         24          18.8%             2.8%            0.9%            11.4%
425         24          20.7%             3.4%            0.2%            13.6%
426         24          21.3%             3.5%            4.0%             9.0%
427         24          20.6%             3.7%            0.0%             8.1%
428         24          15.3%             2.4%            2.6%            15.7%
429         24          16.7%             3.7%            2.8%            23.4%
430         24          17.1%             3.1%            2.4%             1.9%
431         24          17.8%             3.4%            3.0%            17.6%
432         24          16.7%             3.5%            0.7%            12.2%
433         24          18.0%             3.6%            0.4%            32.3%
434         24          18.0%             2.3%            0.0%            11.4%
435         24          16.2%             2.8%            1.3%             3.4%
436         24          14.9%             1.9%            4.1%             2.0%
437         24          15.6%             2.0%            1.7%             6.0%
438         24          15.8%             2.2%            2.9%             1.1%
439         24          15.7%             1.9%            2.9%             4.8%
440         24          16.4%             2.3%            5.7%             7.6%
441         24          16.1%             2.2%            0.6%             2.1%
442         24          16.2%             2.0%            2.9%             1.4%
443         24          17.2%             2.2%            1.0%             6.2%
444         24          16.7%             2.5%            4.0%             2.0%
445         24          18.0%             3.5%            2.8%            15.1%
446         24          16.9%             2.4%            1.6%            13.7%
447         24          15.6%             1.9%            2.4%             3.6%
448         24          17.2%             2.3%            4.1%             3.1%
449         24          16.6%             2.3%           11.2%            15.2%
450         24          16.0%             2.2%            1.4%             5.4%
451         24          17.5%             2.5%            <NA>             <NA>
452         24          18.1%             2.9%            0.0%            16.0%
453         24          18.7%             3.3%            0.0%            17.9%
454         24          18.7%             2.3%            4.2%            16.6%
455         24          17.1%             2.5%            0.7%            10.2%
456         24          16.7%             2.2%            <NA>             <NA>
457         24          16.1%             2.0%            <NA>             <NA>
458         24 Low Population          No Data Zero Population             0.0%
459         24          20.3%             4.0%            1.0%            13.0%
460         24          20.2%             4.7%            2.5%            14.3%
461         24          19.7%             5.0%            1.6%            17.5%
462         24          19.7%             3.7%            6.8%            15.7%
463         24          19.6%             5.7%            3.9%            29.2%
464         24          19.8%             5.4%            1.6%            14.5%
465         24          18.8%             3.6%            1.6%            15.4%
466         24          18.6%             5.6%            0.6%            18.1%
467         24          19.9%             6.3%            2.1%            28.5%
468         24 Low Population          No Data Zero Population             0.0%
469         24          20.5%             2.2%            2.2%            11.9%
470         24          20.6%             2.5%            1.8%             7.0%
471         24          19.9%             2.1%            1.1%            11.3%
472         24          20.1%             2.7%            1.6%            29.6%
473         24          20.2%             2.2%            <NA>             <NA>
474         24          19.3%             1.9%            7.2%             8.1%
475         24          20.4%             2.8%           27.4%             8.9%
476         24          18.1%             2.1%           17.7%             3.4%
477         24          19.6%             2.0%            1.9%             4.8%
478         24          19.8%             1.9%            6.6%             0.6%
479         24          20.1%             2.4%            9.0%             8.8%
480         24          20.1%             2.0%            5.3%            11.4%
481         24          18.4%             1.5%            2.9%             3.0%
482         24          18.5%             1.7%            <NA>             <NA>
483         24          19.8%             1.6%            3.8%             1.1%
484         24          19.0%             1.9%            6.9%            15.9%
485         24          19.1%             2.1%            7.6%            11.4%
486         24          19.5%             1.8%            4.2%             3.5%
487         24          17.9%             1.7%            4.5%             1.2%
488         24          17.9%             1.6%            4.8%             6.0%
489         24          18.2%             2.4%            0.0%             7.2%
490         24          17.9%             1.9%            4.7%            10.1%
491         24          20.0%             2.7%            1.2%            10.9%
492         24          20.8%             2.4%            3.0%            16.2%
493         24          19.8%             2.4%            1.7%            10.1%
494         24          20.6%             2.2%            0.1%            16.0%
495         24          19.8%             1.7%            0.2%             7.0%
496         24          19.9%             2.4%            0.3%             4.7%
497         24          19.8%             1.7%            <NA>             <NA>
498         24          18.7%             1.6%            0.6%             3.7%
499         24          18.9%             1.7%            1.5%             2.8%
500         24          18.9%             1.7%            2.0%             5.1%
501         24          20.4%             1.8%            6.6%             4.6%
502         24          19.2%             1.6%            4.7%             2.2%
503         24          19.5%             2.0%            4.9%             4.1%
504         24          18.9%             2.1%            1.6%            10.2%
505         24          17.0%             1.4%            8.6%             0.0%
506         24          17.3%             1.5%            <NA>             <NA>
507         24          19.3%             1.8%           11.1%             2.4%
508         24          18.0%             1.9%            1.4%            11.1%
509         24          19.6%             1.8%            2.3%             7.0%
510         24          19.7%             2.1%            3.5%             5.7%
511         24          19.7%             2.1%            1.0%             9.4%
512         24          19.2%             2.2%            0.1%             4.1%
513         24          18.6%             2.2%            0.5%             6.0%
514         24          18.8%             2.1%            1.7%             4.9%
515         24          19.9%             2.5%            1.0%            14.4%
516         24          19.7%             2.4%            0.9%             9.5%
517         24          20.9%             2.9%            0.2%            10.4%
518         24          20.8%             2.5%            0.8%            17.8%
519         24          21.5%             3.0%            1.8%            10.6%
520         24          19.5%             2.7%            9.6%            13.5%
521         24          22.3%             2.6%            1.3%            24.1%
522         24          21.2%             2.9%            0.0%            27.6%
523         24          20.6%             2.6%            0.3%            12.5%
524         24          19.8%             2.1%            1.6%             6.0%
525         24          20.6%             2.1%            0.0%            13.9%
526         24          20.9%             2.1%            7.8%             7.7%
527         24          19.7%             2.3%            1.1%            12.1%
528         24          21.7%             2.8%            1.1%             9.7%
529         24          19.3%             1.6%            1.2%             1.5%
530         24          20.9%             4.7%            0.0%            23.4%
531         24          22.4%             3.9%            1.9%            18.0%
532         24          21.0%             3.6%            0.4%             7.8%
533         24          21.6%             5.3%            0.6%            22.3%
534         24          19.6%             5.7%            <NA>             <NA>
535         24          21.3%             3.9%            <NA>             <NA>
536         24          21.9%             4.3%            0.9%            21.8%
537         24          17.6%             2.0%            2.2%            12.9%
538         24          19.8%             1.9%            0.7%             2.3%
539         24          17.9%             1.7%            2.6%             3.1%
540         24          19.5%             2.1%            5.4%             8.2%
541         24          18.3%             1.6%            2.9%             3.8%
542         24          18.2%             3.2%            2.1%            19.5%
543         24          18.8%             1.8%            5.0%             0.4%
544         24          19.6%             1.9%            0.9%             1.7%
545         24          19.2%             1.8%            6.0%             8.3%
546         24          18.6%             2.9%            3.2%             8.3%
547         24          19.2%             2.3%            2.9%            10.8%
548         24          18.5%             2.2%            0.2%            12.0%
549         24          18.8%             2.4%            0.0%             6.1%
550         24          19.9%             3.1%            9.7%            15.0%
551         24          18.3%             2.6%            2.1%             9.8%
552         24          18.5%             2.2%            <NA>             <NA>
553         24          18.0%             2.0%            0.9%             1.0%
554         24          19.2%             1.9%            2.8%             3.4%
555         24          17.9%             2.3%            0.4%             5.0%
556         24          18.4%             2.7%            0.0%             4.5%
557         24          19.8%             2.0%            0.6%             9.3%
558         24          18.2%             2.6%            3.3%            10.4%
559         24          18.4%             2.3%            1.4%            11.9%
560         24          23.5%             4.2%            7.4%            17.8%
561         24          19.0%             2.9%            3.1%            20.1%
562         24          18.5%             2.1%            1.7%             4.4%
563         24          17.2%             1.8%            0.9%             3.5%
564         24          18.7%             2.2%            1.7%             3.1%
565         24          18.4%             1.9%            0.0%             5.5%
566         24          18.4%             2.0%            1.0%             3.0%
567         24          18.4%             2.0%            0.0%             4.0%
568         24          18.4%             2.0%            0.8%             4.2%
569         24          18.0%             2.3%            1.5%             6.8%
570         24          17.6%             2.0%            0.9%             1.7%
571         24          17.3%             2.0%            4.1%            13.7%
572         24          18.7%             1.9%            0.6%             4.6%
573         24          17.2%             1.7%            2.0%             3.8%
574         24          18.8%             1.8%            1.4%             3.6%
575         24          18.6%             2.4%            0.7%             8.6%
576         24          17.8%             1.5%            0.5%             1.5%
577         24          18.5%             2.4%            0.8%            13.6%
578         24          18.5%             2.0%            3.0%             7.6%
579         24          18.2%             1.8%            2.5%             8.0%
580         24          19.0%             2.0%            4.7%            11.8%
581         24          17.4%             1.9%            1.3%             2.1%
582         24          18.8%             2.6%            0.7%             3.7%
583         24          19.1%             2.7%            0.3%             9.2%
584         24          17.7%             2.0%            0.0%             7.2%
585         24          18.6%             2.2%            0.0%             5.1%
586         24          20.2%             3.0%            1.2%             9.7%
587         24          21.3%             3.9%            0.0%            19.1%
588         24          18.6%             3.4%            0.6%             9.6%
589         24          19.3%             2.2%            1.3%            17.2%
590         24          18.9%             2.3%            1.2%            15.7%
591         24          17.7%             2.0%            0.7%             5.6%
592         24          17.9%             2.0%            1.1%             4.3%
593         24          18.1%             1.7%            3.6%             2.8%
594         24          15.6%             1.4%           10.1%             1.5%
595         24          15.5%             1.2%            4.5%             1.3%
596         24          16.2%             1.4%            8.8%             2.4%
597         24          18.5%             2.1%           12.3%             3.5%
598         24          16.2%             1.3%            6.9%             0.4%
599         24          17.6%             1.5%            <NA>             <NA>
600         24          14.2%             1.5%            7.6%             2.1%
601         24          17.8%             1.6%            1.7%             0.8%
602         24          14.8%             1.3%            6.0%             3.1%
603         24          15.1%             1.4%            5.2%             0.0%
604         24          15.1%             1.6%           10.0%             2.6%
605         24          16.0%             1.4%            7.2%             1.4%
606         24          13.6%             1.4%           10.0%             2.1%
607         24          14.6%             1.3%            6.3%             2.2%
608         24          15.5%             1.4%            5.2%             2.4%
609         24          15.1%             1.5%           10.0%             4.4%
610         24          13.7%             1.7%           16.3%             9.5%
611         24          14.9%             1.3%            6.7%             1.5%
612         24          15.6%             1.6%            8.3%             0.8%
613         24          14.0%             1.4%            9.9%             8.7%
614         24          14.6%             1.5%            7.7%             9.3%
615         24          16.1%             1.6%            2.6%             4.0%
616         24          15.5%             1.6%            5.2%             6.4%
617         24          17.3%             2.3%            1.2%             2.8%
618         24          16.6%             1.9%            <NA>             <NA>
619         24          14.7%             1.2%            <NA>             <NA>
620         24          15.2%             1.6%            4.4%             3.1%
621         24          15.3%             1.5%            3.9%             3.7%
622         24          15.9%             1.5%            5.5%             2.3%
623         24          15.5%             1.3%            <NA>             <NA>
624         24          15.1%             1.3%            4.3%             2.2%
625         24          16.9%             1.8%           10.1%             9.5%
626         24          13.8%             1.3%            7.0%             0.0%
627         24          14.1%             1.2%           14.6%             1.7%
628         24          16.1%             1.6%            2.0%             7.1%
629         24          15.6%             1.4%           10.4%             2.0%
630         24          15.6%             1.7%            1.1%             2.7%
631         24          16.2%             1.7%            8.0%             3.1%
632         24          15.8%             1.4%           11.6%             0.9%
633         24          16.1%             1.6%           13.9%             6.6%
634         24          16.1%             1.6%            5.9%             4.3%
635         24          15.8%             1.4%            2.6%             0.2%
636         24          16.4%             1.5%           10.9%            12.7%
637         24          16.1%             1.5%            <NA>             <NA>
638         24          14.6%             1.4%            6.1%             3.5%
639         24          17.2%             1.5%            <NA>             <NA>
640         24          16.6%             1.4%            4.2%             5.9%
641         24          16.7%             1.3%            5.3%             0.0%
642         24          15.4%             1.4%           10.2%             1.4%
643         24          15.1%             1.3%            <NA>             <NA>
644         24          16.4%             2.0%            5.4%             4.8%
645         24          16.3%             1.5%            7.2%             1.8%
646         24          16.4%             1.4%            7.0%             3.2%
647         24          16.5%             1.7%           12.9%             6.7%
648         24          16.6%             2.0%           10.5%             2.4%
649         24          19.4%             3.9%            4.9%            14.9%
650         24          18.1%             4.8%            3.5%            23.6%
651         24          19.3%             3.9%            2.1%            24.6%
652         24          17.8%             5.1%            0.3%            18.1%
653         24          19.7%             5.4%            0.0%            22.6%
654         24 Low Population          No Data Zero Population             0.0%
655         24          16.1%             1.7%            5.0%             2.0%
656         24          15.4%             1.7%            5.4%             8.3%
657         24          16.7%             1.7%           14.3%             4.6%
658         24          16.2%             1.7%           12.6%             0.0%
659         24          18.1%             2.4%            3.9%            11.5%
660         24          16.4%             1.5%            <NA>             <NA>
661         24          17.6%             1.8%            3.0%             2.7%
662         24          18.0%             2.0%            7.4%             3.2%
663         24          18.2%             1.9%            3.2%             8.0%
664         24          13.6%             1.4%            <NA>             <NA>
665         24          15.2%             1.7%           14.7%             2.3%
666         24          16.8%             1.7%           14.4%             3.2%
667         24          16.7%             2.1%           14.6%             2.9%
668         24          17.5%             1.9%           17.4%             0.9%
669         24          13.7%             1.4%            <NA>             <NA>
670         24          15.3%             1.6%            <NA>             <NA>
671         24          17.2%             2.5%            3.1%             6.3%
672         24          17.6%             1.8%            6.4%             3.7%
673         24          15.4%             1.4%            7.9%             0.6%
674         24          14.0%             1.5%           17.2%             1.3%
675         24          12.0%             1.3%            <NA>             <NA>
676         24          13.5%             1.5%            9.6%             4.2%
677         24          15.3%             1.5%           10.8%             0.4%
678         24          12.4%             1.4%           14.7%             0.0%
679         24          13.6%             1.5%           13.2%             3.1%
680         24          16.1%             1.8%           15.0%             8.4%
681         24          15.2%             1.3%            3.9%             2.2%
682         24          14.5%             1.4%            6.2%             0.5%
683         24          15.9%             2.0%            <NA>             <NA>
684         24          15.6%             1.5%           23.8%            10.0%
685         24          16.1%             1.7%           28.7%             3.8%
686         24          14.8%             1.8%           19.1%             1.9%
687         24          16.7%             2.6%           39.5%            14.2%
688         24          15.5%             2.1%           38.1%             1.7%
689         24          15.8%             1.6%            <NA>             <NA>
690         24          16.2%             2.0%            <NA>             <NA>
691         24          14.6%             1.2%           10.6%             1.2%
692         24          16.7%             2.0%            <NA>             <NA>
693         24          16.4%             1.9%           24.3%             4.5%
694         24          18.3%             2.4%           15.6%             7.1%
695         24          16.4%             2.2%            <NA>             <NA>
696         24          13.1%             1.6%           19.2%            16.2%
697         24          17.1%             2.5%           34.2%            20.7%
698         24          16.0%             2.1%           12.0%             2.6%
699         24          17.3%             2.5%           26.5%             2.5%
700         24          16.3%             1.9%           21.8%             7.2%
701         24          16.2%             2.4%           29.0%            15.7%
702         24          16.5%             1.9%           28.7%             4.5%
703         24          14.6%             1.8%            <NA>             <NA>
704         24          15.7%             1.2%            <NA>             <NA>
705         24          17.7%             2.4%           19.0%             6.5%
706         24          17.1%             1.8%           15.7%             0.2%
707         24          16.1%             1.6%           21.5%             2.2%
708         24          16.4%             1.6%           25.3%            10.2%
709         24          15.9%             1.5%           12.1%             0.8%
710         24          15.8%             1.4%           12.6%             2.1%
711         24          15.7%             1.3%            5.2%             4.9%
712         24          14.7%             1.4%            8.5%             1.3%
713         24          14.7%             1.3%           22.0%             0.4%
714         24          16.1%             2.0%           15.4%             7.0%
715         24          17.1%             2.5%           23.9%             6.8%
716         24          15.3%             2.2%           18.3%            10.1%
717         24          17.6%             2.4%           17.1%             4.2%
718         24          14.6%             1.5%           17.8%             4.8%
719         24          14.7%             1.5%           19.1%            10.5%
720         24          16.1%             2.1%           21.2%             3.7%
721         24          17.5%             2.0%           21.7%             4.8%
722         24          14.2%             1.8%           27.2%            10.0%
723         24          12.4%             1.6%           28.2%             3.5%
724         24          15.0%             1.6%           13.5%             4.1%
725         24          14.3%             1.2%            8.9%             1.3%
726         24          15.9%             1.5%            8.8%             0.4%
727         24          15.2%             1.4%            8.1%             3.0%
728         24          13.2%             1.4%           12.2%             1.5%
729         24          15.0%             1.2%           10.7%             2.3%
730         24          16.3%             1.6%           20.7%             9.2%
731         24          17.1%             2.0%           26.6%             7.3%
732         24          15.4%             1.9%           20.2%             1.3%
733         24          14.9%             1.1%            2.6%             2.1%
734         24          14.7%             1.2%            5.2%             2.0%
735         24          13.6%             1.2%            5.9%             2.4%
736         24          14.5%             1.2%           11.9%             3.0%
737         24          14.8%             1.5%           14.4%             1.8%
738         24          15.2%             1.5%           11.7%             3.8%
739         24          15.8%             1.0%            <NA>             <NA>
740         24          16.6%             0.9%            6.9%             0.8%
741         24          15.6%             1.2%            3.5%             2.9%
742         24          15.2%             0.9%           16.7%             1.3%
743         24          14.7%             1.2%           14.8%             9.1%
744         24          15.3%             1.7%           26.2%            13.2%
745         24          12.9%             1.2%           14.6%             1.0%
746         24          13.5%             1.2%           20.4%             4.9%
747         24          14.5%             1.4%            5.7%             2.2%
748         24          16.9%             1.6%            2.1%             3.5%
749         24          15.6%             1.5%            2.8%             2.0%
750         24          15.7%             1.6%           17.1%             2.6%
751         24          14.5%             1.6%           11.0%             4.6%
752         24          16.3%             1.5%            7.8%             1.5%
753         24          15.8%             1.4%            6.1%             1.6%
754         24          15.8%             1.6%            6.2%             0.6%
755         24          16.5%             1.6%           10.9%             6.1%
756         24          15.3%             1.6%           10.2%             5.7%
757         24          16.2%             1.6%            6.0%             3.7%
758         24          14.2%             1.7%            6.6%             2.1%
759         24          15.2%             2.0%           10.6%             2.6%
760         24          14.2%             1.7%           10.4%             2.9%
761         24          15.0%             1.7%            <NA>             <NA>
762         24          14.8%             1.7%           20.3%             3.6%
763         24          14.2%             2.1%            9.1%             1.5%
764         24          16.3%             2.0%           11.6%             1.1%
765         24          14.6%             1.5%           13.4%             1.8%
766         24          11.6%             1.4%            <NA>             <NA>
767         24          15.1%             2.2%            <NA>             <NA>
768         24          16.1%             2.5%           14.2%             1.8%
769         24          16.0%             1.9%           13.7%             7.9%
770         24          14.2%             2.0%           21.1%             9.3%
771         24          15.9%             1.9%           22.2%             7.8%
772         24          14.4%             1.6%           14.2%             1.3%
773         24          13.7%             1.8%           13.4%             4.0%
774         24          16.5%             2.4%            9.8%             4.7%
775         24          17.0%             2.8%           23.0%             5.5%
776         24          16.6%             1.7%           20.4%            11.1%
777         24          16.6%             2.4%           42.3%             7.8%
778         24          16.7%             1.0%            7.2%            10.2%
779         24          17.6%             1.4%           17.3%             9.8%
780         24          15.4%             1.2%           21.3%             0.7%
781         24          16.6%             1.1%           11.1%             6.1%
782         24          16.1%             1.2%           16.3%             8.0%
783         24          19.4%             1.8%           29.4%             5.0%
784         24          17.4%             2.6%           45.9%            15.9%
785         24          15.8%             2.2%           40.7%             8.6%
786         24          16.4%             1.3%           10.7%             6.0%
787         24          15.9%             1.3%           15.4%             0.5%
788         24          17.0%             2.0%           34.7%             7.5%
789         24          17.1%             1.6%            9.6%             8.5%
790         24          15.3%             1.4%            5.1%             1.2%
791         24          15.7%             1.6%            9.6%             0.6%
792         24          15.7%             1.1%            <NA>             <NA>
793         24          17.5%             1.1%            <NA>             <NA>
794         24          17.2%             1.3%           14.6%             1.3%
795         24          16.3%             1.4%           17.4%             9.0%
796         24          16.0%             1.3%            5.1%            12.2%
797         24          14.8%             1.3%            2.3%             5.6%
798         24          16.1%             1.5%            6.3%             2.6%
799         24          15.9%             1.9%           14.1%             2.9%
800         24          15.2%             1.8%           13.9%             4.9%
801         24          15.2%             1.5%           10.1%             5.1%
802         24          15.0%             1.8%           21.2%             3.9%
803         24          17.2%             2.3%           24.6%             4.0%
804         24          15.2%             1.9%            5.2%             3.5%
805         24          14.9%             1.7%           17.0%             3.8%
806         24          14.4%             2.0%           14.5%             3.5%
807         24          15.2%             1.7%            <NA>             <NA>
808         24          17.6%             2.7%           28.0%            11.2%
809         24          18.2%             2.2%           31.4%             9.6%
810         24          15.9%             1.8%           25.7%             9.2%
811         24          13.3%             2.7%           15.7%            15.2%
812         24          10.7%             1.9%            5.2%            14.9%
813         24          11.7%             1.6%            5.8%            10.4%
814         24          15.5%             2.4%           15.3%            13.5%
815         24          15.2%             2.0%            9.9%             2.4%
816         24          15.8%             2.1%           25.2%            10.0%
817         24          15.2%             1.9%           35.5%            13.4%
818         24          15.1%             2.5%           17.5%             9.2%
819         24          15.5%             2.3%           31.1%             3.1%
820         24          15.6%             2.2%           29.0%             6.4%
821         24          15.9%             2.7%           34.1%            12.7%
822         24          16.4%             2.8%           34.4%             7.3%
823         24          15.3%             1.7%           12.1%             6.5%
824         24          15.8%             1.5%           12.1%             8.5%
825         24          16.2%             1.4%            6.4%             1.4%
826         24          16.9%             2.6%           31.4%             8.2%
827         24          15.6%             2.1%           20.7%             5.3%
828         24          15.2%             1.8%            8.6%             5.6%
829         24          15.6%             1.5%            7.6%             5.3%
830         24          16.3%             1.9%           13.0%             5.7%
831         24          15.9%             1.8%           11.4%             7.7%
832         24          15.3%             1.3%            2.0%             2.9%
833         24          16.0%             1.3%            8.2%             3.4%
834         24          15.5%             1.2%            2.2%             1.3%
835         24          14.9%             1.1%            5.3%             0.0%
836         24          14.9%             0.9%           10.1%             4.5%
837         24          14.3%             1.1%            7.5%             4.7%
838         24          14.0%             1.2%            8.5%             1.4%
839         24          14.1%             1.1%            4.9%             2.4%
840         24          16.1%             1.1%            7.6%             0.5%
841         24          15.0%             1.0%            7.7%             1.1%
842         24          15.3%             1.0%            2.4%             0.6%
843         24          16.8%             1.2%            8.5%             4.5%
844         24          15.6%             0.7%            3.2%             0.7%
845         24          15.1%             0.9%           11.6%             4.2%
846         24          16.8%             1.0%            6.7%             2.3%
847         24          15.3%             1.1%            2.8%             7.0%
848         24          14.7%             1.0%            1.2%             3.6%
849         24          15.1%             1.0%            1.8%             2.6%
850         24          15.1%             1.0%            1.5%             2.9%
851         24          15.2%             1.0%            2.4%             0.0%
852         24          13.7%             0.8%            5.8%             3.2%
853         24          15.0%             1.0%            3.2%             3.0%
854         24          15.6%             1.0%            0.7%             2.9%
855         24          15.4%             0.9%            3.9%             8.0%
856         24          15.0%             1.1%            5.9%             4.2%
857         24          14.9%             1.1%            2.7%             1.3%
858         24          15.1%             1.1%            2.4%             2.6%
859         24          13.8%             1.1%            7.5%             3.1%
860         24          14.6%             1.1%            6.3%             2.3%
861         24          14.0%             1.0%            4.2%             0.0%
862         24          13.8%             1.1%           10.6%             1.6%
863         24          13.8%             1.1%           10.6%             0.0%
864         24          14.7%             1.2%            4.3%             0.4%
865         24          14.6%             1.1%            5.6%             0.5%
866         24          14.6%             1.3%           11.8%             4.9%
867         24          13.7%             1.1%            7.8%             1.1%
868         24          14.5%             1.3%           20.6%             7.2%
869         24          14.4%             1.1%            7.5%             1.3%
870         24          14.8%             2.0%            6.6%             6.6%
871         24          14.3%             1.7%           18.7%            16.7%
872         24          13.6%             2.1%           13.5%             2.6%
873         24          12.8%             2.1%            6.8%             1.3%
874         24          13.3%             1.8%           12.8%             3.0%
875         24          14.5%             2.0%           27.5%            10.6%
876         24          14.1%             1.8%           11.2%             5.1%
877         24          12.9%             1.9%            9.6%             6.7%
878         24          12.5%             1.6%            <NA>             <NA>
879         24          14.4%             2.0%           16.8%             8.5%
880         24          15.0%             1.8%            8.4%            10.6%
881         24          13.4%             1.7%            7.3%            14.6%
882         24          11.2%             1.7%           10.3%             4.9%
883         24          12.9%             1.7%           17.9%             3.8%
884         24          13.4%             1.5%            <NA>             <NA>
885         24          13.2%             1.7%            <NA>             <NA>
886         24          14.2%             1.8%            3.1%             1.9%
887         24          14.0%             2.0%            4.0%             2.2%
888         24          13.3%             1.8%            4.8%             1.3%
889         24          12.1%             1.8%            5.0%             0.4%
890         24          12.8%             1.8%            6.1%             2.4%
891         24          13.4%             1.8%            4.0%             1.1%
892         24          12.3%             1.6%            6.5%             0.8%
893         24          12.6%             2.2%           23.6%            10.9%
894         24          13.0%             1.7%           13.9%             5.6%
895         24          13.8%             1.8%            7.5%             3.9%
896         24          13.9%             1.7%            4.9%             2.4%
897         24          12.6%             1.7%            4.8%             1.5%
898         24          11.2%             2.0%            <NA>             <NA>
899         24          13.4%             1.9%            3.0%             3.8%
900         24          13.2%             1.8%            2.2%             0.6%
901         24          11.1%             1.5%            3.9%             0.0%
902         24          12.8%             1.8%            3.1%             3.5%
903         24          12.8%             1.9%            1.7%             5.1%
904         24          11.1%             1.7%            0.9%             3.0%
905         24          10.8%             1.5%            2.0%             4.1%
906         24          12.9%             1.8%            1.8%             0.0%
907         24          12.7%             1.9%            4.4%             9.2%
908         24          12.0%             2.4%            <NA>             <NA>
909         24          13.2%             2.4%            <NA>             <NA>
910         24          11.9%             2.1%            0.7%             5.1%
911         24          13.1%             2.2%            0.5%             4.6%
912         24          11.6%             1.9%            1.2%             1.7%
913         24          11.5%             1.5%            0.7%             1.2%
914         24          11.8%             1.9%            1.7%             0.0%
915         24          13.0%             2.4%            0.6%             4.3%
916         24          12.2%             2.1%            1.0%             1.4%
917         24          11.9%             2.1%            5.8%             1.4%
918         24          12.3%             2.4%            8.4%             5.8%
919         24          13.9%             2.6%            1.3%             4.3%
920         24          14.4%             3.7%            1.7%            18.0%
921         24          13.2%             2.3%            1.2%             9.4%
922         24          12.5%             2.3%            1.9%             4.2%
923         24          12.2%             2.0%            2.1%             0.8%
924         24          12.8%             2.3%           19.0%             1.8%
925         24          16.9%             2.2%            <NA>             <NA>
926         24          12.0%             2.5%            2.9%             2.9%
927         24          12.1%             2.1%            0.3%             4.8%
928         24          12.1%             2.2%            1.0%             2.5%
929         24          12.5%             2.8%            7.6%             3.8%
930         24          12.5%             2.5%            7.8%             2.7%
931         24          12.0%             2.6%            0.4%             7.0%
932         24          12.2%             2.3%            5.8%             8.3%
933         24          13.0%             2.8%            4.7%            19.1%
934         24          12.4%             2.3%            0.8%             0.9%
935         24          11.8%             2.4%            7.3%             6.4%
936         24          11.7%             2.2%            4.9%            11.1%
937         24          13.1%             2.1%            0.6%             6.5%
938         24          12.1%             2.1%           11.8%             3.2%
939         24          10.8%             2.1%            6.0%             2.3%
940         24          11.2%             2.1%            4.3%             5.8%
941         24          11.5%             2.1%            3.3%             4.0%
942         24          12.1%             1.8%            2.2%             6.7%
943         24          12.1%             2.1%            3.3%             1.3%
944         24          12.3%             2.5%           13.8%             5.0%
945         24          11.8%             2.3%            7.0%             5.7%
946         24          11.4%             2.0%           18.2%             6.4%
947         24          12.4%             2.9%           27.2%             8.1%
948         24          12.7%             2.2%            6.6%            11.7%
949         24          12.3%             2.5%           11.2%             4.1%
950         24          13.3%             2.4%            7.8%             8.1%
951         24          12.6%             2.6%           13.0%            10.9%
952         24          11.4%             2.5%           15.3%             2.4%
953         24          11.4%             2.4%            7.2%             7.0%
954         24          12.8%             3.0%           12.3%             5.9%
955         24          13.6%             3.5%            3.2%            13.7%
956         24          13.0%             2.8%            2.2%             4.9%
957         24          13.8%             2.3%            6.7%             5.6%
958         24          13.7%             2.7%            2.8%            15.6%
959         24          13.0%             2.4%            <NA>             <NA>
960         24          14.6%             3.6%           28.6%            13.8%
961         24          13.7%             2.7%            <NA>             <NA>
962         24          13.5%             2.9%            4.7%            11.9%
963         24          13.1%             3.5%            1.1%            11.9%
964         24          12.2%             3.1%            <NA>             <NA>
965         24          12.9%             2.5%            <NA>             <NA>
966         24          12.6%             2.6%            2.9%             5.8%
967         24          13.4%             2.7%            4.6%            11.8%
968         24          12.2%             3.0%            3.7%             9.2%
969         24          13.2%             3.3%            3.6%            12.8%
970         24          12.2%             2.3%            6.9%             7.8%
971         24          13.9%             3.3%           13.5%            26.0%
972         24          12.3%             3.2%            4.5%            14.4%
973         24          13.5%             2.1%            3.5%            13.2%
974         24          14.0%             2.4%           14.9%            12.8%
975         24          12.8%             2.7%            2.3%            12.6%
976         24          12.6%             2.3%            4.1%             9.1%
977         24          13.7%             3.0%            9.5%            16.8%
978         24          14.3%             3.1%            7.2%            10.1%
979         24          14.4%             2.6%            1.2%             8.7%
980         24          13.1%             3.1%            7.0%            12.9%
981         24          13.2%             3.2%            2.8%            16.1%
982         24          12.2%             2.6%            0.6%             8.4%
983         24          12.9%             3.1%            8.8%             6.0%
984         24          14.8%             3.3%            0.5%            14.5%
985         24          13.0%             2.8%            3.5%            20.4%
986         24          13.2%             2.8%            6.4%             8.7%
987         24          13.2%             2.3%            1.1%            16.8%
988         24          12.8%             2.4%           10.3%            17.6%
989         24          13.6%             3.4%            4.5%            21.7%
990         24          13.0%             3.7%            5.9%            12.5%
991         24          13.5%             4.1%            7.1%            15.9%
992         24          13.3%             3.9%            6.3%            20.2%
993         24          13.2%             2.3%            5.1%            13.3%
994         24          13.1%             3.0%            4.0%            11.5%
995         24          12.5%             2.8%            4.5%             6.2%
996         24          13.7%             3.8%            7.5%            16.3%
997         24          12.6%             3.1%            6.5%            13.6%
998         24          12.2%             2.7%            6.4%            22.8%
999         24          12.9%             3.9%            5.3%            14.7%
1000        24          13.8%             3.2%            8.6%             7.5%
1001        24          13.0%             3.0%            8.4%             4.3%
1002        24          13.9%             3.8%            <NA>             <NA>
1003        24          14.4%             3.5%            <NA>             <NA>
1004        24          14.2%             2.5%           13.3%            12.3%
1005        24          14.5%             2.8%           16.6%            12.0%
1006        24          12.3%             2.4%            5.4%             3.9%
1007        24          12.1%             2.7%            2.2%             9.2%
1008        24          12.0%             1.9%            0.0%            11.3%
1009        24          12.3%             1.7%            4.6%             2.6%
1010        24          12.1%             2.1%            2.2%             4.3%
1011        24          11.3%             1.9%            3.4%             0.2%
1012        24          10.7%             1.8%            6.1%             1.3%
1013        24          12.0%             2.2%            <NA>             <NA>
1014        24          11.3%             1.9%            <NA>             <NA>
1015        24          12.9%             2.4%            6.4%             7.3%
1016        24          13.5%             2.2%            6.7%             5.5%
1017        24          11.8%             2.2%            3.0%             4.6%
1018        24          12.1%             2.2%            5.1%             1.5%
1019        24          11.3%             2.2%           13.0%             0.6%
1020        24          12.5%             3.0%            5.4%             8.7%
1021        24          13.0%             2.4%           21.3%             6.5%
1022        24          13.2%             2.5%           26.4%             4.3%
1023        24          13.0%             2.2%           19.0%             6.2%
1024        24          12.6%             2.4%           18.9%            10.9%
1025        24          12.9%             2.6%           20.4%             4.6%
1026        24          14.6%             3.0%           18.4%            20.0%
1027        24          14.2%             2.5%           22.5%            10.5%
1028        24          14.1%             3.0%           24.3%             8.8%
1029        24          14.1%             3.0%           37.3%            14.1%
1030        24          14.0%             3.0%           28.9%            10.0%
1031        24          14.2%             2.9%           47.6%            15.8%
1032        24          14.5%             2.7%           16.8%            13.8%
1033        24          13.3%             2.9%           24.5%            14.7%
1034        24          14.0%             2.4%            7.2%             9.1%
1035        24          13.4%             2.4%           24.4%            11.6%
1036        24          12.2%             2.0%            2.9%             3.8%
1037        24          13.6%             3.1%           10.0%            24.6%
1038        24          13.3%             2.8%           24.0%            12.2%
1039        24          14.0%             2.6%           24.8%             8.9%
1040        24          13.4%             2.3%           11.9%             6.9%
1041        24          14.3%             2.3%           24.0%            12.3%
1042        24          13.9%             2.4%           48.4%            19.8%
1043        24          12.8%             2.2%           24.1%            15.1%
1044        24          12.8%             3.0%           22.1%            17.3%
1045        24          14.5%             2.5%           55.8%            13.3%
1046        24          13.9%             2.6%           43.3%            10.8%
1047        24          13.1%             2.5%           36.5%             5.3%
1048        24          14.7%             3.1%           50.0%            17.4%
1049        24          16.2%             2.4%           78.9%            19.4%
1050        24          15.4%             2.3%           74.6%             6.2%
1051        24          14.3%             3.1%           49.8%             6.6%
1052        24          13.6%             2.8%           37.0%             6.4%
1053        24          14.3%             3.0%           52.9%             6.6%
1054        24          12.4%             2.4%           31.3%             3.5%
1055        24          15.0%             2.1%           57.6%             8.1%
1056        24          14.7%             2.3%           44.8%            11.3%
1057        24          14.3%             2.0%           28.6%             6.3%
1058        24          13.3%             1.9%           17.9%             4.0%
1059        24          14.2%             2.5%           35.8%             7.1%
1060        24          14.2%             2.3%           18.3%             5.0%
1061        24          13.8%             2.0%            <NA>             <NA>
1062        24          14.0%             1.8%            <NA>             <NA>
1063        24          13.7%             1.6%            8.1%             1.5%
1064        24          14.8%             2.2%           32.2%            16.0%
1065        24          14.7%             2.9%           41.5%            22.1%
1066        24          15.0%             2.6%           38.6%            11.6%
1067        24          12.8%             2.5%           15.3%             7.8%
1068        24          13.2%             1.2%            3.9%             5.4%
1069        24          12.1%             1.6%            6.7%             4.5%
1070        24          13.3%             2.1%           16.1%             7.8%
1071        24          12.8%             1.2%            5.0%             3.8%
1072        24          14.2%             1.5%           27.2%             7.3%
1073        24          14.6%             1.6%           27.8%             9.7%
1074        24          13.9%             2.4%           22.3%             4.8%
1075        24          14.8%             2.1%           28.0%             5.0%
1076        24          15.6%             2.5%           18.5%             9.4%
1077        24          14.9%             2.2%           14.6%             9.0%
1078        24          20.6%             2.8%            <NA>             <NA>
1079        24          12.4%             2.2%           15.2%             4.8%
1080        24          12.9%             2.1%           26.9%             3.4%
1081        24          12.8%             2.3%           51.0%             3.0%
1082        24          13.6%             2.2%           30.4%             5.1%
1083        24          13.7%             2.0%           14.7%             8.2%
1084        24          11.8%             1.8%           14.2%             5.2%
1085        24          12.9%             1.5%            7.2%             3.0%
1086        24          13.4%             2.0%           22.7%             9.1%
1087        24          13.0%             2.4%           15.3%             9.0%
1088        24          18.2%             4.8%            1.4%            15.4%
1089        24          19.8%             4.1%            3.3%            20.0%
1090        24          18.3%             3.6%            0.9%            11.2%
1091        24          17.5%             3.0%            0.3%             4.1%
1092        24          17.9%             2.9%            0.9%            10.0%
1093        24          17.1%             2.8%            5.5%             6.2%
1094        24          17.5%             3.3%            1.7%             8.7%
1095        24          18.3%             2.6%            1.0%             5.0%
1096        24          17.3%             2.3%            3.0%             4.8%
1097        24          17.6%             2.8%            1.5%             4.0%
1098        24          18.3%             2.9%            0.0%             7.7%
1099        24 Low Population          No Data Zero Population             0.0%
1100        24 Low Population          No Data Zero Population             0.0%
1101        24 Low Population          No Data Zero Population             0.0%
1102        24          18.0%             2.7%            0.3%             3.8%
1103        24          16.7%             2.5%            0.8%            12.2%
1104        24          18.0%             2.7%            0.7%            10.3%
1105        24          18.4%             2.4%            1.3%            13.3%
1106        24          17.4%             3.7%            0.0%            22.8%
1107        24          16.6%             2.5%            1.6%            12.4%
1108        24          16.2%             2.1%            <NA>             <NA>
1109        24          16.9%             2.0%            <NA>             <NA>
1110        24          17.5%             2.6%            0.9%            12.0%
1111        24          18.6%             2.6%            <NA>             <NA>
1112        24          16.4%             2.4%            <NA>             <NA>
1113        24          16.8%             2.0%            <NA>             <NA>
1114        24          17.8%             2.6%            <NA>             <NA>
1115        24          17.8%             2.7%            2.3%            11.7%
1116        24          17.0%             2.5%            <NA>             <NA>
1117        24          16.9%             2.6%            <NA>             <NA>
1118        24          18.0%             3.0%            0.8%            12.1%
1119        24 Low Population          No Data Zero Population             0.0%
1120        24          21.1%             7.3%            1.9%            11.3%
1121        24          20.6%             5.9%            1.4%            16.9%
1122        24          20.4%             6.9%            0.3%            34.5%
1123        24          19.4%             6.4%            <NA>             <NA>
1124        24          20.3%             5.5%            0.9%            17.5%
1125        24          21.6%             6.6%            0.0%            22.9%
1126        24          14.5%             3.5%            <NA>             <NA>
1127        24 Low Population          No Data Zero Population             0.0%
1128        24          18.8%             3.1%            0.2%            10.8%
1129        24          15.8%             2.4%            1.7%             3.2%
1130        24          16.9%             3.1%            7.1%            17.0%
1131        24          17.8%             3.0%            8.5%            16.7%
1132        24          18.3%             2.6%            0.6%            11.0%
1133        24          17.7%             2.2%            2.2%            19.5%
1134        24          16.0%             3.3%            0.5%             5.3%
1135        24          16.5%             3.4%            1.1%             7.3%
1136        24          18.6%             4.4%            0.6%             7.7%
1137        24          17.2%             3.6%            2.3%             9.8%
1138        24 Low Population          No Data Zero Population             0.0%
1139        24          20.6%             2.6%            3.3%            13.0%
1140        24          19.6%             2.6%            2.1%             9.3%
1141        24          22.5%             3.6%            2.3%            19.3%
1142        24          24.7%             1.6%            2.5%            19.2%
1143        24          22.3%             2.0%            0.7%            24.9%
1144        24          23.4%             3.4%            4.4%            11.8%
1145        24          20.7%             3.2%            4.2%            16.6%
1146        24          20.4%             3.0%            1.9%            15.4%
1147        24          23.3%             1.5%            5.3%            37.1%
1148        24          23.2%             1.5%            1.7%            30.1%
1149        24          23.4%             3.6%           11.6%            18.6%
1150        24          20.8%             2.6%            0.6%            17.6%
1151        24          20.5%             2.7%            1.0%            12.5%
1152        24          22.4%             4.6%            0.5%             5.3%
1153        24          20.2%             2.6%            1.8%            16.3%
1154        24          18.4%             2.2%            3.3%            12.1%
1155        24          20.9%             3.0%            <NA>             <NA>
1156        24          21.9%             3.6%            <NA>             <NA>
1157        24          21.0%             3.6%            0.2%            18.4%
1158        24          21.3%             4.1%            0.8%            23.2%
1159        24          19.0%             2.7%            <NA>             <NA>
1160        24          20.5%             3.0%            0.2%            15.3%
1161        24          19.8%             2.9%            <NA>             <NA>
1162        24          14.2%          No Data            3.8%             0.0%
1163        24          19.9%             2.5%            1.5%            13.8%
1164        24          19.6%             2.1%            <NA>             <NA>
1165        24          20.5%             2.9%            2.6%            12.9%
1166        24          20.7%             2.7%            0.7%            11.7%
1167        24          19.3%             2.5%            3.0%            13.3%
1168        24          19.9%             2.8%            1.1%            14.1%
1169        24          19.9%             3.0%            <NA>             <NA>
1170        24          20.7%             3.3%            0.0%            10.3%
1171        24          20.5%             4.9%           14.8%            19.2%
1172        24          18.7%             3.1%            0.4%            12.4%
1173        24          19.2%             6.3%           23.6%            30.3%
1174        24          19.9%             4.1%            3.2%            11.3%
1175        24          21.9%             5.5%            2.2%            14.7%
1176        24          19.7%             3.8%            6.3%             6.6%
1177        24          19.8%             3.6%            2.8%            12.6%
1178        24          18.3%             5.1%            3.1%            24.5%
1179        24          18.2%             2.7%            7.8%             9.4%
1180        24          21.2%             3.7%            1.6%            14.4%
1181        24          19.7%             3.1%            6.9%            12.7%
1182        24          23.1%             3.1%            <NA>             <NA>
1183        24          20.6%             3.4%            8.2%             9.6%
1184        24          22.2%             6.0%            3.1%            15.0%
1185        24          18.8%             2.9%            1.2%             3.6%
1186        24          21.2%             4.3%            1.2%            14.9%
1187        24          20.3%             4.4%            1.3%            18.0%
1188        24          20.7%             3.9%            <NA>             <NA>
1189        24          18.7%             4.0%            2.1%            17.5%
1190        24          19.6%             5.4%            2.9%             9.4%
1191        24          17.5%             4.1%            3.1%             8.4%
1192        24          18.6%             6.7%            4.7%            12.2%
1193        24          19.1%             3.6%            3.0%             4.6%
1194        24          17.5%             3.8%            1.6%             2.7%
1195        24          18.1%             5.5%            2.5%             4.6%
1196        24          19.3%             4.1%            1.4%            14.0%
1197        24          19.5%             4.4%            1.6%            11.3%
1198        24          18.5%             4.5%            1.5%             8.1%
1199        24          17.8%             4.0%            <NA>             <NA>
1200        24          19.5%             3.8%            0.6%            14.0%
1201        24          19.2%             5.9%            5.0%            23.5%
1202        24          19.7%             3.6%            0.2%            32.5%
1203        24          19.7%             6.3%            1.2%            16.8%
1204        24          19.3%             5.1%            3.1%             8.2%
1205        24 Low Population          No Data Zero Population             0.0%
1206        24 Low Population          No Data Zero Population             0.0%
1207        24          21.9%             1.6%            0.6%             4.8%
1208        24          20.6%             1.7%            1.8%             9.2%
1209        24          21.8%             1.5%            7.0%             6.4%
1210        24          21.2%             1.4%            4.6%             4.1%
1211        24          22.0%             1.8%            7.2%             4.9%
1212        24          22.0%             2.1%            4.0%             3.6%
1213        24          19.2%             1.8%            8.0%             6.7%
1214        24          21.1%             1.1%            2.7%             5.6%
1215        24          24.0%             5.1%            3.0%            17.1%
1216        24          21.1%             1.3%            7.6%             7.1%
1217        24          19.3%             1.4%            7.8%             2.9%
1218        24          22.4%             2.6%            5.4%            15.5%
1219        24          21.9%             3.2%            8.6%            24.3%
1220        24          22.4%             2.8%            4.5%            13.8%
1221        24          21.4%             2.5%            2.8%            11.2%
1222        24          18.0%             1.8%            3.1%            19.5%
1223        24          23.1%             5.5%            3.8%            23.0%
1224        24          22.7%             5.1%            9.5%            10.9%
1225        24          20.9%             6.1%            4.2%            19.5%
1226        24          20.6%             3.5%            7.1%            27.9%
1227        24          20.0%             3.0%            2.6%            12.8%
1228        24          22.5%             5.8%            0.2%            27.9%
1229        24          19.9%             5.9%            0.0%            46.2%
1230        24          20.9%             6.2%            3.9%            25.6%
1231        24          18.6%             4.4%            2.7%            29.1%
1232        24          22.1%             6.3%            0.0%            18.0%
1233        24          21.1%             6.4%            2.0%            10.8%
1234        24          19.9%             6.5%            1.2%            25.1%
1235        24          17.8%             7.3%            2.4%            12.7%
1236        24          21.7%             5.1%            0.1%             8.6%
1237        24          20.4%             3.7%            3.9%            12.7%
1238        24          17.9%             2.9%            2.1%            14.8%
1239        24          20.4%             3.5%            2.2%            17.3%
1240        24          22.6%             5.9%            5.4%            27.7%
1241        24          20.8%             4.0%            1.2%            20.2%
1242        24          21.3%             5.2%            0.0%            21.7%
1243        24          20.2%             6.3%            0.0%            25.5%
1244        24          21.8%             6.5%            1.2%            33.3%
1245        24          21.1%             5.8%            0.6%            34.6%
1246        24          21.3%             5.7%            5.6%            30.3%
1247        24          24.4%             6.6%            2.4%            31.1%
1248        24          19.3%          No Data            3.6%             0.0%
1249        24          20.7%             1.6%            1.5%             1.6%
1250        24          21.1%             1.5%            0.9%            11.3%
1251        24          19.1%             1.2%            8.0%             4.6%
1252        24          21.1%             2.0%            1.7%             1.1%
1253        24          22.4%             2.2%            4.3%             1.9%
1254        24          20.5%             2.8%            1.6%            12.0%
1255        24          20.8%             4.4%            0.0%            15.0%
1256        24          20.3%             2.3%            1.0%             9.2%
1257        24          20.2%             3.2%            2.5%            21.4%
1258        24          21.5%             3.1%            2.2%             8.5%
1259        24          20.3%             3.1%            0.6%            20.8%
1260        24          21.0%             3.3%            2.5%            18.7%
1261        24          20.0%             4.7%            4.6%            25.0%
1262        24          20.6%             5.3%            2.7%            27.0%
1263        24          22.5%             2.0%            2.7%             2.2%
1264        24          19.6%             1.9%            3.1%            10.9%
1265        24          22.3%             2.8%            5.3%            17.8%
1266        24          24.0%             2.7%            2.6%             9.7%
1267        24          18.0%             2.8%            1.4%            24.5%
1268        24          21.0%             2.2%            1.1%             2.1%
1269        24          22.0%             1.9%            5.0%            14.3%
1270        24          24.1%             6.3%            6.1%            17.4%
1271        24          20.1%             4.6%            0.8%            15.0%
1272        24          23.1%             8.9%            0.0%            35.2%
1273        24          22.3%             7.2%            0.0%            43.7%
1274        24          20.1%             5.4%            5.4%            30.1%
1275        24          21.9%             6.5%            1.3%            38.6%
1276        24          20.6%             5.3%            0.3%            35.1%
1277        24          20.7%             6.1%            0.0%            38.9%
1278        24          18.6%             4.8%            1.8%            17.5%
1279        24          18.5%             4.5%            0.0%            33.2%
1280        24          19.7%             4.3%            0.0%            42.9%
1281        24          18.0%             4.2%            0.0%            26.2%
1282        24          19.3%             4.9%            2.0%            25.5%
1283        24          18.6%             4.2%            2.4%            19.9%
1284        24          20.6%             6.9%            0.9%            39.7%
1285        24          21.7%             6.9%            4.3%            18.4%
1286        24          20.7%             6.2%            4.9%            34.5%
1287        24          22.7%             5.8%            3.1%            26.8%
1288        24          21.3%             7.9%            1.3%            57.0%
1289        24          22.1%            11.0%            1.4%            44.2%
1290        24          20.9%             6.0%            0.0%            50.7%
1291        24          19.4%             5.6%            0.3%            35.2%
1292        24          20.9%             6.6%            0.4%            30.3%
1293        24          18.9%             4.3%            1.0%            21.7%
1294        24          19.2%             4.3%            0.0%            25.8%
1295        24          21.9%             2.8%            0.7%            10.0%
1296        24          23.8%             6.7%            0.4%            27.4%
1297        24          21.4%             4.4%            1.7%            27.4%
1298        24          25.3%             7.1%            <NA>             <NA>
1299        24          20.4%             3.9%            <NA>             <NA>
1300        24          21.5%             3.4%            1.7%            14.2%
1301        24          23.4%             6.4%            7.5%            21.6%
1302        24          22.0%             5.5%            0.9%            16.1%
1303        24          25.5%             7.4%            4.6%            42.6%
1304        24          22.1%             7.8%            0.0%            16.0%
1305        24          20.1%             7.1%            0.0%            36.8%
1306        24          25.5%             8.8%            1.9%            33.3%
1307        24          22.5%             8.5%            0.3%            35.4%
1308        24          25.0%             5.4%           15.6%            23.2%
1309        24          21.7%             5.8%            0.9%            12.4%
1310        24          19.6%             4.9%            0.5%            35.4%
1311        24          19.6%             6.5%            0.0%            30.9%
1312        24          21.1%             5.2%            1.4%            21.1%
1313        24          21.7%             3.1%            1.8%             7.4%
1314        24          23.8%             3.1%            9.0%             9.8%
1315        24          20.5%             1.3%            2.5%            14.2%
1316        24          22.8%             2.0%            2.0%             7.2%
1317        24          22.9%             1.7%            0.5%             6.9%
1318        24          21.9%             1.3%            0.6%             4.4%
1319        24          21.4%             1.2%            0.9%             2.7%
1320        24          20.4%             1.1%            1.8%             2.7%
1321        24          21.8%             1.3%            0.0%             1.3%
1322        24          22.3%             1.7%            0.3%             3.9%
1323        24          20.0%             3.0%            0.7%            12.3%
1324        24          20.6%             3.9%            4.5%            10.2%
1325        24          23.1%             3.7%            2.4%            34.0%
1326        24          21.0%             4.4%            0.0%            15.7%
1327        24          25.7%             6.9%            0.0%            40.5%
1328        24          22.4%             4.5%           15.9%            20.8%
1329        24          24.2%             3.7%            5.2%            16.5%
1330        24          21.8%             4.0%           13.3%            24.6%
1331        24          23.3%             5.7%            3.2%            23.0%
1332        24          26.2%             4.3%            5.5%            24.9%
1333        24          24.9%             4.2%           12.4%            23.9%
1334        24          24.7%             4.3%            4.5%            24.5%
1335        24          26.6%             5.7%            2.1%            39.0%
1336        24 Low Population          No Data Zero Population             0.0%
1337        24          20.7%             3.0%            1.9%             8.1%
1338        24          19.8%             3.9%            2.2%            13.5%
1339        24          20.3%             3.7%            9.6%            13.2%
1340        24          20.1%             4.4%           13.5%            16.5%
1341        24          21.1%             3.2%            3.6%            17.6%
1342        24          21.4%             5.1%            0.0%            15.8%
1343        24          21.6%             5.8%            1.4%            15.1%
1344        24          25.5%             3.6%            3.8%            14.7%
1345        24          26.3%             4.4%           22.3%            35.9%
1346        24          21.8%             3.8%            4.2%            17.2%
1347        24          21.1%             3.4%            0.0%            21.0%
1348        24          24.0%             4.4%           28.2%            14.5%
1349        24          23.0%             3.3%           24.4%            19.2%
1350        24          26.5%             6.7%            3.3%            16.3%
1351        24          26.0%             3.2%            9.2%            16.4%
1352        24          21.9%             2.4%           25.7%             9.2%
1353        24          23.1%             2.9%           22.7%            25.6%
1354        24          21.6%             1.3%            0.6%             5.5%
1355        24          23.7%             3.6%           12.2%            12.5%
1356        24          21.8%             1.6%            0.0%             4.8%
1357        24          21.1%             2.9%            0.0%            10.6%
1358        24          21.2%             3.7%            2.2%             8.2%
1359        24          20.5%             2.8%            2.8%             2.0%
1360        24          19.4%             3.0%            4.4%             4.2%
1361        24          21.6%             3.1%            1.7%             4.4%
1362        24          20.6%             3.2%            0.6%             8.4%
1363        24          20.8%             3.5%            0.8%             6.7%
1364        24          21.8%             2.9%            2.1%             9.9%
1365        24          20.4%             2.9%            0.4%             8.2%
1366        24          20.1%             3.2%            1.2%             6.4%
1367        24          21.2%             2.8%            5.8%            16.8%
1368        24          21.0%             3.3%            4.3%            11.0%
1369        24          21.3%             3.0%            3.9%             9.9%
1370        24          19.4%             3.5%            2.3%             9.1%
1371        24          19.7%             3.7%            1.8%            14.4%
1372        24          18.5%             2.7%            5.7%            18.2%
1373        24          21.8%             2.3%           12.2%            14.4%
1374        24          18.9%             3.6%            1.6%             2.3%
1375        24          18.4%             3.5%            0.2%            14.0%
1376        24          19.4%             3.6%            0.2%            14.7%
1377        24          20.2%             3.6%            2.9%            17.8%
1378        24          20.2%             4.3%            7.6%            15.6%
1379        24          20.7%             4.6%            3.2%            19.5%
1380        24          21.8%             2.1%            4.7%            20.1%
1381        24          26.3%             1.5%            2.9%             3.4%
1382        24          19.8%             1.6%            1.0%             2.9%
1383        24          18.0%             1.4%            2.9%             0.9%
1384        24          19.1%             1.4%            3.4%             2.8%
1385        24          20.0%             1.8%            1.2%             3.3%
1386        24          17.7%             0.8%            4.8%             9.1%
1387        24          20.6%             5.4%            1.7%            23.8%
1388        24          18.6%             5.0%            0.9%            30.5%
1389        24          20.6%             4.9%            3.1%            34.8%
1390        24          21.0%             8.1%            0.3%            33.6%
1391        24          19.1%             3.0%            2.4%            16.0%
1392        24          20.7%             2.5%            2.6%            13.6%
1393        24          20.5%             2.0%            3.3%            10.5%
1394        24          21.3%             2.1%            3.0%            13.2%
1395        24          20.5%             3.4%            7.7%            39.6%
1396        24          20.7%             3.5%            7.3%            15.5%
1397        24          20.4%             3.9%            1.0%            18.2%
1398        24          18.0%             4.1%            1.2%            30.5%
1399        24          17.8%             3.9%            0.4%            17.1%
1400        24          20.5%             3.5%            1.9%            26.7%
1401        24          19.6%             3.6%            0.8%            33.1%
1402        24          19.0%             3.1%            0.0%            13.2%
1403        24          17.6%             4.4%            0.0%            20.4%
1404        24          20.9%             2.6%            0.0%            18.8%
1405        24          20.4%             3.2%            1.7%            20.2%
1406        24          24.3%             6.6%            1.3%            26.2%
          badmental percentunemployed
1             15.6%              2.5%
2             14.2%              3.4%
3             14.9%              <NA>
4             15.5%              <NA>
5             17.4%              9.5%
6             15.0%              5.3%
7             17.3%              7.2%
8             18.7%             10.3%
9             16.7%             12.9%
10            15.4%              6.7%
11            13.6%              3.0%
12            14.9%              6.9%
13            12.5%              2.6%
14            14.4%              2.8%
15            16.0%              8.3%
16            15.8%             15.2%
17            14.0%              5.4%
18            16.0%              9.3%
19            19.9%             10.2%
20            14.7%              8.1%
21            14.9%              7.1%
22            15.9%             10.3%
23            15.5%              9.0%
24            11.7%              4.2%
25            14.1%              <NA>
26            13.2%              <NA>
27            12.4%              <NA>
28            12.7%              7.3%
29            12.6%              4.9%
30            11.9%              4.3%
31            12.3%              4.5%
32            12.9%              2.4%
33            12.7%              6.9%
34            12.6%              1.9%
35            11.9%              3.4%
36            11.2%              5.2%
37            14.8%              3.2%
38            11.8%              4.3%
39            10.8%              2.3%
40            12.5%              <NA>
41            10.2%              1.8%
42            13.4%              <NA>
43            12.6%              <NA>
44            11.0%              5.4%
45            15.6%              <NA>
46            14.7%              3.5%
47            13.5%              0.5%
48            12.6%              3.7%
49            17.6%              0.3%
50            13.2%              3.0%
51            13.0%              6.2%
52            12.8%              2.5%
53            14.2%              5.3%
54            14.0%              <NA>
55            15.5%              <NA>
56            15.8%              4.4%
57            14.5%              6.4%
58            15.0%              5.7%
59            15.0%              <NA>
60            14.0%              <NA>
61            13.8%              <NA>
62            16.1%              <NA>
63            16.3%              <NA>
64            10.9%              2.6%
65            12.7%              3.0%
66            11.1%              <NA>
67            11.3%              <NA>
68            10.5%              5.3%
69            10.8%              2.0%
70            10.7%              2.7%
71            12.4%              1.8%
72            12.7%              2.7%
73            12.7%              8.4%
74            11.8%              <NA>
75            12.8%              4.7%
76            13.5%              3.1%
77            12.0%              3.4%
78            11.3%              3.1%
79            13.2%              <NA>
80            12.2%              <NA>
81            13.9%              <NA>
82            12.9%              8.3%
83            13.5%              3.6%
84            15.2%              4.3%
85            14.0%              3.5%
86            15.2%              6.2%
87            15.3%              2.1%
88            14.9%              <NA>
89            12.4%              <NA>
90            12.4%              4.0%
91            13.7%              4.9%
92            16.6%              5.0%
93            14.7%              <NA>
94            13.2%              3.7%
95            13.4%              6.0%
96            13.1%              1.0%
97            15.1%              2.8%
98            15.3%   Zero Population
99            12.8%              <NA>
100           15.8%              2.9%
101           17.0%              5.6%
102           16.2%              4.0%
103           12.4%              1.2%
104           12.5%              <NA>
105           12.2%              3.7%
106           14.2%              6.0%
107           13.1%              3.2%
108           16.3%              8.5%
109           16.6%              4.2%
110           15.3%              8.8%
111           15.1%              <NA>
112           15.0%              <NA>
113           13.8%              4.6%
114           12.0%              4.1%
115           14.0%              1.6%
116           16.9%             10.3%
117           14.9%              1.0%
118           14.5%              5.5%
119           15.2%              8.4%
120           14.8%              2.7%
121           14.6%              2.2%
122           12.6%              3.4%
123           12.3%              1.5%
124           15.6%              5.5%
125            9.6%              1.4%
126           11.6%              5.0%
127  Low Population   Zero Population
128  Low Population   Zero Population
129           10.2%              0.0%
130           14.9%              2.5%
131           12.1%              2.0%
132           11.2%              5.3%
133           13.8%              2.3%
134           14.5%              2.8%
135           13.6%              0.7%
136           14.8%              7.1%
137           13.2%              3.0%
138           12.0%              4.1%
139           15.6%              4.6%
140           14.8%              9.9%
141           15.4%              8.0%
142           15.9%             10.3%
143           14.9%              5.5%
144           12.2%              3.5%
145           12.6%              4.7%
146           12.7%              6.5%
147           13.7%              5.0%
148           14.7%              2.8%
149           15.4%              4.7%
150           14.2%              5.1%
151           12.7%              3.4%
152           14.4%             12.2%
153           15.0%              5.4%
154           14.1%              3.5%
155           15.1%             11.4%
156           15.5%              6.6%
157           15.8%              5.3%
158           14.0%              6.4%
159           16.2%              4.0%
160           16.3%              6.2%
161           17.0%              <NA>
162           15.3%              6.1%
163           15.5%              7.7%
164           13.9%              5.0%
165           15.3%              1.6%
166           13.7%              4.9%
167           13.3%              <NA>
168           14.6%              6.3%
169           12.6%              4.2%
170           13.9%              8.5%
171           12.4%              5.2%
172           13.8%              2.4%
173           13.4%             10.6%
174           13.0%              2.6%
175           11.4%              2.3%
176           13.1%              7.0%
177           11.3%              7.7%
178           12.4%              1.9%
179           12.8%              5.7%
180           11.6%              <NA>
181           14.2%              5.2%
182           10.4%              2.4%
183           10.2%              3.1%
184            9.9%              1.9%
185           13.6%              3.2%
186           14.4%              9.0%
187           15.4%             14.1%
188           18.7%              7.6%
189           13.0%              5.3%
190           15.2%              8.2%
191           13.4%              3.3%
192           14.7%              8.9%
193           16.7%             10.0%
194           13.1%              2.4%
195           12.7%              4.6%
196           11.7%              7.0%
197           12.9%              2.7%
198           13.1%              3.1%
199           12.9%              2.7%
200           13.5%              4.4%
201           11.7%              6.3%
202           11.5%              1.8%
203           10.3%              5.4%
204           10.9%              0.9%
205           10.0%              0.0%
206           11.2%              0.5%
207           10.3%              2.0%
208           13.6%              4.8%
209           11.7%              6.7%
210           15.8%              5.7%
211           16.3%              2.4%
212           11.5%              3.4%
213           10.8%              2.3%
214           10.8%              3.0%
215           11.4%              1.3%
216           11.1%              3.0%
217           12.5%              4.6%
218           11.9%              2.3%
219           11.6%              2.1%
220           11.3%              4.8%
221           12.8%              2.8%
222           12.6%              2.7%
223           12.1%              0.4%
224           11.4%              0.8%
225           14.1%              5.8%
226           13.8%              3.4%
227           14.0%              2.3%
228           14.8%              3.2%
229           12.7%              4.0%
230           12.9%              4.6%
231           13.4%              4.2%
232           13.1%              2.1%
233           11.9%              <NA>
234           16.7%              1.9%
235           13.9%              4.6%
236           13.9%              2.8%
237           15.0%              4.7%
238           14.8%              6.8%
239           17.7%              6.7%
240           17.6%              4.2%
241           15.4%             10.5%
242           17.3%             14.3%
243           16.1%              6.2%
244           16.5%              3.4%
245           17.3%              6.0%
246           17.2%              1.5%
247           16.1%              3.0%
248           16.8%              7.7%
249           17.2%             11.4%
250           18.0%              5.4%
251           17.2%              4.3%
252           15.9%              6.1%
253           16.8%              6.8%
254           17.4%              <NA>
255           18.6%              5.9%
256           16.1%              2.7%
257           16.7%             10.1%
258           19.2%              5.5%
259           15.4%              4.9%
260           13.3%              3.7%
261           15.3%              5.7%
262           14.6%              5.8%
263           16.6%              7.4%
264           14.4%              6.3%
265           14.2%              6.3%
266           15.5%              4.2%
267           14.9%              7.6%
268           14.0%              3.2%
269           13.0%              3.5%
270           15.8%              4.3%
271           14.3%              2.6%
272           14.9%             11.8%
273           14.8%              6.1%
274           15.5%              7.0%
275           14.3%              3.5%
276           14.2%              4.3%
277           15.2%             12.9%
278           15.5%              6.1%
279           15.2%              5.0%
280           15.8%              6.9%
281           16.4%              9.1%
282           18.7%              9.9%
283           18.3%              5.7%
284           17.0%              5.3%
285           14.5%              5.7%
286           13.8%              3.7%
287           16.3%             11.6%
288           15.9%              3.2%
289           17.1%              1.5%
290           16.0%              6.2%
291           17.3%              8.0%
292           17.7%              5.9%
293           14.5%              3.1%
294           13.4%              2.6%
295           14.2%              7.3%
296           16.2%              3.6%
297           14.2%              1.8%
298           16.1%              2.1%
299           14.6%              3.8%
300           15.1%              7.0%
301           15.0%              8.9%
302           18.9%              5.1%
303           15.2%              6.2%
304           17.4%              5.7%
305           10.2%              1.8%
306           11.6%              6.0%
307           16.8%              <NA>
308           14.4%              4.4%
309           10.0%              1.8%
310           10.3%              3.1%
311           12.0%              1.0%
312           12.8%              2.8%
313           10.8%              1.9%
314           30.4%             11.5%
315            8.2%              0.0%
316           11.3%              1.7%
317           13.5%              2.6%
318           13.9%              2.9%
319           11.0%              1.8%
320           13.3%              6.1%
321           13.2%              5.6%
322           14.1%              4.5%
323           15.0%              6.2%
324           17.5%              6.7%
325           15.4%             11.1%
326           15.1%              3.0%
327           16.2%              4.8%
328           13.5%              4.6%
329           12.8%              4.4%
330           14.7%              7.9%
331           14.2%              4.1%
332           14.4%              7.5%
333           14.6%              2.4%
334           14.6%              1.8%
335           17.8%              4.4%
336           14.3%              3.9%
337           13.7%              3.3%
338           24.9%              2.5%
339           15.3%              3.7%
340  Low Population              <NA>
341  Low Population   Zero Population
342  Low Population   Zero Population
343           12.5%              <NA>
344           12.9%              <NA>
345           12.7%              5.1%
346           13.2%              3.1%
347           14.6%              <NA>
348           13.9%              3.2%
349           13.7%              2.0%
350           13.9%              2.1%
351           13.0%              6.5%
352           13.9%              6.5%
353           14.9%              2.9%
354           14.6%              2.9%
355           13.5%              1.8%
356           14.4%              <NA>
357           13.0%              <NA>
358           12.6%              <NA>
359           14.8%              4.1%
360           15.4%              5.0%
361  Low Population   Zero Population
362           18.0%              4.9%
363           17.0%              4.4%
364           16.8%              5.4%
365           14.8%              6.6%
366           15.0%              7.3%
367           16.7%              4.8%
368           14.5%              1.9%
369           14.9%              4.3%
370           17.8%              3.9%
371           15.5%              5.1%
372           14.0%              4.5%
373           13.6%              4.6%
374           13.7%              2.5%
375           12.6%              3.9%
376           12.1%              2.8%
377           12.4%              2.0%
378           12.6%              2.6%
379           12.3%              5.2%
380           13.6%              2.5%
381           13.0%              1.6%
382           11.6%              1.5%
383           13.2%              0.9%
384           12.0%              2.1%
385           13.3%              4.9%
386           13.4%              3.2%
387           14.0%              2.3%
388           15.2%              3.3%
389           14.2%              2.6%
390           14.0%              1.9%
391           13.3%              1.9%
392           11.4%              7.3%
393           14.3%              2.6%
394           14.9%              6.2%
395           12.7%              2.4%
396           13.1%              <NA>
397           14.6%              <NA>
398           13.3%              6.0%
399           13.3%              2.5%
400           13.0%              4.7%
401           14.5%              2.3%
402           14.0%              5.0%
403           14.5%              0.9%
404           12.7%              3.3%
405           12.9%              2.5%
406           12.6%              3.1%
407           13.2%              3.5%
408           12.7%              2.6%
409           13.7%              4.2%
410           14.1%              5.1%
411           18.3%             16.3%
412           14.9%              4.4%
413           16.7%              4.3%
414           14.5%              6.2%
415           16.6%              <NA>
416           13.7%              5.7%
417           14.4%              3.7%
418           13.8%              6.7%
419           17.5%              7.0%
420           13.8%              1.2%
421           16.2%              6.3%
422           15.7%              <NA>
423           15.2%              5.2%
424           13.7%              2.5%
425           14.8%              6.0%
426           15.4%              9.3%
427           14.9%              3.4%
428           13.5%             10.4%
429           14.2%              4.3%
430           16.1%              1.4%
431           15.5%              4.1%
432           13.8%              5.5%
433           14.9%              6.5%
434           13.8%              1.5%
435           13.0%              2.6%
436           13.0%              3.0%
437           13.6%              7.9%
438           14.8%              4.7%
439           13.4%              4.7%
440           14.9%              2.6%
441           13.5%              3.4%
442           13.5%              4.4%
443           13.9%              2.3%
444           14.2%              3.4%
445           16.6%              9.8%
446           14.4%              4.2%
447           13.7%              4.2%
448           15.1%              9.8%
449           14.9%              4.0%
450           12.5%              4.6%
451           13.8%              <NA>
452           14.1%              4.5%
453           14.6%              1.6%
454           14.4%              1.3%
455           13.4%              1.4%
456           13.1%              <NA>
457           14.3%              <NA>
458  Low Population   Zero Population
459           14.6%              5.7%
460           15.6%              6.1%
461           13.7%              6.6%
462           14.4%              7.0%
463           17.1%             19.3%
464           16.3%              6.8%
465           12.6%              7.1%
466           12.4%              4.5%
467           14.0%              2.2%
468  Low Population   Zero Population
469           14.1%              2.9%
470           14.4%              5.2%
471           13.2%              1.9%
472           15.8%              4.8%
473           16.5%              <NA>
474           15.0%              4.7%
475           17.2%              6.3%
476           13.3%              5.5%
477           13.5%              4.0%
478           14.7%              6.4%
479           15.2%              3.7%
480           14.4%              1.7%
481           12.0%              5.2%
482           13.0%              <NA>
483           14.8%              6.6%
484           13.7%              5.2%
485           14.6%              3.9%
486           13.8%              1.8%
487           12.2%              3.3%
488           12.3%              2.6%
489           11.7%              7.1%
490           11.8%              1.8%
491           13.5%              1.2%
492           14.3%              4.6%
493           13.3%              0.4%
494           14.0%              4.4%
495           13.1%              3.2%
496           13.1%              5.9%
497           13.1%              <NA>
498           12.3%              4.1%
499           12.3%              1.5%
500           12.4%              5.7%
501           13.9%              4.0%
502           12.5%              5.9%
503           12.8%              2.4%
504           12.5%              2.8%
505           12.2%              3.0%
506           12.0%              <NA>
507           14.1%              4.5%
508           12.0%              5.5%
509           13.4%              4.3%
510           13.2%              6.9%
511           13.1%              1.3%
512           12.4%              3.5%
513           11.9%              2.5%
514           12.1%              3.8%
515           13.3%              2.4%
516           13.1%              5.2%
517           14.6%              1.4%
518           14.2%              5.8%
519           15.0%              2.1%
520           14.2%              2.9%
521           16.8%              5.5%
522           14.5%              3.6%
523           14.0%              3.7%
524           13.1%              3.3%
525           15.3%              4.0%
526           14.7%              5.3%
527           13.5%              4.7%
528           15.6%              8.9%
529           12.8%              3.0%
530           14.6%              3.2%
531           16.1%              4.2%
532           14.8%              7.4%
533           15.4%              6.3%
534           13.4%              <NA>
535           15.0%              <NA>
536           15.6%              4.6%
537           12.2%              1.6%
538           14.4%              2.0%
539           12.4%              2.5%
540           15.0%              2.8%
541           12.9%              2.9%
542           12.8%              1.3%
543           13.6%              6.4%
544           14.7%              1.7%
545           14.2%              1.8%
546           13.8%              4.7%
547           16.6%              5.2%
548           13.5%              7.1%
549           13.7%              1.3%
550           16.9%              7.2%
551           14.8%              7.3%
552           14.4%              <NA>
553           13.8%              4.1%
554           15.0%              2.4%
555           12.1%              3.7%
556           13.0%              5.8%
557           15.2%             10.3%
558           13.5%              3.8%
559           15.0%              1.8%
560           20.1%              6.5%
561           15.4%              1.6%
562           13.1%              1.6%
563           11.5%              1.4%
564           13.1%              4.4%
565           12.7%              3.3%
566           12.8%              4.8%
567           12.4%              5.5%
568           12.7%              3.6%
569           12.2%              2.3%
570           12.0%              2.9%
571           11.9%              5.3%
572           13.0%              3.1%
573           11.5%              2.8%
574           13.3%              2.2%
575           13.7%              9.2%
576           12.4%              1.1%
577           12.9%              5.6%
578           13.1%              7.6%
579           13.6%              2.8%
580           13.5%              1.5%
581           12.2%              4.7%
582           12.9%              4.6%
583           13.4%              4.3%
584           11.8%              1.7%
585           12.9%              6.7%
586           14.7%              2.1%
587           15.8%              4.4%
588           13.3%              5.4%
589           15.1%              6.6%
590           13.8%              8.3%
591           12.4%              4.4%
592           12.8%              5.6%
593           16.1%              2.0%
594           11.1%              1.0%
595           10.8%              4.1%
596           11.7%              1.8%
597           14.9%              3.7%
598           11.9%              2.6%
599           13.2%              <NA>
600           12.3%              3.2%
601           14.0%              6.5%
602           10.1%              0.0%
603           10.5%              6.1%
604           10.5%              3.7%
605           12.0%              1.1%
606            9.4%              2.8%
607            9.8%              2.1%
608           10.3%              2.1%
609           10.5%              3.7%
610           11.1%              5.2%
611           10.0%              2.7%
612           11.8%              4.6%
613           11.1%              0.4%
614           10.1%              1.7%
615           10.7%              7.8%
616           10.4%              2.1%
617           11.9%              2.3%
618           11.3%              <NA>
619           10.1%              <NA>
620           10.0%              3.7%
621           10.3%              4.8%
622           12.1%              3.2%
623           11.6%              <NA>
624           10.7%              2.5%
625           13.4%              6.4%
626            9.9%              1.9%
627           10.0%              1.2%
628           12.0%              5.3%
629           11.5%              5.5%
630           10.8%              5.7%
631           12.8%              1.9%
632           12.0%              5.1%
633           13.1%              5.1%
634           12.0%              4.5%
635           10.5%              1.7%
636           12.7%              4.0%
637           11.5%              <NA>
638           10.8%              2.9%
639           14.4%              <NA>
640           12.1%              1.9%
641           12.0%              3.4%
642           10.9%              4.7%
643           10.8%              <NA>
644           13.0%              2.2%
645           13.3%              4.4%
646           12.8%              8.1%
647           13.4%              6.6%
648           14.1%              3.1%
649           14.0%              3.2%
650           12.9%              6.2%
651           14.8%              1.4%
652           12.6%              1.5%
653           14.0%              4.2%
654  Low Population   Zero Population
655           10.7%              8.0%
656           10.5%              2.4%
657           12.4%              3.8%
658           12.4%              6.5%
659           12.4%              2.0%
660           11.2%              <NA>
661           12.0%              2.0%
662           13.3%              4.0%
663           12.7%              3.2%
664           10.4%              <NA>
665           11.6%              3.5%
666           12.2%              4.7%
667           13.2%              5.9%
668           13.4%              2.0%
669           10.3%              <NA>
670           11.5%              <NA>
671           11.3%              1.8%
672           11.8%              4.3%
673            9.8%              2.2%
674            9.4%              2.8%
675            8.7%              <NA>
676            9.1%              3.6%
677           10.3%              2.7%
678            9.4%              2.7%
679           10.0%              0.8%
680           12.5%              4.8%
681            9.8%              2.8%
682            9.9%              1.0%
683           12.0%              <NA>
684           12.7%              3.2%
685           12.7%              3.8%
686           10.9%              1.9%
687           14.5%              3.0%
688           12.2%              4.7%
689           12.4%              <NA>
690           13.3%              <NA>
691           10.3%              6.1%
692           14.4%              <NA>
693           13.3%              4.0%
694           14.8%             13.8%
695           13.1%              <NA>
696            9.2%              4.3%
697           15.3%              5.0%
698           12.0%              4.5%
699           14.0%              8.5%
700           12.2%             10.5%
701           12.5%              5.0%
702           13.6%              5.2%
703           11.7%              <NA>
704           11.8%              <NA>
705           15.2%              5.5%
706           13.2%              4.4%
707           13.1%              2.4%
708           13.4%              1.7%
709           11.1%              4.6%
710           10.4%              4.6%
711           10.1%              5.3%
712            9.8%              3.2%
713           10.4%              4.6%
714           13.5%              4.3%
715           14.0%              7.6%
716           12.3%              4.6%
717           14.7%              5.4%
718           11.2%              8.2%
719           10.8%              3.6%
720           12.8%              4.1%
721           14.0%              6.2%
722           11.6%              2.8%
723            9.0%              3.6%
724           10.3%              4.6%
725            9.1%              3.6%
726           10.8%              2.8%
727           10.3%              3.3%
728            8.3%              1.3%
729           10.4%              7.7%
730           12.3%              5.7%
731           13.3%              2.8%
732           11.5%              2.5%
733            9.0%              2.3%
734            9.1%              3.0%
735            8.7%              3.3%
736            9.0%              2.7%
737           10.8%              1.7%
738           10.1%              2.8%
739           10.3%              <NA>
740           11.3%              1.8%
741           10.6%              4.7%
742           10.9%              2.2%
743           10.6%              2.3%
744           12.8%              4.8%
745            8.7%              2.7%
746            9.6%              3.2%
747            9.0%              2.9%
748           11.1%              2.5%
749           10.1%              0.5%
750           10.7%              3.9%
751            9.8%              3.7%
752           11.0%              2.1%
753           10.9%              3.2%
754           11.1%              4.4%
755           11.8%              2.6%
756           10.4%              4.5%
757           11.1%              3.7%
758           10.1%              2.3%
759           10.9%              8.6%
760           10.3%              2.8%
761           12.6%              <NA>
762           11.8%              5.8%
763           11.0%              9.5%
764           13.9%              5.5%
765           11.8%              2.6%
766            8.4%              <NA>
767           12.8%              <NA>
768           14.8%              8.3%
769           13.8%              4.4%
770           10.8%              5.2%
771           12.8%              5.9%
772           10.1%              5.8%
773            9.9%              5.7%
774           14.7%              6.9%
775           14.9%             11.9%
776           15.0%              9.7%
777           14.9%              6.3%
778           11.6%              5.4%
779           14.9%              8.0%
780           11.8%              4.3%
781           12.1%              2.7%
782           12.1%              6.3%
783           16.2%              5.7%
784           15.5%              9.2%
785           13.9%              6.7%
786           10.6%              4.3%
787           11.0%              5.5%
788           14.4%              8.6%
789           12.9%              6.6%
790           10.2%              3.5%
791           11.9%              3.4%
792           12.1%              <NA>
793           13.5%              <NA>
794           13.3%              4.1%
795           12.5%              2.6%
796           11.3%              5.9%
797            9.5%              6.0%
798           10.9%              2.6%
799           11.6%              4.0%
800           11.1%              1.4%
801           10.1%              4.4%
802           11.3%              6.4%
803           14.4%              7.3%
804           10.4%              2.9%
805           11.3%             11.1%
806           10.5%              6.4%
807           11.9%              <NA>
808           15.6%              9.6%
809           16.2%              6.0%
810           12.6%              6.0%
811            9.1%              7.8%
812            6.1%              6.2%
813            6.8%             11.6%
814           12.4%             11.8%
815           11.7%              3.5%
816           12.6%              9.8%
817           12.3%              7.7%
818           12.5%              8.5%
819           12.7%              7.0%
820           12.6%              4.2%
821           13.5%              8.3%
822           13.8%              9.6%
823           10.6%              3.2%
824           11.5%              1.6%
825           11.0%              2.1%
826           14.3%              5.0%
827           12.5%              3.1%
828           11.9%              4.2%
829           10.9%              3.2%
830           12.7%              7.1%
831           11.9%              0.8%
832            9.4%              2.6%
833           10.4%              4.8%
834            9.6%              1.8%
835            9.6%              2.2%
836            9.3%              0.0%
837            9.1%              3.3%
838            9.0%              0.5%
839            8.6%              2.5%
840           10.2%              1.9%
841            9.4%              2.7%
842            9.1%              0.8%
843           11.4%              1.8%
844            9.8%              3.7%
845            9.9%              0.9%
846           11.5%              3.6%
847           10.0%              3.1%
848            8.9%              2.5%
849            9.0%              1.6%
850            8.7%              2.2%
851            9.0%              2.8%
852            8.3%              1.2%
853            8.9%              4.8%
854            9.5%              1.9%
855           10.2%              0.5%
856            9.4%              6.8%
857            8.9%              7.9%
858            9.1%              3.9%
859            8.4%              7.2%
860            9.0%              3.8%
861            8.6%              2.4%
862            8.5%              4.3%
863            8.6%              2.3%
864            9.2%              2.9%
865            9.1%              2.7%
866            9.7%              3.5%
867            8.5%              2.5%
868           10.0%             14.1%
869            8.9%              1.1%
870           13.4%              7.0%
871           14.3%              5.0%
872           13.5%              9.9%
873           12.3%             12.0%
874           13.6%              6.0%
875           14.7%              8.0%
876           11.8%              2.6%
877           13.0%              7.6%
878           12.0%              <NA>
879           15.5%              3.9%
880           16.3%              3.7%
881           13.6%              4.4%
882           10.9%              2.0%
883           12.9%              4.4%
884           13.8%              <NA>
885           13.0%              <NA>
886           12.0%              3.0%
887           11.8%              3.4%
888           11.6%              5.9%
889           12.0%              6.7%
890           11.9%              5.7%
891           13.7%              5.7%
892           12.2%              9.7%
893           13.1%              5.6%
894           13.8%             12.7%
895           11.5%              8.2%
896           11.6%              1.6%
897           12.0%              4.6%
898           11.4%              <NA>
899           12.4%              4.5%
900           11.5%              6.0%
901           11.1%              2.4%
902           12.2%              5.0%
903           12.3%             11.1%
904           11.1%              5.8%
905           10.4%              5.6%
906           12.7%              2.5%
907           13.1%              4.0%
908           12.3%              <NA>
909           14.3%              <NA>
910           13.0%              5.5%
911           13.9%              5.0%
912           12.0%              4.9%
913           11.9%              4.3%
914           11.9%              3.6%
915           13.3%              2.7%
916           12.4%              6.4%
917           12.2%              7.0%
918           12.0%              1.2%
919           12.2%              7.3%
920           13.2%              3.8%
921           12.9%              4.3%
922           12.5%              3.9%
923           12.4%              4.2%
924           13.6%              7.6%
925           16.6%              <NA>
926           12.4%              3.5%
927           12.7%              4.5%
928           12.8%              3.1%
929           13.3%              4.2%
930           13.1%              8.1%
931           12.4%              9.8%
932           12.8%              9.8%
933           13.2%              8.7%
934           12.9%              5.9%
935           12.0%              4.5%
936           12.1%              3.0%
937           11.7%              9.9%
938           12.6%              5.6%
939           10.6%              6.0%
940           11.5%              4.0%
941           10.7%              6.7%
942           12.3%              8.6%
943           12.4%              7.7%
944           12.7%              9.7%
945           12.2%              6.6%
946           11.5%              3.6%
947           13.2%              5.3%
948           13.7%              4.5%
949           12.8%              7.5%
950           14.3%              7.7%
951           13.5%             11.8%
952           11.5%              6.5%
953           12.0%              3.4%
954           13.6%              8.5%
955           15.3%              3.6%
956           14.4%             14.5%
957           15.5%              7.5%
958           15.5%              5.4%
959           14.2%              <NA>
960           16.4%              6.0%
961           15.1%              <NA>
962           15.3%              8.4%
963           14.7%              7.2%
964           13.1%              <NA>
965           14.6%              <NA>
966           14.1%              8.6%
967           15.1%             14.9%
968           12.7%              5.9%
969           14.2%              7.8%
970           12.7%              4.3%
971           14.6%              5.9%
972           12.9%              6.1%
973           15.4%              8.6%
974           15.8%              7.0%
975           14.0%             11.9%
976           13.6%              2.5%
977           14.9%              6.9%
978           16.7%              6.1%
979           16.7%              6.8%
980           13.6%              6.3%
981           14.7%              9.4%
982           13.3%              4.5%
983           13.9%             13.3%
984           17.3%              3.0%
985           14.6%              4.7%
986           14.9%              6.7%
987           14.8%              8.1%
988           14.4%              6.6%
989           15.2%             10.2%
990           14.5%             12.9%
991           15.3%             10.5%
992           14.9%             11.7%
993           14.6%              3.3%
994           14.3%              5.1%
995           13.6%              8.6%
996           15.6%             23.2%
997           14.0%              6.9%
998           13.4%              2.2%
999           14.6%              7.9%
1000          15.8%             10.3%
1001          14.4%              4.7%
1002          15.5%              <NA>
1003          16.3%              <NA>
1004          16.2%             11.8%
1005          16.7%              6.6%
1006          13.2%              3.6%
1007          12.8%             14.8%
1008          12.5%              1.6%
1009          12.8%             10.4%
1010          12.8%              9.2%
1011          11.6%              5.5%
1012          10.8%              2.5%
1013          12.7%              <NA>
1014          11.8%              <NA>
1015          14.4%              5.2%
1016          15.3%              8.9%
1017          12.3%              8.8%
1018          12.8%              5.2%
1019          12.2%              6.9%
1020          13.8%              6.1%
1021          13.3%              7.9%
1022          13.5%              8.4%
1023          13.5%             10.6%
1024          13.4%             11.7%
1025          13.5%              5.4%
1026          16.0%             12.9%
1027          15.7%              8.1%
1028          14.7%              7.3%
1029          15.1%             11.3%
1030          15.1%             11.1%
1031          15.4%              3.6%
1032          16.4%             14.1%
1033          14.0%             10.4%
1034          14.9%              5.0%
1035          14.6%              4.7%
1036          10.3%              1.5%
1037          15.2%              6.6%
1038          13.8%              5.8%
1039          14.4%              5.7%
1040          12.8%              3.6%
1041          16.1%              6.6%
1042          15.4%              8.2%
1043          13.8%              9.4%
1044          13.7%              4.9%
1045          15.7%              1.9%
1046          15.2%              4.8%
1047          14.4%             10.5%
1048          15.6%              7.1%
1049          18.6%              7.1%
1050          17.4%              6.3%
1051          15.5%              8.3%
1052          14.4%              5.5%
1053          15.5%              5.1%
1054          12.4%              2.8%
1055          16.3%              2.2%
1056          16.4%              9.6%
1057          15.5%              7.6%
1058          14.1%              5.7%
1059          15.0%              3.9%
1060          13.8%              3.1%
1061          12.9%              <NA>
1062          13.9%              <NA>
1063          11.1%              2.0%
1064          15.6%              4.7%
1065          16.0%              6.9%
1066          15.9%              8.8%
1067          12.6%              2.2%
1068          11.5%              6.1%
1069          12.3%              5.4%
1070          14.1%              6.0%
1071          12.9%             14.8%
1072          15.9%              6.2%
1073          16.4%              8.2%
1074          12.6%              3.6%
1075          14.1%              3.4%
1076          15.3%              7.5%
1077          13.5%              3.3%
1078          22.4%              <NA>
1079          12.5%             10.0%
1080          12.5%              2.6%
1081          13.1%             10.3%
1082          13.1%              5.7%
1083          12.6%              3.4%
1084          11.5%              1.8%
1085          11.3%              2.7%
1086          14.2%              7.7%
1087          13.5%             12.0%
1088          14.0%              7.4%
1089          15.6%              3.7%
1090          14.0%              0.9%
1091          13.0%              2.2%
1092          13.2%              1.5%
1093          12.1%              4.3%
1094          13.7%              2.3%
1095          13.4%              2.6%
1096          12.3%              2.5%
1097          12.5%              6.0%
1098          13.8%              4.1%
1099 Low Population   Zero Population
1100 Low Population   Zero Population
1101 Low Population   Zero Population
1102          14.4%              2.9%
1103          13.5%              3.9%
1104          14.5%              4.8%
1105          15.2%              1.4%
1106          14.3%              2.7%
1107          12.7%              9.1%
1108          12.9%              <NA>
1109          13.5%              <NA>
1110          13.6%              2.0%
1111          17.8%              <NA>
1112          12.5%              <NA>
1113          14.5%              <NA>
1114          16.4%              <NA>
1115          16.5%              4.1%
1116          14.7%              <NA>
1117          13.2%              <NA>
1118          15.1%              8.0%
1119 Low Population   Zero Population
1120          20.5%             16.1%
1121          15.6%              4.7%
1122          14.3%              5.7%
1123          13.9%              <NA>
1124          14.5%              1.1%
1125          16.7%             18.4%
1126          14.4%              <NA>
1127 Low Population   Zero Population
1128          13.5%              1.8%
1129          10.1%              1.7%
1130          13.7%              1.9%
1131          13.6%              3.6%
1132          13.2%              1.8%
1133          12.4%              3.0%
1134          10.4%              2.9%
1135          10.6%              4.3%
1136          12.8%              1.1%
1137          11.9%              5.8%
1138 Low Population   Zero Population
1139          14.5%              8.2%
1140          13.8%              4.4%
1141          16.8%              7.0%
1142          19.4%             12.6%
1143          18.8%              8.6%
1144          18.5%              7.6%
1145          15.8%             11.3%
1146          14.5%              5.0%
1147          18.3%             16.8%
1148          17.5%             13.8%
1149          18.7%              8.4%
1150          15.0%              4.4%
1151          14.3%              3.4%
1152          16.5%              2.8%
1153          13.6%              2.2%
1154          12.5%              2.6%
1155          15.2%              <NA>
1156          15.5%              <NA>
1157          14.8%              4.4%
1158          14.9%              5.7%
1159          13.2%              <NA>
1160          14.2%              5.7%
1161          13.8%              <NA>
1162          14.3%   Zero Population
1163          14.0%              6.1%
1164          13.9%              <NA>
1165          14.6%              4.2%
1166          14.5%              4.8%
1167          13.0%              3.5%
1168          13.5%              6.6%
1169          13.5%              <NA>
1170          14.3%             12.3%
1171          17.6%              9.1%
1172          14.0%              6.8%
1173          18.8%              4.8%
1174          15.4%              7.4%
1175          19.1%             14.6%
1176          14.7%              3.8%
1177          14.6%              6.5%
1178          16.9%             14.6%
1179          13.1%              2.5%
1180          16.5%             11.6%
1181          14.7%              5.9%
1182          19.4%              <NA>
1183          15.4%             14.0%
1184          16.4%              9.5%
1185          12.4%              1.7%
1186          15.3%              4.8%
1187          15.3%              7.1%
1188          16.0%              <NA>
1189          13.4%              5.0%
1190          14.2%              6.4%
1191          11.4%              3.8%
1192          12.3%              3.5%
1193          12.8%             12.6%
1194          11.1%              4.3%
1195          11.6%              2.2%
1196          13.4%              1.7%
1197          14.1%              8.6%
1198          14.2%              5.1%
1199          11.3%              <NA>
1200          13.9%              3.8%
1201          15.5%              8.1%
1202          14.2%              9.5%
1203          15.8%             11.0%
1204          13.1%              6.4%
1205 Low Population   Zero Population
1206 Low Population   Zero Population
1207          13.6%              1.0%
1208          13.1%              1.8%
1209          13.7%              0.4%
1210          13.3%              6.2%
1211          14.0%              2.3%
1212          14.4%              2.3%
1213          13.3%              2.3%
1214          13.2%              0.5%
1215          20.9%             10.8%
1216          14.9%              2.7%
1217          13.9%              1.8%
1218          17.8%              4.2%
1219          17.5%              4.5%
1220          17.5%             14.0%
1221          16.1%              3.1%
1222          13.3%             11.0%
1223          20.9%             11.1%
1224          20.8%             24.5%
1225          18.8%             12.8%
1226          17.8%             17.9%
1227          15.8%              5.2%
1228          20.6%             15.4%
1229          17.4%             20.2%
1230          18.7%             14.5%
1231          15.9%              8.2%
1232          19.6%             15.0%
1233          19.1%              9.9%
1234          17.4%             12.8%
1235          15.2%              7.0%
1236          19.4%             19.0%
1237          17.0%              9.4%
1238          13.9%              4.6%
1239          15.9%              8.0%
1240          19.6%              3.7%
1241          17.5%             13.8%
1242          19.1%             17.6%
1243          18.0%             31.2%
1244          19.6%             18.9%
1245          18.9%             21.6%
1246          19.0%             17.8%
1247          22.3%              9.3%
1248          19.3%   Zero Population
1249          14.3%              4.3%
1250          14.9%              5.0%
1251          12.3%              8.3%
1252          14.2%              1.8%
1253          18.0%             10.2%
1254          15.5%              5.7%
1255          17.5%              5.0%
1256          16.1%              7.2%
1257          15.7%              5.0%
1258          15.6%              8.0%
1259          17.0%              2.5%
1260          17.4%              6.8%
1261          17.4%              4.0%
1262          18.4%             12.9%
1263          14.1%              1.5%
1264          12.1%              2.6%
1265          14.8%              1.8%
1266          15.8%              2.2%
1267          13.6%             15.4%
1268          13.9%              6.7%
1269          16.0%              8.4%
1270          22.4%             30.0%
1271          17.3%              3.7%
1272          21.3%              8.3%
1273          20.5%             11.5%
1274          17.8%             10.2%
1275          20.0%             12.8%
1276          18.1%             12.6%
1277          18.6%             21.7%
1278          15.9%              0.5%
1279          15.7%             16.9%
1280          17.3%             10.9%
1281          15.1%             11.4%
1282          16.6%             10.3%
1283          15.6%              7.1%
1284          18.1%             16.4%
1285          19.6%             15.1%
1286          18.3%             11.5%
1287          20.9%             16.1%
1288          19.3%             25.2%
1289          20.3%             18.4%
1290          18.5%             13.1%
1291          16.9%             11.6%
1292          18.8%             25.0%
1293          16.3%              5.0%
1294          16.7%              6.4%
1295          17.8%              4.2%
1296          21.4%              2.9%
1297          18.8%             14.1%
1298          23.8%              <NA>
1299          17.4%              <NA>
1300          17.0%              6.2%
1301          21.4%             13.7%
1302          17.5%              4.4%
1303          21.8%             22.5%
1304          20.1%              7.3%
1305          17.8%              7.4%
1306          22.0%             21.9%
1307          20.8%             17.5%
1308          20.3%              7.9%
1309          17.7%             18.2%
1310          16.9%             13.3%
1311          16.8%              5.5%
1312          17.9%              7.9%
1313          16.3%             10.0%
1314          18.9%              9.0%
1315          13.1%              1.6%
1316          16.3%              0.2%
1317          14.9%              1.4%
1318          14.0%              1.2%
1319          12.9%              2.2%
1320          12.2%              1.2%
1321          13.7%              0.6%
1322          14.0%              0.6%
1323          16.8%              2.1%
1324          17.5%              3.8%
1325          16.3%              6.2%
1326          18.5%              6.1%
1327          23.9%             20.5%
1328          18.4%              4.0%
1329          16.8%              3.6%
1330          19.5%             12.0%
1331          20.3%             23.1%
1332          19.2%             17.5%
1333          18.7%              7.5%
1334          19.9%             18.8%
1335          20.8%              9.7%
1336 Low Population   Zero Population
1337          15.8%              3.8%
1338          16.2%              9.4%
1339          17.1%              3.5%
1340          17.3%              8.1%
1341          18.3%              4.3%
1342          18.7%              4.3%
1343          18.7%             10.7%
1344          20.9%              1.9%
1345          18.4%              1.8%
1346          19.3%              1.7%
1347          18.8%              3.8%
1348          19.7%              1.9%
1349          16.2%              3.7%
1350          22.3%             13.8%
1351          19.5%              9.0%
1352          15.3%              2.7%
1353          17.4%              1.0%
1354          13.6%              4.0%
1355          19.1%              5.0%
1356          13.8%              4.9%
1357          15.1%             11.4%
1358          16.9%              6.9%
1359          14.1%              2.0%
1360          14.2%              1.9%
1361          16.3%             10.6%
1362          16.1%              6.0%
1363          15.0%              5.7%
1364          15.2%              0.6%
1365          14.6%              4.6%
1366          14.7%              8.0%
1367          19.0%              3.3%
1368          16.6%              8.7%
1369          14.9%              2.6%
1370          15.8%              7.9%
1371          16.8%             10.5%
1372          15.0%              7.6%
1373          16.1%              4.4%
1374          15.2%              6.6%
1375          15.6%              4.9%
1376          16.4%             10.7%
1377          17.9%              9.6%
1378          17.5%             20.8%
1379          17.9%             19.7%
1380          15.5%              4.1%
1381          19.4%              3.5%
1382          11.8%              2.2%
1383          10.3%              1.4%
1384          11.6%              2.2%
1385          11.9%              3.7%
1386           9.6%              2.4%
1387          18.1%             12.4%
1388          15.5%              8.5%
1389          17.9%             13.0%
1390          18.8%              6.9%
1391          14.7%             11.2%
1392          14.2%             10.6%
1393          13.6%              1.2%
1394          14.2%             10.1%
1395          14.9%              5.4%
1396          15.8%              7.0%
1397          17.5%             12.3%
1398          15.0%             15.8%
1399          14.6%              6.3%
1400          17.1%              3.2%
1401          16.7%              9.6%
1402          15.0%              4.6%
1403          14.6%             10.8%
1404          16.5%              3.0%
1405          17.4%              9.1%
1406          22.7%             20.1%

Remove Percents

# Chunk Explanation: Here in this section I will remove the % in the values using Gsub. This is because when graphing and modeling the percents messed up the graphs. R was not registering the values as numeric and therefore all analysis was affected. Doing this does not compromise the integrity of the data. 

# Remove "%" symbol using gsub
merged_data$percentunemployed<- gsub("%", "", merged_data$percentunemployed)
merged_data$depressrate <- gsub("%", "", merged_data$depressrate)
merged_data$energyburdenrate <- gsub("%", "", merged_data$energyburdenrate)
merged_data$englishrates <- gsub("%", "", merged_data$englishrates)
merged_data$internetlackrate <- gsub("%", "", merged_data$internetlackrate)
merged_data$badmental <- gsub("%", "", merged_data$badmental)
### merged_data$percentunemployed <- gsub("%", "", merged_data$percentunemployed)
# Convert the column to numeric (depending on later results)
merged_data$percentunemployed <- as.numeric(merged_data$percentunemployed)
Warning: NAs introduced by coercion
merged_data$depressrate <- as.numeric(merged_data$depressrate)
Warning: NAs introduced by coercion
merged_data$energyburdenrate <- as.numeric(merged_data$energyburdenrate)
Warning: NAs introduced by coercion
merged_data$englishrates <- as.numeric(merged_data$englishrates)
Warning: NAs introduced by coercion
merged_data$internetlackrate <- as.numeric(merged_data$internetlackrate)
merged_data$badmental <- as.numeric(merged_data$badmental)
Warning: NAs introduced by coercion
### merged_data$percentunemployed <- as.numeric(merged_data$percentunemployed)

General Cleaning Description

In this section I have renamed columns for clarity, added the appropriate years, and removed redundant and unneeded columns. This was all done to make the merging of the data sets and general analysis run more smoothly. I have ensured that this removal and editing of names does not compromise or take away from the data’s integrity

Ascribe County To Each Observation

# Define a dictionary to map starting codes to county names
county_codes <- c('24001' = 'Allegheny', '24003' = 'Anne Arrundel', '24510' = 'Baltimore City','24005' = 'Baltimore', '24009' = 'Calvert', '24013' = 'Carroll', '24015' = 'Cecil', '24017' = 'Charles', '24019' = 'Dorchester', '24021' = 'Fredrick', '24023' = 'Garrett', '24025' = 'Harford', '24027' = 'Howard', '24031' = 'Montgomery', '24033' = 'P.G County', '24035' = 'Queen Anne','24039' = 'Somorsett','24037' = 'St. Mary','24041' = 'Talbot','24043' = 'Washington','24045' = 'Wicomico', '24047' = 'Worcestor', '24029' = 'Kent County')

# Create a new column 'County' based on the starting 4 digits of 'CensusTract'
merged_data$County <- sapply(merged_data$CensusTract, function(x) county_codes[substr(x, 1, 5)])

# View the updated data frame
print(data)
function (..., list = character(), package = NULL, lib.loc = NULL, 
    verbose = getOption("verbose"), envir = .GlobalEnv, overwrite = TRUE) 
{
    fileExt <- function(x) {
        db <- grepl("\\.[^.]+\\.(gz|bz2|xz)$", x)
        ans <- sub(".*\\.", "", x)
        ans[db] <- sub(".*\\.([^.]+\\.)(gz|bz2|xz)$", "\\1\\2", 
            x[db])
        ans
    }
    my_read_table <- function(...) {
        lcc <- Sys.getlocale("LC_COLLATE")
        on.exit(Sys.setlocale("LC_COLLATE", lcc))
        Sys.setlocale("LC_COLLATE", "C")
        read.table(...)
    }
    stopifnot(is.character(list))
    names <- c(as.character(substitute(list(...))[-1L]), list)
    if (!is.null(package)) {
        if (!is.character(package)) 
            stop("'package' must be a character vector or NULL")
    }
    paths <- find.package(package, lib.loc, verbose = verbose)
    if (is.null(lib.loc)) 
        paths <- c(path.package(package, TRUE), if (!length(package)) getwd(), 
            paths)
    paths <- unique(normalizePath(paths[file.exists(paths)]))
    paths <- paths[dir.exists(file.path(paths, "data"))]
    dataExts <- tools:::.make_file_exts("data")
    if (length(names) == 0L) {
        db <- matrix(character(), nrow = 0L, ncol = 4L)
        for (path in paths) {
            entries <- NULL
            packageName <- if (file_test("-f", file.path(path, 
                "DESCRIPTION"))) 
                basename(path)
            else "."
            if (file_test("-f", INDEX <- file.path(path, "Meta", 
                "data.rds"))) {
                entries <- readRDS(INDEX)
            }
            else {
                dataDir <- file.path(path, "data")
                entries <- tools::list_files_with_type(dataDir, 
                  "data")
                if (length(entries)) {
                  entries <- unique(tools::file_path_sans_ext(basename(entries)))
                  entries <- cbind(entries, "")
                }
            }
            if (NROW(entries)) {
                if (is.matrix(entries) && ncol(entries) == 2L) 
                  db <- rbind(db, cbind(packageName, dirname(path), 
                    entries))
                else warning(gettextf("data index for package %s is invalid and will be ignored", 
                  sQuote(packageName)), domain = NA, call. = FALSE)
            }
        }
        colnames(db) <- c("Package", "LibPath", "Item", "Title")
        footer <- if (missing(package)) 
            paste0("Use ", sQuote(paste("data(package =", ".packages(all.available = TRUE))")), 
                "\n", "to list the data sets in all *available* packages.")
        else NULL
        y <- list(title = "Data sets", header = NULL, results = db, 
            footer = footer)
        class(y) <- "packageIQR"
        return(y)
    }
    paths <- file.path(paths, "data")
    for (name in names) {
        found <- FALSE
        for (p in paths) {
            tmp_env <- if (overwrite) 
                envir
            else new.env()
            if (file_test("-f", file.path(p, "Rdata.rds"))) {
                rds <- readRDS(file.path(p, "Rdata.rds"))
                if (name %in% names(rds)) {
                  found <- TRUE
                  if (verbose) 
                    message(sprintf("name=%s:\t found in Rdata.rds", 
                      name), domain = NA)
                  thispkg <- sub(".*/([^/]*)/data$", "\\1", p)
                  thispkg <- sub("_.*$", "", thispkg)
                  thispkg <- paste0("package:", thispkg)
                  objs <- rds[[name]]
                  lazyLoad(file.path(p, "Rdata"), envir = tmp_env, 
                    filter = function(x) x %in% objs)
                  break
                }
                else if (verbose) 
                  message(sprintf("name=%s:\t NOT found in names() of Rdata.rds, i.e.,\n\t%s\n", 
                    name, paste(names(rds), collapse = ",")), 
                    domain = NA)
            }
            if (file_test("-f", file.path(p, "Rdata.zip"))) {
                warning("zipped data found for package ", sQuote(basename(dirname(p))), 
                  ".\nThat is defunct, so please re-install the package.", 
                  domain = NA)
                if (file_test("-f", fp <- file.path(p, "filelist"))) 
                  files <- file.path(p, scan(fp, what = "", quiet = TRUE))
                else {
                  warning(gettextf("file 'filelist' is missing for directory %s", 
                    sQuote(p)), domain = NA)
                  next
                }
            }
            else {
                files <- list.files(p, full.names = TRUE)
            }
            files <- files[grep(name, files, fixed = TRUE)]
            if (length(files) > 1L) {
                o <- match(fileExt(files), dataExts, nomatch = 100L)
                paths0 <- dirname(files)
                paths0 <- factor(paths0, levels = unique(paths0))
                files <- files[order(paths0, o)]
            }
            if (length(files)) {
                for (file in files) {
                  if (verbose) 
                    message("name=", name, ":\t file= ...", .Platform$file.sep, 
                      basename(file), "::\t", appendLF = FALSE, 
                      domain = NA)
                  ext <- fileExt(file)
                  if (basename(file) != paste0(name, ".", ext)) 
                    found <- FALSE
                  else {
                    found <- TRUE
                    zfile <- file
                    zipname <- file.path(dirname(file), "Rdata.zip")
                    if (file.exists(zipname)) {
                      Rdatadir <- tempfile("Rdata")
                      dir.create(Rdatadir, showWarnings = FALSE)
                      topic <- basename(file)
                      rc <- .External(C_unzip, zipname, topic, 
                        Rdatadir, FALSE, TRUE, FALSE, FALSE)
                      if (rc == 0L) 
                        zfile <- file.path(Rdatadir, topic)
                    }
                    if (zfile != file) 
                      on.exit(unlink(zfile))
                    switch(ext, R = , r = {
                      library("utils")
                      sys.source(zfile, chdir = TRUE, envir = tmp_env)
                    }, RData = , rdata = , rda = load(zfile, 
                      envir = tmp_env), TXT = , txt = , tab = , 
                      tab.gz = , tab.bz2 = , tab.xz = , txt.gz = , 
                      txt.bz2 = , txt.xz = assign(name, my_read_table(zfile, 
                        header = TRUE, as.is = FALSE), envir = tmp_env), 
                      CSV = , csv = , csv.gz = , csv.bz2 = , 
                      csv.xz = assign(name, my_read_table(zfile, 
                        header = TRUE, sep = ";", as.is = FALSE), 
                        envir = tmp_env), found <- FALSE)
                  }
                  if (found) 
                    break
                }
                if (verbose) 
                  message(if (!found) 
                    "*NOT* ", "found", domain = NA)
            }
            if (found) 
                break
        }
        if (!found) {
            warning(gettextf("data set %s not found", sQuote(name)), 
                domain = NA)
        }
        else if (!overwrite) {
            for (o in ls(envir = tmp_env, all.names = TRUE)) {
                if (exists(o, envir = envir, inherits = FALSE)) 
                  warning(gettextf("an object named %s already exists and will not be overwritten", 
                    sQuote(o)))
                else assign(o, get(o, envir = tmp_env, inherits = FALSE), 
                  envir = envir)
            }
            rm(tmp_env)
        }
    }
    invisible(names)
}
<bytecode: 0x1237b5488>
<environment: namespace:utils>

EDA : Statewide Analysis

Guiding Question: How is Montgomery County Performing In Comparison To Other Counties?

How Do Community Factors Like Internet Access Relate to Employment And English Proficiency?

Visual 1: Crude Depression Rates Across Maryland Counties

average_by_county <- merged_data %>%
  group_by(County) %>%
  summarize(Average = mean(depressrate))
average_by_county <- average_by_county %>% filter(!is.na(Average))
# Explanation: I removed the N/As and chose to focus on counties that possesed data substantial enough for analysis 

# Create the bar graph
ggplot(average_by_county, aes(x = County, y = Average, fill = County)) +
  geom_bar(bins = 10, stat = "identity")+
  labs(title = "Average of Crude Depression Rates by County", x = "County", y = "Average Value")
Warning in geom_bar(bins = 10, stat = "identity"): Ignoring unknown parameters:
`bins`

Explanation: The bar graph shows that Montgomery County has among the lowest Crude Depression Rates Among Adults in Maryland. However, the data should also be explored on a county level.

Visual 2: Households Without Internet Across Counties

merged_data <- merged_data[!is.na(merged_data$internetlackrate), ] 
internet_by_county <- merged_data %>%
  group_by(County) %>%
  summarize(Average = mean(internetlackrate))
# Create the bar graph
ggplot(internet_by_county, aes(x = County, y = Average)) +
  geom_bar(bins = 8, stat = "identity")+
  labs(title = "Percent Of Population With No Home Internet", x = "County", y = "Average Value")
Warning in geom_bar(bins = 8, stat = "identity"): Ignoring unknown parameters:
`bins`

Explanation: Among all MD Counties Montgomery County has the lowest reported number of households with no internet access

Visual 3: Violin Plot for 3 Counties Internet Access (MoCo, PG, and Baltimore County)

# Explanation: These 3 counties were selected for brief EDA for 2 major reasons. Montgomery County was selected because it is the county this project is centered around. PG County was then selected because it is in the center of median family income in MD as of 2020 and Baltimore County was towards the bottom of the list. Having these 3 counties that have differing median incomes could allow us to see the impact of finances on the data. 
moco_bmore_pg_data <- merged_data[merged_data$County %in% c("Montgomery", "Baltimore", "P.G County","Howard"), ]
ggplot(moco_bmore_pg_data, aes(x = County, y = internetlackrate, fill = County)) +
  geom_violin(position = "dodge") +
# Customize (optional)
  labs(x = "County", y = "Internet Access", title = "Distribution of Internet Access by County") +
  theme_bw()

Visual 3B: Expanded Into Ridge Plot

library(ggridges)
ggplot(moco_bmore_pg_data, aes(x = internetlackrate, y = County, fill = County)) +
  geom_density_ridges(scale = 1) +
  geom_density_ridges_gradient(scale = 1.5, rel_min_height = 0.05)+
  labs(title = 'Internet Access Ridge Plot [MoCo, PG, Baltimore]',
       y = 'County',
       x = 'Percent of Housholds Without Home Internet') 
Picking joint bandwidth of 1.36
Picking joint bandwidth of 1.36

  theme_ridges() + 
  theme(legend.position = "none")
List of 97
 $ line                      :List of 6
  ..$ colour       : chr "black"
  ..$ linewidth    : num 0.636
  ..$ linetype     : num 1
  ..$ lineend      : chr "butt"
  ..$ arrow        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_line" "element"
 $ rect                      :List of 5
  ..$ fill         : chr "transparent"
  ..$ colour       : logi NA
  ..$ linewidth    : num 0
  ..$ linetype     : num 0
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_rect" "element"
 $ text                      :List of 11
  ..$ family       : chr ""
  ..$ face         : chr "plain"
  ..$ colour       : chr "black"
  ..$ size         : num 14
  ..$ hjust        : num 0.5
  ..$ vjust        : num 0.5
  ..$ angle        : num 0
  ..$ lineheight   : num 0.9
  ..$ margin       : 'margin' num [1:4] 0points 0points 0points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ title                     : NULL
 $ aspect.ratio              : NULL
 $ axis.title                : NULL
 $ axis.title.x              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 1
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 6points 0points 3points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.title.x.top          :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : num 0
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 3.5points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.title.x.bottom       : NULL
 $ axis.title.y              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 1
  ..$ vjust        : NULL
  ..$ angle        : num 90
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 6points 0points 3points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.title.y.left         : NULL
 $ axis.title.y.right        :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : num 0
  ..$ angle        : num -90
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 0points 3.5points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.text                 :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : chr "black"
  ..$ size         : num 12
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.text.x               :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 3points 0points 0points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.text.x.top           :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : num 0
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 2.8points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.text.x.bottom        : NULL
 $ axis.text.y               :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 1
  ..$ vjust        : num 0
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 3points 0points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.text.y.left          : NULL
 $ axis.text.y.right         :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 0
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 0points 2.8points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ axis.ticks                :List of 6
  ..$ colour       : chr "grey90"
  ..$ linewidth    : num 0.5
  ..$ linetype     : NULL
  ..$ lineend      : NULL
  ..$ arrow        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_line" "element"
 $ axis.ticks.x              : NULL
 $ axis.ticks.x.top          : NULL
 $ axis.ticks.x.bottom       : NULL
 $ axis.ticks.y              :List of 6
  ..$ colour       : chr "grey90"
  ..$ linewidth    : num 0.5
  ..$ linetype     : NULL
  ..$ lineend      : NULL
  ..$ arrow        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_line" "element"
 $ axis.ticks.y.left         : NULL
 $ axis.ticks.y.right        : NULL
 $ axis.ticks.length         : 'simpleUnit' num 3.5points
  ..- attr(*, "unit")= int 8
 $ axis.ticks.length.x       : NULL
 $ axis.ticks.length.x.top   : NULL
 $ axis.ticks.length.x.bottom: NULL
 $ axis.ticks.length.y       : NULL
 $ axis.ticks.length.y.left  : NULL
 $ axis.ticks.length.y.right : NULL
 $ axis.line                 : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ axis.line.x               : NULL
 $ axis.line.x.top           : NULL
 $ axis.line.x.bottom        : NULL
 $ axis.line.y               : NULL
 $ axis.line.y.left          : NULL
 $ axis.line.y.right         : NULL
 $ legend.background         :List of 5
  ..$ fill         : NULL
  ..$ colour       : logi NA
  ..$ linewidth    : NULL
  ..$ linetype     : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_rect" "element"
 $ legend.margin             : 'margin' num [1:4] 7points 7points 7points 7points
  ..- attr(*, "unit")= int 8
 $ legend.spacing            : 'simpleUnit' num 14points
  ..- attr(*, "unit")= int 8
 $ legend.spacing.x          : NULL
 $ legend.spacing.y          : NULL
 $ legend.key                : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ legend.key.size           : 'simpleUnit' num 1lines
  ..- attr(*, "unit")= int 3
 $ legend.key.height         : NULL
 $ legend.key.width          : NULL
 $ legend.text               :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 0.857
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ legend.text.align         : NULL
 $ legend.title              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 0
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ legend.title.align        : NULL
 $ legend.position           : chr "none"
 $ legend.direction          : NULL
 $ legend.justification      : chr [1:2] "left" "center"
 $ legend.box                : NULL
 $ legend.box.just           : NULL
 $ legend.box.margin         : 'margin' num [1:4] 0cm 0cm 0cm 0cm
  ..- attr(*, "unit")= int 1
 $ legend.box.background     : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ legend.box.spacing        : 'simpleUnit' num 14points
  ..- attr(*, "unit")= int 8
 $ panel.background          : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ panel.border              : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ panel.spacing             : 'simpleUnit' num 7points
  ..- attr(*, "unit")= int 8
 $ panel.spacing.x           : NULL
 $ panel.spacing.y           : NULL
 $ panel.grid                :List of 6
  ..$ colour       : chr "white"
  ..$ linewidth    : NULL
  ..$ linetype     : NULL
  ..$ lineend      : NULL
  ..$ arrow        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_line" "element"
 $ panel.grid.major          :List of 6
  ..$ colour       : chr "grey90"
  ..$ linewidth    : num 0.5
  ..$ linetype     : NULL
  ..$ lineend      : NULL
  ..$ arrow        : logi FALSE
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_line" "element"
 $ panel.grid.minor          : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ panel.grid.major.x        : NULL
 $ panel.grid.major.y        : NULL
 $ panel.grid.minor.x        : NULL
 $ panel.grid.minor.y        : NULL
 $ panel.ontop               : logi FALSE
 $ plot.background           : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ plot.title                :List of 11
  ..$ family       : NULL
  ..$ face         : chr "bold"
  ..$ colour       : NULL
  ..$ size         : num 14
  ..$ hjust        : num 0
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 7points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.title.position       : chr "panel"
 $ plot.subtitle             :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 0.857
  ..$ hjust        : num 0
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 6points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.caption              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 0.857
  ..$ hjust        : num 1
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 6points 0points 0points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.caption.position     : chr "panel"
 $ plot.tag                  :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 1.2
  ..$ hjust        : num 0.5
  ..$ vjust        : num 0.5
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.tag.position         : chr "topleft"
 $ plot.margin               : 'margin' num [1:4] 7points 14points 7points 7points
  ..- attr(*, "unit")= int 8
 $ strip.background          :List of 5
  ..$ fill         : chr "grey80"
  ..$ colour       : chr "grey50"
  ..$ linewidth    : num 0
  ..$ linetype     : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_rect" "element"
 $ strip.background.x        : NULL
 $ strip.background.y        : NULL
 $ strip.clip                : chr "inherit"
 $ strip.placement           : chr "inside"
 $ strip.text                :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 0.857
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ strip.text.x              : NULL
 $ strip.text.x.bottom       : NULL
 $ strip.text.x.top          : NULL
 $ strip.text.y              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : num -90
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ strip.text.y.left         :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : num 90
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ strip.text.y.right        : NULL
 $ strip.switch.pad.grid     : 'simpleUnit' num 3.5points
  ..- attr(*, "unit")= int 8
 $ strip.switch.pad.wrap     : 'simpleUnit' num 3.5points
  ..- attr(*, "unit")= int 8
 - attr(*, "class")= chr [1:2] "theme" "gg"
 - attr(*, "complete")= logi TRUE
 - attr(*, "validate")= logi TRUE

Explanation: Compared to other counties Montgomery County seems to perform well in a lot of areas. Here we can see that when it comes to % of housholds in a given census tract without internet access Montgomery County has lower values compared to counties like Baltimore, and PG. However, Howard County has less households without internet access.

Data Product 1: Preliminary Statistical Analysis

Visual 4: Internet Access and English Proficiency Scatter Plot Across MD

merged_data <- merged_data[!is.na(merged_data$englishrates), ] 
ggplot(merged_data, aes(x = internetlackrate, y = englishrates, color = County)) +
  geom_point() +
  labs(x = "% No Internet Access", y = "Poor English Speaking Rate (%)", title = "Internet Access vs. English Speaking Rates")+
    theme_bw()

Visual 4B: Internet Access and English Profficiency Scatter Plot Across MD (Montgomery County, Howard County, PG County, Baltimore County)

ggplot(moco_bmore_pg_data, aes(x = internetlackrate, y = englishrates)) +
  geom_point() +  # Add points to represent data points
  facet_wrap(~ County) +  # Separate plots by county
  labs(x = "% No Internet Access", y = "% of Population Speaking Poor English", title = "Internet Access vs. English Speaking Rates (By County)") +
  theme_bw()+
  theme(strip.background =element_rect(fill="black"))+
  theme(strip.text = element_text(colour = 'white'))
Warning: Removed 2 rows containing missing values (`geom_point()`).

# Remove Percent in Employment Percents
merged_data$percentunemployed <- gsub("%", "", merged_data$percentunemployed)
merged_data <- merged_data[!is.na(merged_data$percentunemployed), ]
merged_data$percentunemployed <- as.numeric(merged_data$percentunemployed)
ggplot(merged_data, aes(x = internetlackrate, y = percentunemployed, color = County)) +
  geom_point() +
  labs(x = " Households With No Internet Access (%)", y = "Unemployment (%)", title = "Internet Access vs. Unemployment")

Visual 5B: Internet Access and Employment Scatter Plot Across MD Core Counties (Montgomery County, Howard County, PG County, Baltimore County)

ggplot(moco_bmore_pg_data, aes(x = internetlackrate, y = percentunemployed)) +
  geom_point() +  # Add points to represent data points
  facet_wrap(~ County) +  # Separate plots by county
  labs(x = "% No Internet Access", y = "% Unemployment", title = "Internet Access vs. Unemployment (By County)") +
  theme_bw()+
  theme(strip.background =element_rect(fill="black"))+
  theme(strip.text = element_text(colour = 'white'))
Warning: Removed 2 rows containing missing values (`geom_point()`).

Visual 6: Internet Access and Mental Health Across MD Core Counties

ggplot(moco_bmore_pg_data, aes(x = internetlackrate, y = badmental)) +
  geom_point() +  # Add points to represent data points
  facet_wrap(~ County) +  # Separate plots by county
  labs(x = "% No Internet Access", y = "% Reported 14+ Bad Mental Health Days", title = "Internet Access vs. Reported Bad Mental Health Days (By County)") +
  theme_bw()+
  theme(strip.background =element_rect(fill="black"))+
  theme(strip.text = element_text(colour = 'white'))
Warning: Removed 2 rows containing missing values (`geom_point()`).

Visual 7: English Speaking and Mental Health

ggplot(moco_bmore_pg_data, aes(x = internetlackrate, y = badmental)) +
  geom_point() +  # Add points to represent data points
  facet_wrap(~ County) +  # Separate plots by county
  labs(x = "% No Home Internet", y = "% Reported 14+ Bad Mental Health Days", title = "English Proficiency vs. Reported Bad Mental Health Days (By County)") +
  theme_bw()+
  theme(strip.background =element_rect(fill="black"))+
  theme(strip.text = element_text(colour = 'white'))
Warning: Removed 2 rows containing missing values (`geom_point()`).

Visual 8: Energy Burden and Internet Access Across MD Core Counties

ggplot(moco_bmore_pg_data, aes(x = energyburdenrate, y = internetlackrate)) +
  geom_point() +  # Add points to represent data points
  facet_wrap(~ County) +  # Separate plots by county
  labs(x = "% Energy Burden" , y = "% No Home Internet", title = "% Energy Burden (By County) Vs % No Home Internet vs. ") +
  theme_bw()+
  theme(strip.background =element_rect(fill="black"))+
  theme(strip.text = element_text(colour = 'white'))
Warning: Removed 2 rows containing missing values (`geom_point()`).

# Definition: Energy Burden: Percent of Area's gross income spent on home energy costs (which includes internet costs)

EDA General Conclusions: Community design factors such as English Proficiency, % Energy Burden, and Internet Access Appear to have an impact on Life Outcomes such as: Employment, Depression Rates, and Poor Mental Health Days.

Guiding Questions:

  1. How does energy burden impact one’s access to health in Montgomery County?
  2. Can we pinpoint locations in need of intervention, where the brunt of disparities are experienced the most?
  3. Does energy burden have a significant impact on one’s access to the internet?
  4. What community design factor (Internet Access, Energy Burden, % With Poor English) impact personal outcomes (Employment, Depression, Mental Health) the most?

Data Product 2: In Depth Statistical Analysis on Montgomery County Variables

Using Linear and Regression Models I will explore the extent of how these variables impact each other and work to create an efficient model for Montgomery County only. First I must subset the data set again to only include Montgomery County Variables.

MoCo Subset

# Specify my target county
target_county <- "Montgomery"

# Subset the data for the target county
moco_data <- merged_data %>%
  filter(County == target_county)

Model 1: Energy Burden And Internet Access (Does energy burden have a significant impact on one’s access to the internet?)

model1 <- lm(internetlackrate ~ energyburdenrate, data = moco_data)  # y ~ x represents dependent variable ~ independent
summary(model1)

Call:
lm(formula = internetlackrate ~ energyburdenrate, data = moco_data)

Residuals:
    Min      1Q  Median      3Q     Max 
-6.4568 -2.3681 -0.7955  1.7984 12.4432 

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)       -1.7903     0.8846  -2.024   0.0444 *  
energyburdenrate   4.0189     0.5228   7.688  7.3e-13 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 3.444 on 194 degrees of freedom
Multiple R-squared:  0.2335,    Adjusted R-squared:  0.2296 
F-statistic:  59.1 on 1 and 194 DF,  p-value: 7.302e-13

Model Analysis

  1. Positive Relationship: The coefficient for energyburdenrate is positive (4.0189) and statistically significant (p-value < 0.0001), indicating a positive association between energy burden rate and internet lack rate. As the energy burden rate increases, the internet lack rate also tends to increase.
  2. Residuals: The minimum residual is -6.4568, the first quartile (Q1) is -2.3681, the median is -0.7955, the third quartile (Q3) is 1.7984, and the maximum residual is 12.4432. These values suggest that the model fits the data reasonably well, with most residuals falling within a moderate range around zero.
  3. R-squared: The multiple R-squared (0.2335) indicates that the model explains approximately 23.35% of the variance in internet lack rate based on the energy burden rate. The adjusted R-squared (0.2296) takes into account the number of predictors (one in this case) and is slightly lower.
  4. F-statistic: The F-statistic (59.1) and its highly significant p-value (0.00000000000073) further support the model’s overall significance. There is strong evidence that the relationship between energy burden rate and internet lack rate is not due to chance.
  5. Limitations: This model only considers one independent variable (energy burden rate). Other factors might influence internet lack rate, and including them could improve the model’s explanatory power. R-squared (around 23%) suggests a moderate association, not a perfect fit. There might be unexplained variation in the data.

Guided Question Answer: Yes, there is a significant relationship between the % Energy Burden and the % Household With No Internet Access. This essentially means that when the % Energy Burden is higher, indicating that energy takes up more of a census tract’s median income, individuals are less likely to have home internet insurance. This is an issue internet access is a necessity in this current world. Through online connection individuals can apply for jobs and expand their education, leading them to earn increased income. But it seems like individuals who are from these high Energy Burden locations are at a disadvantage as internet is not accessible because of income. It is important to note that the r^2 value is on the lower end so a better more accurate model can be created.

Model 2: Depression, Bad Mental Health Days, and Internet Access (How does energy burden and internet access impact one’s access to health in Montgomery County?)

# Interet + Energy Burden's impact on Unemployment
model2 <- lm(percentunemployed ~ internetlackrate + energyburdenrate, data = moco_data)
summary(model2)

Call:
lm(formula = percentunemployed ~ internetlackrate + energyburdenrate, 
    data = moco_data)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.9815 -1.2938 -0.3828  0.9916 10.1667 

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)       0.11429    0.58236   0.196   0.8446    
internetlackrate  0.10220    0.04677   2.185   0.0301 *  
energyburdenrate  2.37163    0.38898   6.097 5.78e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 2.244 on 193 degrees of freedom
Multiple R-squared:  0.2704,    Adjusted R-squared:  0.2628 
F-statistic: 35.76 on 2 and 193 DF,  p-value: 6.139e-14
# Load libraries (assuming 'pROC' is not already loaded)
library(pROC)
Type 'citation("pROC")' for a citation.

Attaching package: 'pROC'
The following objects are masked from 'package:stats':

    cov, smooth, var
# Sample your data (replace with your actual sampling method)
set.seed(123)  # Set a seed for reproducibility
sample_size <- 0.7  # Adjust sample size as needed
data_sampled <- sample(nrow(moco_data), size = nrow(moco_data) * sample_size)
data_subset <- moco_data[data_sampled, ]

Model 3: Employment and Internet Access+Energy Burden (Can we predict employment based on these factors?)

Model Testing

Data Product 3: Leaflet Map of Locations With Accessible Internet Access (Among All County WiFi Spots)

# Load required libraries
library(tidycensus)
library(tidyverse)
library(sf)
Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE
library(tigris)
To enable caching of data, set `options(tigris_use_cache = TRUE)`
in your R script or .Rprofile.
library(leaflet)
# Load Shapefile and Merge With County Data 
library(tigris)
moco_tracts <- tracts(state = "MD", county = "Montgomery")
Retrieving data for the year 2022

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |                                                                      |   1%
  |                                                                            
  |=                                                                     |   1%
  |                                                                            
  |=                                                                     |   2%
  |                                                                            
  |==                                                                    |   2%
  |                                                                            
  |==                                                                    |   3%
  |                                                                            
  |===                                                                   |   4%
  |                                                                            
  |===                                                                   |   5%
  |                                                                            
  |====                                                                  |   5%
  |                                                                            
  |====                                                                  |   6%
  |                                                                            
  |=====                                                                 |   6%
  |                                                                            
  |=====                                                                 |   7%
  |                                                                            
  |=====                                                                 |   8%
  |                                                                            
  |======                                                                |   8%
  |                                                                            
  |======                                                                |   9%
  |                                                                            
  |=======                                                               |  10%
  |                                                                            
  |========                                                              |  11%
  |                                                                            
  |========                                                              |  12%
  |                                                                            
  |=========                                                             |  13%
  |                                                                            
  |==========                                                            |  14%
  |                                                                            
  |===========                                                           |  15%
  |                                                                            
  |===========                                                           |  16%
  |                                                                            
  |============                                                          |  17%
  |                                                                            
  |============                                                          |  18%
  |                                                                            
  |=============                                                         |  18%
  |                                                                            
  |=============                                                         |  19%
  |                                                                            
  |==============                                                        |  19%
  |                                                                            
  |==============                                                        |  20%
  |                                                                            
  |==============                                                        |  21%
  |                                                                            
  |===============                                                       |  22%
  |                                                                            
  |================                                                      |  23%
  |                                                                            
  |=================                                                     |  24%
  |                                                                            
  |==================                                                    |  26%
  |                                                                            
  |===================                                                   |  26%
  |                                                                            
  |===================                                                   |  27%
  |                                                                            
  |===================                                                   |  28%
  |                                                                            
  |====================                                                  |  28%
  |                                                                            
  |====================                                                  |  29%
  |                                                                            
  |=====================                                                 |  30%
  |                                                                            
  |======================                                                |  31%
  |                                                                            
  |======================                                                |  32%
  |                                                                            
  |=======================                                               |  33%
  |                                                                            
  |========================                                              |  34%
  |                                                                            
  |========================                                              |  35%
  |                                                                            
  |=========================                                             |  35%
  |                                                                            
  |=========================                                             |  36%
  |                                                                            
  |==========================                                            |  37%
  |                                                                            
  |===============================                                       |  45%
  |                                                                            
  |================================                                      |  45%
  |                                                                            
  |=====================================                                 |  53%
  |                                                                            
  |=======================================                               |  55%
  |                                                                            
  |=======================================                               |  56%
  |                                                                            
  |========================================                              |  57%
  |                                                                            
  |=========================================                             |  58%
  |                                                                            
  |==========================================                            |  60%
  |                                                                            
  |===========================================                           |  61%
  |                                                                            
  |============================================                          |  63%
  |                                                                            
  |==============================================                        |  66%
  |                                                                            
  |================================================                      |  69%
  |                                                                            
  |=================================================                     |  71%
  |                                                                            
  |==================================================                    |  71%
  |                                                                            
  |==================================================                    |  72%
  |                                                                            
  |===================================================                   |  72%
  |                                                                            
  |====================================================                  |  74%
  |                                                                            
  |======================================================                |  77%
  |                                                                            
  |======================================================                |  78%
  |                                                                            
  |=======================================================               |  78%
  |                                                                            
  |=======================================================               |  79%
  |                                                                            
  |========================================================              |  80%
  |                                                                            
  |=========================================================             |  81%
  |                                                                            
  |=========================================================             |  82%
  |                                                                            
  |===========================================================           |  84%
  |                                                                            
  |===========================================================           |  85%
  |                                                                            
  |============================================================          |  86%
  |                                                                            
  |=============================================================         |  87%
  |                                                                            
  |==============================================================        |  88%
  |                                                                            
  |===============================================================       |  90%
  |                                                                            
  |===============================================================       |  91%
  |                                                                            
  |================================================================      |  91%
  |                                                                            
  |=================================================================     |  93%
  |                                                                            
  |==================================================================    |  94%
  |                                                                            
  |===================================================================   |  95%
  |                                                                            
  |===================================================================   |  96%
  |                                                                            
  |======================================================================| 100%
moco_mapping <- merge(moco_data, moco_tracts, by.x = "CensusTract", by.y = "GEOID")
# Rename columns
moco_mapping <- rename(moco_mapping, lat = INTPTLAT)
moco_mapping <- rename(moco_mapping, long = INTPTLON)
# Convert columns to numeric from characters
moco_mapping$lat <- as.numeric(moco_mapping$lat)
moco_mapping$long <- as.numeric(moco_mapping$long)
# Create the Leaflet map
map <- leaflet (moco_mapping) |>
  addProviderTiles("Esri.NatGeoWorldMap") |># Add basemap tiles
  setView(lng = -77.2405, lat = 39.1547, zoom = 10)|>
  addCircles(
 data = moco_mapping)
Assuming "long" and "lat" are longitude and latitude, respectively
# Set initial view (adjust as needed) 
print(map)

Overlay with internet lack rates map on Tablaeu (put final link here) and add interactivity

Summary 1. Does it Impact x 2. Does it impact y 3. Does it impact z 4. Implications/What Comes Next