Project 1
Jayden Brown
2025-10-16
Is there significance in the number of speed humps and the ward they’re located in? Is there a trend in the year the speed humps were built and the ward they are in?
##Introduction For the project 1, I’ll be using the Speed Hump csv data set I got from the data.gov catalog. There are 18 variables total in this data set, but I will be exploring four main variables: ward, created, year created, and count. The goal is to find out if there is significance between the speed humps and what ward of D.C. they are located in. Another objective is to find whether certain wards had more speed humps created in specific years which may indicate changes like fatal events, new school zones, gentrification, and other factors.
##Approach Step 1 will be to get a look at my data set’s structure from top to bottom, double checking for missing values, and inspecting my variables. Step 2 will be using the appropriate functions to answer the questions I formulated for the project while using headers and visualization in relevant areas of the code using graphs, charts, etc to represent trends and patterns.Step 3 is discussion of results and explaining answers to project questions.
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.2
## ✔ ggplot2 4.0.0 ✔ tibble 3.3.0
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
## ── 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 errorslibrary (dplyr)
library (ggplot2)
library (corrplot)## corrplot 0.95 loadedsetwd("C:/Users/Admin/Desktop/DATA101")
dataset <- read.csv("Speed_Humps.csv")Exploring the Dataset
library(ggplot2)
str(dataset)## 'data.frame': 269 obs. of 18 variables:
## $ X : num -8575516 -8574299 -8575170 -8574938 -8575503 ...
## $ Y : num 4720230 4717687 4717584 4717338 4717212 ...
## $ ADDRESS : chr "1500 Blk. Of Roxanna Street " "Aspen st NW 700 & 800 blk (2) 12Ft" "6700 Luzon Ave. NW" "1300 Van Buren Street" ...
## $ WARD : int 4 4 4 4 4 4 4 4 4 4 ...
## $ COUNT_ : int 2 2 1 3 1 4 1 1 1 3 ...
## $ INSTALLYEAR : chr "FY-09" "FY-07" "FY-09" "FY-09" ...
## $ XCOORD : num 396954 397900 397222 397402 396963 ...
## $ YCOORD : num 146888 144917 144838 144647 144549 ...
## $ LATITUDE : num 39 39 39 39 39 ...
## $ LONGITUDE : num -77 -77 -77 -77 -77 ...
## $ GIS_ID : chr "SpeedHump_1" "SpeedHump_2" "SpeedHump_3" "SpeedHump_4" ...
## $ SE_ANNO_CAD_DATA: logi NA NA NA NA NA NA ...
## $ OBJECTID : int 1 2 3 4 5 6 7 8 9 10 ...
## $ GLOBALID : chr "{5E5A2395-83F4-41BF-8B97-438EEA33163D}" "{49286EFC-2D3B-4AB9-9FBE-3CE0836443A8}" "{FFA31925-A5E2-4B07-9CB7-40B31F849AD3}" "{D2A51825-6D4B-4E2F-9632-555596D1F651}" ...
## $ CREATOR : logi NA NA NA NA NA NA ...
## $ CREATED : logi NA NA NA NA NA NA ...
## $ EDITOR : chr "DCGIS" "DCGIS" "DCGIS" "DCGIS" ...
## $ EDITED : chr "2018/01/08 22:18:59+00" "2018/01/08 22:18:58+00" "2018/01/08 22:18:59+00" "2018/01/08 22:18:59+00" ...Question 1: Create a dataset containing the year the speed humps were installed and the ward they were in to see if there’s association between the two.
dataset |>
filter(!is.na(INSTALLYEAR) & !is.na(WARD))## X Y
## 1 -8575516 4720230
## 2 -8574299 4717687
## 3 -8575170 4717584
## 4 -8574938 4717338
## 5 -8575503 4717212
## 6 -8575113 4717028
## 7 -8572381 4716995
## 8 -8574198 4716988
## 9 -8573973 4716963
## 10 -8572703 4716864
## 11 -8573609 4716823
## 12 -8571886 4716511
## 13 -8574100 4716133
## 14 -8573580 4715999
## 15 -8573505 4715968
## 16 -8579418 4715777
## 17 -8572914 4715734
## 18 -8573505 4715711
## 19 -8572270 4715633
## 20 -8574493 4715537
## 21 -8580584 4715490
## 22 -8573147 4715329
## 23 -8573880 4715308
## 24 -8573694 4715287
## 25 -8581687 4715186
## 26 -8570309 4714977
## 27 -8574562 4714932
## 28 -8574789 4714929
## 29 -8572787 4714851
## 30 -8573466 4714824
## 31 -8574472 4714816
## 32 -8573396 4714806
## 33 -8575115 4714781
## 34 -8571097 4714743
## 35 -8571035 4714681
## 36 -8573856 4714628
## 37 -8571040 4714520
## 38 -8573860 4714290
## 39 -8572432 4714259
## 40 -8575291 4714239
## 41 -8573510 4714178
## 42 -8570756 4714146
## 43 -8572421 4714146
## 44 -8574381 4713707
## 45 -8579906 4713399
## 46 -8571109 4713083
## 47 -8574183 4712899
## 48 -8573855 4712576
## 49 -8575545 4712520
## 50 -8574122 4712424
## 51 -8574773 4712404
## 52 -8574653 4712365
## 53 -8574796 4712321
## 54 -8581347 4712303
## 55 -8581469 4712302
## 56 -8581469 4712302
## 57 -8579030 4712278
## 58 -8574329 4712219
## 59 -8574645 4712183
## 60 -8583365 4712049
## 61 -8569669 4711932
## 62 -8569860 4711920
## 63 -8569860 4711920
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## 65 -8575245 4711918
## 66 -8570074 4711906
## 67 -8570203 4711898
## 68 -8567684 4711753
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## 70 -8570453 4711740
## 71 -8570759 4711507
## 72 -8570759 4711507
## 73 -8570759 4711437
## 74 -8570759 4711437
## 75 -8574003 4711225
## 76 -8579492 4711159
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## 78 -8572239 4711122
## 79 -8579554 4711104
## 80 -8579683 4711104
## 81 -8579309 4711104
## 82 -8577583 4711060
## 83 -8579241 4711043
## 84 -8570758 4710942
## 85 -8574291 4710939
## 86 -8574291 4710939
## 87 -8574347 4710813
## 88 -8570638 4710722
## 89 -8570088 4710686
## 90 -8570088 4710686
## 91 -8570036 4710553
## 92 -8569958 4710485
## 93 -8569674 4710393
## 94 -8569806 4710350
## 95 -8569750 4710294
## 96 -8573031 4710253
## 97 -8572781 4710253
## 98 -8573257 4710253
## 99 -8571746 4710102
## 100 -8571746 4710102
## 101 -8571746 4710102
## 102 -8577558 4709959
## 103 -8577146 4709893
## 104 -8572168 4709790
## 105 -8572168 4709790
## 106 -8573042 4709614
## 107 -8572536 4709479
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## 109 -8572504 4709373
## 110 -8572983 4709354
## 111 -8570065 4709298
## 112 -8573062 4709268
## 113 -8573012 4709241
## 114 -8573005 4709191
## 115 -8576596 4709162
## 116 -8572302 4709077
## 117 -8572302 4709077
## 118 -8572452 4709054
## 119 -8570141 4708975
## 120 -8572288 4708906
## 121 -8565081 4708761
## 122 -8575728 4708656
## 123 -8573387 4708585
## 124 -8573709 4708394
## 125 -8573555 4708394
## 126 -8573137 4708372
## 127 -8565267 4708320
## 128 -8571428 4708166
## 129 -8564600 4708146
## 130 -8573601 4708135
## 131 -8571387 4708090
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## 133 -8571428 4707988
## 134 -8568954 4707983
## 135 -8564649 4707908
## 136 -8563972 4707599
## 137 -8563193 4707594
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## 141 -8563825 4707413
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## 145 -8569711 4707137
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## 147 -8568384 4706823
## 148 -8564108 4706817
## 149 -8564281 4706750
## 150 -8564286 4706705
## 151 -8562601 4706676
## 152 -8568976 4706677
## 153 -8566810 4706637
## 154 -8562736 4706503
## 155 -8566609 4706469
## 156 -8566609 4706469
## 157 -8567079 4706464
## 158 -8562296 4706456
## 159 -8562219 4706343
## 160 -8562067 4706342
## 161 -8561838 4706276
## 162 -8563105 4706253
## 163 -8562975 4706224
## 164 -8569935 4706223
## 165 -8563213 4706207
## 166 -8564297 4706199
## 167 -8562566 4706077
## 168 -8563022 4706039
## 169 -8563476 4706039
## 170 -8563195 4706039
## 171 -8563195 4706039
## 172 -8562409 4705690
## 173 -8563088 4705656
## 174 -8563343 4705540
## 175 -8562917 4705528
## 176 -8569263 4705531
## 177 -8565624 4705518
## 178 -8563977 4705473
## 179 -8563897 4705350
## 180 -8563740 4705333
## 181 -8565570 4705308
## 182 -8564009 4705279
## 183 -8563238 4705246
## 184 -8563238 4705246
## 185 -8564524 4704981
## 186 -8563121 4704957
## 187 -8563163 4704934
## 188 -8569966 4704931
## 189 -8569966 4704931
## 190 -8567219 4704904
## 191 -8565170 4704549
## 192 -8565170 4704549
## 193 -8565248 4704549
## 194 -8563916 4704433
## 195 -8570269 4704355
## 196 -8570407 4704325
## 197 -8564297 4704306
## 198 -8564151 4704306
## 199 -8564478 4704280
## 200 -8563699 4704278
## 201 -8564241 4704027
## 202 -8567641 4703983
## 203 -8567430 4703964
## 204 -8567543 4703727
## 205 -8568770 4703659
## 206 -8567050 4703541
## 207 -8568734 4703500
## 208 -8567452 4703499
## 209 -8567679 4703356
## 210 -8569542 4703309
## 211 -8567179 4703304
## 212 -8567400 4703245
## 213 -8566280 4703230
## 214 -8566742 4703148
## 215 -8567900 4703084
## 216 -8566188 4703073
## 217 -8569599 4702969
## 218 -8566419 4702922
## 219 -8565362 4702883
## 220 -8565637 4702718
## 221 -8569265 4702449
## 222 -8567313 4702444
## 223 -8565652 4702432
## 224 -8567464 4702267
## 225 -8566606 4702050
## 226 -8566359 4701977
## 227 -8566435 4701935
## 228 -8566842 4701857
## 229 -8566842 4701857
## 230 -8566852 4701730
## 231 -8566555 4701721
## 232 -8566357 4701685
## 233 -8568500 4701677
## 234 -8566519 4701478
## 235 -8569952 4701261
## 236 -8569952 4701261
## 237 -8569463 4701246
## 238 -8569463 4701246
## 239 -8571197 4701157
## 240 -8569783 4701100
## 241 -8569445 4700947
## 242 -8570438 4700914
## 243 -8569962 4700374
## 244 -8568916 4700029
## 245 -8571762 4700019
## 246 -8568271 4699946
## 247 -8568337 4699873
## 248 -8571366 4699781
## 249 -8571430 4699686
## 250 -8571587 4699448
## 251 -8571807 4699376
## 252 -8571991 4699200
## 253 -8570321 4698756
## 254 -8571020 4698702
## 255 -8570713 4698667
## 256 -8571049 4698587
## 257 -8571321 4698491
## 258 -8571719 4698227
## 259 -8570847 4697782
## 260 -8571219 4697487
## 261 -8571665 4697362
## 262 -8572786 4696922
## 263 -8572344 4696910
## 264 -8572786 4696787
## 265 -8572729 4696760
## 266 -8571508 4696586
## 267 -8572682 4696549
## 268 -8571566 4696482
## 269 -8572591 4696436
## ADDRESS WARD
## 1 1500 Blk. Of Roxanna Street 4
## 2 Aspen st NW 700 & 800 blk (2) 12Ft 4
## 3 6700 Luzon Ave. NW 4
## 4 1300 Van Buren Street 4
## 5 1400-1500 Blk. Underwood Street 4
## 6 1300 Blk Tuckerman St. NW (4) 4
## 7 100 Tuckerman Street NE 4
## 8 700 Blk Tuckerman ST (Rapir 1 speed Hump) 4
## 9 600 Tuckerman St. NW 4
## 10 Unit Blk Sheridan St. NW 4
## 11 400 Sheridan St. NW 4
## 12 300-400 Blk. Of Quackenbos Street NE 4
## 13 Oglethorpe Street 4
## 14 5800 4th St NW 4
## 15 5800 3rd Pl NW (22') 4
## 16 3700 Jenifer St. NW 3
## 17 Unit blk. Of Madison NW 4
## 18 5700 Blk 3rd Pl. NW (2) 4
## 19 5600 Blk. Of 1 st Street NE 4
## 20 900 Longfellow Street 4
## 21 4100 Harrison Street NW 3
## 22 200 Jefferson Street NW 4
## 23 500-600 Jefferson Street NW 4
## 24 400 Blk Jefferson St NW 4
## 25 46th bet Fessenden st NW (3) 12 ft 3
## 26 1100 Blk Galloway St NE btw S. Dakota & Sargeant Rd 5
## 27 900 Blk Hamilton ST NW (2) 4
## 28 1200 Blk. Hamilton Street NW 4
## 29 Farragut Pl NW unit blk (2) 12Ft 4
## 30 300 Blk. Of Gallatin Street NW 4
## 31 5100 9th Street NW 4
## 32 300 Gallatin St. NW 4
## 33 1300 Blk Gallatin ST NW 4
## 34 Farragut Pl. Betw. 6th St & S. Dakota Ave 5
## 35 Farraday Pl btw 6th St & S. Dakota Ave NE 5
## 36 600 Farragut St. NW 4
## 37 Emerson St NE btw 6th St. & 8th St. 5
## 38 500 Blk Decatur St NW (1) 4
## 39 Unit Blk Crittenden St NE 5
## 40 1400 Decatur St. NW 4
## 41 4700 4th Street NW 4
## 42 Unit Blk of Crittenden and Unit Blk of Buchanan, NE 5
## 43 Unit Blk Buchanan St NE 5
## 44 4400 9th St. NW 4
## 45 Upton St & 38th st NW ( 2 cross walks , (2) 12Ft) 3
## 46 7th st NE bet Taylor & Randulph st (2) 12Ft 5
## 47 4000 Blk 8th ST Bet Taylor ST & Randolph ST 4
## 48 600 Blk Quebec PL NW 1
## 49 Hertford PL NW Bet Oak ST & Ogden ST NW (1) 1
## 50 700 Blk Princeton PL NW 1
## 51 3600 Blk 11th ST NW 1
## 52 3614 10th ST NW (1) 1
## 53 3600 Blk 11th st NW (2) 1
## 54 4400 blk Newark St. NW 3
## 55 45th St. NW (22') 3
## 56 45th St. NW (22') 3
## 57 3400-3600 Newark Street NW 3
## 58 800 Otis Place NW 1
## 59 3500 Blk 10th ST NW 1
## 60 5100 Blk Macomb ST NW (1) 3
## 61 Lawrence Street NE bet. 15th and 16th Street 5
## 62 Lawrence Street NE bet. 14th and 15th Street 5
## 63 Lawrence Street NE bet. 14th & 15th Street 5
## 64 Lawrence Street NE bet. 14th and 15th Street 5
## 65 Newton st Nw 1400 blk (2) 12Ft 1
## 66 Lawrence Street NE bet. 13th and 14th Street 5
## 67 1300 Blk Lawrence St. NE btw 13th & 14th 5
## 68 3000 Blk Clinton St. NE 5
## 69 1200-1300 blk. Kearney Street NE BET. 12TH # 13th 5
## 70 1200-1300 blk. Kearney Street NE BET. 12th # 13th 5
## 71 3100 10th St NE bet.Irving and Jackson street 5
## 72 10th Street NE bet. Irving & Jackson St (3100 Blk) 5
## 73 10th Street NE bet. Girard & Irving St (2900-3000 Blk) 5
## 74 2900 & 3000 10th St NE bet. Girard and Irving street 5
## 75 500-600 Blk Gresham Place NW 1
## 76 2800 Block of 36th Street, NW 3
## 77 2800 Block of 36th Street, NW 3
## 78 Girard st., N.E. Bet. North Capitol st. and Franklin st. 5
## 79 3600 Block of Fulton St. between 36th St and 36th Pl 3
## 80 3600 Block of Fulton St. between 36th Pl and Wis Ave. 3
## 81 3500 Block of Fulton Street, NW 3
## 82 2600 & 2700 Blk Woodley Rd NW 3
## 83 2700 Block of 35th Street, NW 3
## 84 2700 Blk 10th St. NE 5
## 85 700 Blk Faimont ST NW 1
## 86 Wallach Pl NW 1300 blk (2) 12Ft 1
## 87 700-900 Block of Euclid Street, NW 1
## 88 1000 Douglas street NE bet. 10th and 12th street 5
## 89 14TH Street NE bet. Montana Ave. & Saratoga Ave. 5
## 90 14TH Street NE bet. Montana Ave. & Saratoga Ave. 5
## 91 Saratoga Ave NE. bet. Brentwood rd & 14th street 5
## 92 2400 Blk 14th ST Bet Downing & Saratoga AV NE (2) 5
## 93 2300 Blk 15th Street NE 5
## 94 14TH Street NE bet. Adams & Downing Place 5
## 95 2300 Blk 14th Street NE 5
## 96 100 Blk Adams St. NW 5
## 97 Unit Blk Adams St. NW 5
## 98 100 Blk Adams St btw 1st & 2nd St NW 1
## 99 300 blk. Of W Street NE 5
## 100 300 W Street NE 4TH & Rhode Island Ave. 5
## 101 300 Blk W Street NE 5
## 102 2400 Kalarama road NW 2
## 103 2200 Kalarama road NW 2
## 104 U Street NE Btw 2nd St. & Summit Pl NE 5
## 105 U Street NE betw, 1st St. & Summit Place NE 5
## 106 Unit Blk T Street NW (12) 5
## 107 Unit BLK Seaton Place NW (3) 12FT 5
## 108 2200 blk S St. Bewteen 22nd & 24th St NE 5
## 109 Lincoln Rd & T ST NE (2) 5
## 110 Unit BLK S Street NW (2) Tables 5
## 111 1800,1900 & 2000 Galludet St NE 5
## 112 100 Blk Randolph Place between 1st & 2nd NW 5
## 113 Unit blk Randolph pl NW (2) 22ft 5
## 114 Unit Blk R Street NW 5
## 115 20th & R Street SE (12) 2
## 116 Unit & 100 BLK Quincy St NE (2) 12FT 5
## 117 Unit Blk Quincy Pl NW (12) 5
## 118 Unit Blk Quincy Pl NE 5
## 119 1800,1900 & 2000 Capitol Ave NE 5
## 120 Unit & 100 BLK Q St NE (2) 22FT 5
## 121 4300 of Polk Street NE 7
## 122 1500 Islamic Way 2
## 123 400 Blk O St. NW 2
## 124 1300 5th St NW 2
## 125 400 Blk N St. NW 2
## 126 Unit - 200 Blk N St. NW 5
## 127 4000-4300 Anacostia Ave 7
## 128 400-600 M St NE 6
## 129 1100 Blk 45 Place St NE 7
## 130 440 M ST NW (12) 2
## 131 600 Orleans place NE 6
## 132 Lyman Place NE bet. 17th and 19th streets 5
## 133 600 morton place, NE 6
## 134 Lang Place NE bet. 17th and 19th street 5
## 135 1000 Blk 45Th St NE 7
## 136 Jay st NE 4900 blk (2) 12Ft 7
## 137 Jay St. NE between 50th Pl & Division Ave 7
## 138 1400 Blk Morse St. NE 5
## 139 1400 Blk Morse NE (22ft) 5
## 140 26th Street Bet. Benning Road & i (Eye) Street, NE (22") 5
## 141 5000-5100 blk. Of Hayes Street NE 7
## 142 Hayes St. NE between 50th Pl. & Division Ave 7
## 143 55th ST Bet James PL & Eastern AV NE (3) 7
## 144 4100 & 4200 Blk Hayes ST NE (6) 7
## 145 1500 Blk Gayles ST NE (1) 22ft 7
## 146 15th Street , F Street & Tenn Ave NE (raised cross walk) 7
## 147 Oklahoma ave Ne 500 blk (3) 12Ft 7
## 148 4900 Blk Fitch Pl NE 7
## 149 500 Blk 48th St NE (4) 7
## 150 48th pl NE 500 blk (4) 12Ft 7
## 151 400 Blk 57th St NE, 7
## 152 400 Blk 20th St NE (12') 7
## 153 3400 Dix St. NE 7
## 154 5600 blk. Of Clay Place 7
## 155 300 36th Street NE 7
## 156 Unit - 100 Blk Darrington Street SW 7
## 157 3300 Clay St NE 7
## 158 300 Blk 59th Street NE 7
## 159 5900 Blk. Of Clay Place NE 7
## 160 6000 Blk Clay Street NE 7
## 161 200 Blk. Of 62th Street NE 7
## 162 200 blk. Of 54th Street NE 7
## 163 200 blk. of 55th Street NE 7
## 164 1400 Blk Constitution Ave NE (12') 6
## 165 5300 & 5400 Blk Blaine St NE 7
## 166 4700 Blk Blaine St NE, 7
## 167 57th Pl NE 200 blk (3) 12Ft 7
## 168 Unit & 100 Blk 55th St NE 7
## 169 5200 Blk Ames St NE 7
## 170 5300 Blk. of Ames Street, NE 7
## 171 5300 Blk. of Ames Street, NE 7
## 172 100 Blk 58th St SE 7
## 173 Unit blk 54th St. SE 7
## 174 Unit blk 53th St. SE 7
## 175 Unit 55th St. SE 7
## 176 200 Blk 18th Street SE 7
## 177 4300 C Street SE 7
## 178 4900 Blk B St SE (2) 7
## 179 200 Blk 50th St SE (2) 7
## 180 5000 Blk Bass Pl SE (2) 7
## 181 300 block of Burns Street, NE 7
## 182 4900 Blk C St SE (3) 7
## 183 5300 blk. Of Bass Place SE 7
## 184 5300 blk. Of Bass Place SE 7
## 185 E st SE bet. Benning rd & Falls Ter (2) 22Ft 7
## 186 5400 D St. SE 7
## 187 54th St between C&D st NE (2) 22Ft 7
## 188 1200-1400 Blk E Street SE (12') 6
## 189 1400 E St. SE 6
## 190 3200 blk. Of E Street SE 7
## 191 700-800 hilltop terrace SE 7
## 192 700-800 Hilltop terrace SE 7
## 193 4300 blk. G Street SE 7
## 194 5000 Blk Hanna PL SE (2) 7
## 195 1300 Blk Potomac Ave SE (22") 6
## 196 1200 Blk Potomac Ave SE 6
## 197 4600 blk H street S.E 7
## 198 4600 Blk H Street SE 7
## 199 1100 blk. Of 45th Place SE (one way street) 7
## 200 5100 Blk H St SE (3) 7
## 201 4600 Hillside Terr. SE 7
## 202 3000 - 3100 blocks of M Street, SE 7
## 203 3100 Blk M Place SE 7
## 204 3000 block N Street SE 7
## 205 2100- 2300 Nicholson Place SE 7
## 206 3200 block Pope Street SE 7
## 207 2200 Blk Prout ST SE (2) 8
## 208 3000 -3100 blocks of O Street, SE 7
## 209 3000 - 3100 blk. of P street SE 7
## 210 1600 blk Fairlawn Av 8
## 211 3200 O St. SE 7
## 212 3100 & 3000 blocks of Q Street, SE 7
## 213 3600 Blk Texas Ave SE 7
## 214 3300-3700- Carpenter st SE 7
## 215 1600 blk. Of 28th Place SE 7
## 216 1600 - 1700 38th street SE 7
## 217 1600 & 1700 Blk 16th ST SE (3) 8
## 218 3500 Blk texas Ave SE 7
## 219 1600-4200 Blks Fort Dupont St SE 7
## 220 1600 Fort Davis Place 7
## 221 18th & Good Hope Rd (2) 8
## 222 32nd st SE bet. Alabama & Park Dr SE (3) 12Ft 7
## 223 1700 40th street SE 7
## 224 2100 Blk 31st Street SE (12') 7
## 225 3600 Blk Suitland Rd SE (3) 7
## 226 3700 Blk Suitland Rd SE (2) 7
## 227 3700 Block of Bangor Street, SE 7
## 228 34th st SE 2300 Blk (2) 12Ft 7
## 229 34th st SE 2300 blk (5) 12Ft 7
## 230 Bangor st SE 3400 blk (1) 22Ft 7
## 231 3600 Blk Bangor St. SE 7
## 232 3600 & 3700 Blk Camden St SE (4) 7
## 233 2400 Blk Wagner ST SE (1) 22FT 8
## 234 2400 blk. Of 36th Place. SE 7
## 235 Morris Rd./Erie St. SE form Pomeroy to Bruce PL. SE 8
## 236 Morris Rd./Erie St. SE from Pomeroy to Bruce PL. SE 8
## 237 Morris Rd./ SE 17th Street to Bruce PL. SE 8
## 238 Morris Rd./ SE 17th Street to Bruce PL. SE 8
## 239 2900 Blk Pomeroy Rd SE (3) 8
## 240 2300 Blk Elvans Rd SE (2) 8
## 241 1700 Blk Gainesville St SE (2) 8
## 242 2400-2500 Pomeroy Rd SE 8
## 243 12th Pl SE 2600 blk (1) 22Ft 8
## 244 1900-2100 Savannah Terr. Se 8
## 245 400 blk-600blk Lebuam st. SE (6) 12ft 8
## 246 3400 Blk 24th ST Se (3) 8
## 247 3400 Blk 23rd ST SE (3) 12 ft 8
## 248 500 blk Labaum st se (3) 12ft 8
## 249 600 Blk Melon St SE 8
## 250 300 Blk Parkland Pl. 8
## 251 300 Raleigh Street SE 8
## 252 3300 Blk Brothers Pl SE (4) 8
## 253 Mississippi Ave from Wheeler Rd to 13th St SE 8
## 254 700 Blk Upsal ST SE (3) 8
## 255 900-1200 Blk Mississippi Ave SE 8
## 256 700 Blk Mississippi AV SE (2) 8
## 257 Mississippi Ave from 6th St to 7th St SE 8
## 258 3800 Blk 4th St SE (1) 22Ft 8
## 259 800 Blk Xenia St SE (3) 8
## 260 600 blk Atlantic st ( 3) 12ft 8
## 261 Brandywine Street SE 8
## 262 Unit Blk. Of Darrington Street SW 8
## 263 4300 blk. Of Halley Terr. SE 8
## 264 100 Blk Elmira St. SW 8
## 265 Unit Blk Elmira St. SW 8
## 266 600 blk Galveston PL se(2) 12ft 8
## 267 Unit Blk Galveston Pl SW 8
## 268 6th St from Atlantic to Galveston St SE 8
## 269 Unit Blk Galveston Pl SW (2) 8
## COUNT_ INSTALLYEAR XCOORD YCOORD LATITUDE LONGITUDE GIS_ID
## 1 2 FY-09 396953.5 146888.4 38.98993 -77.03516 SpeedHump_1
## 2 2 FY-07 397899.5 144917.2 38.97217 -77.02424 SpeedHump_2
## 3 1 FY-09 397221.7 144837.6 38.97145 -77.03206 SpeedHump_3
## 4 3 FY-09 397402.3 144646.9 38.96973 -77.02998 SpeedHump_4
## 5 1 FY-09 396962.6 144548.9 38.96885 -77.03505 SpeedHump_5
## 6 4 FY-08 397265.7 144406.0 38.96756 -77.03155 SpeedHump_6
## 7 1 FY-09 399393.0 144380.5 38.96734 -77.00700 SpeedHump_7
## 8 1 FY-08 397978.4 144375.0 38.96729 -77.02333 SpeedHump_8
## 9 1 FY-09 398153.8 144355.8 38.96711 -77.02130 SpeedHump_9
## 10 3 FY-08 399142.0 144278.4 38.96642 -77.00990 SpeedHump_10
## 11 2 FY-08 398436.9 144247.0 38.96613 -77.01804 SpeedHump_11
## 12 2 FY-09 399777.9 144004.7 38.96395 -77.00256 SpeedHump_12
## 13 2 FY-09 398054.6 143711.8 38.96131 -77.02245 SpeedHump_13
## 14 2 FY-09 398458.9 143608.1 38.96038 -77.01778 SpeedHump_14
## 15 1 FY-08 398517.9 143584.2 38.96016 -77.01710 SpeedHump_15
## 16 1 FY-09 393913.7 143437.8 38.95883 -77.07022 SpeedHump_16
## 17 2 FY-09 398977.5 143402.7 38.95853 -77.01180 SpeedHump_17
## 18 2 FY-08 398517.9 143384.9 38.95837 -77.01710 SpeedHump_18
## 19 1 FY-09 399479.1 143324.0 38.95782 -77.00601 SpeedHump_19
## 20 2 FY-09 397748.1 143250.1 38.95715 -77.02598 SpeedHump_20
## 21 1 FY-09 393006.1 143216.2 38.95682 -77.08069 SpeedHump_21
## 22 2 FY-09 398796.5 143088.4 38.95570 -77.01388 SpeedHump_22
## 23 2 FY-09 398225.4 143072.0 38.95555 -77.02047 SpeedHump_23
## 24 2 FY-08 398370.6 143056.0 38.95541 -77.01880 SpeedHump_24
## 25 3 FY-07 392146.4 142981.6 38.95470 -77.09061 SpeedHump_25
## 26 6 FY-09 401005.9 142815.2 38.95324 -76.98840 SpeedHump_26
## 27 2 FY-07 397694.4 142781.1 38.95293 -77.02660 SpeedHump_27
## 28 1 FY-09 397518.0 142778.5 38.95290 -77.02863 SpeedHump_28
## 29 2 FY-07 399076.2 142717.9 38.95236 -77.01066 SpeedHump_29
## 30 2 FY-09 398548.2 142696.7 38.95217 -77.01675 SpeedHump_30
## 31 1 FY-08 397764.8 142691.0 38.95212 -77.02579 SpeedHump_31
## 32 2 FY-08 398602.0 142683.1 38.95205 -77.01613 SpeedHump_32
## 33 1 FY-08 397264.1 142664.2 38.95187 -77.03156 SpeedHump_33
## 34 3 FY-08 400392.5 142633.6 38.95160 -76.99547 SpeedHump_34
## 35 3 FY-08 400441.2 142585.8 38.95117 -76.99491 SpeedHump_35
## 36 2 FY-08 398244.3 142545.2 38.95080 -77.02025 SpeedHump_36
## 37 4 FY-08 400437.2 142460.7 38.95004 -76.99496 SpeedHump_37
## 38 1 FY-08 398241.2 142283.2 38.94844 -77.02029 SpeedHump_38
## 39 1 FY-08 399353.1 142258.5 38.94822 -77.00746 SpeedHump_39
## 40 1 FY-08 397126.6 142243.4 38.94808 -77.03315 SpeedHump_40
## 41 2 FY-08 398513.5 142195.9 38.94766 -77.01715 SpeedHump_41
## 42 4 FY-09 400657.9 142171.3 38.94744 -76.99241 SpeedHump_42
## 43 1 FY-08 399361.6 142171.2 38.94744 -77.00737 SpeedHump_43
## 44 1 FY-08 397835.2 141830.7 38.94437 -77.02497 SpeedHump_44
## 45 2 FY-07 393532.3 141594.2 38.94222 -77.07460 SpeedHump_45
## 46 2 FY-07 400383.2 141346.5 38.94001 -76.99558 SpeedHump_46
## 47 1 FY-07 397989.5 141203.8 38.93872 -77.02319 SpeedHump_47
## 48 1 FY-07 398244.4 140953.1 38.93646 -77.02025 SpeedHump_48
## 49 1 FY-08 396928.2 140910.1 38.93607 -77.03543 SpeedHump_49
## 50 3 FY-08 398036.9 140835.6 38.93540 -77.02264 SpeedHump_50
## 51 2 FY-07 397529.5 140820.5 38.93527 -77.02849 SpeedHump_51
## 52 1 FY-08 397622.8 140790.2 38.93499 -77.02742 SpeedHump_52
## 53 2 FY-08 397511.3 140756.2 38.93469 -77.02870 SpeedHump_53
## 54 2 FY-09 392409.7 140744.9 38.93456 -77.08755 SpeedHump_54
## 55 2 FY-08 392314.6 140744.7 38.93455 -77.08864 SpeedHump_55
## 56 2 FY-08 392314.6 140744.7 38.93455 -77.08864 SpeedHump_56
## 57 5 FY-09 394214.2 140724.5 38.93439 -77.06673 SpeedHump_57
## 58 2 FY-09 397875.0 140676.4 38.93397 -77.02451 SpeedHump_58
## 59 1 FY-07 397628.8 140648.9 38.93372 -77.02735 SpeedHump_59
## 60 1 FY-08 390837.7 140549.8 38.93278 -77.10567 SpeedHump_60
## 61 2 FY-09 401505.2 140454.1 38.93197 -76.98264 SpeedHump_61
## 62 1 FY-09 401356.3 140444.6 38.93188 -76.98436 SpeedHump_62
## 63 1 FY-09 401356.3 140444.6 38.93188 -76.98436 SpeedHump_63
## 64 1 FY-09 401356.3 140444.6 38.93188 -76.98436 SpeedHump_64
## 65 2 FY-07 397161.7 140443.5 38.93187 -77.03273 SpeedHump_65
## 66 2 FY-09 401189.1 140433.9 38.93179 -76.98629 SpeedHump_66
## 67 2 FY-08 401088.6 140427.4 38.93173 -76.98744 SpeedHump_67
## 68 5 FY-08 403051.0 140315.1 38.93071 -76.96481 SpeedHump_68
## 69 2 FY-09 400894.5 140304.7 38.93062 -76.98968 SpeedHump_69
## 70 2 FY-09 400894.5 140304.7 38.93062 -76.98968 SpeedHump_70
## 71 1 FY-09 400655.7 140124.2 38.92900 -76.99244 SpeedHump_71
## 72 1 FY-09 400655.7 140124.2 38.92900 -76.99244 SpeedHump_72
## 73 2 FY-09 400655.9 140069.6 38.92851 -76.99244 SpeedHump_73
## 74 2 FY-09 400655.9 140069.6 38.92851 -76.99244 SpeedHump_74
## 75 2 FY-08 398129.3 139905.3 38.92702 -77.02157 SpeedHump_75
## 76 1 FY-09 393853.4 139856.5 38.92656 -77.07089 SpeedHump_76
## 77 1 FY-09 393853.4 139856.5 38.92656 -77.07089 SpeedHump_77
## 78 2 FY-09 399503.2 139825.3 38.92630 -77.00573 SpeedHump_78
## 79 1 FY-09 393804.7 139814.2 38.92618 -77.07145 SpeedHump_79
## 80 1 FY-09 393704.9 139814.1 38.92618 -77.07260 SpeedHump_80
## 81 1 FY-09 393996.1 139814.0 38.92618 -77.06924 SpeedHump_81
## 82 2 FY-08 395340.5 139778.3 38.92587 -77.05373 SpeedHump_82
## 83 2 FY-09 394048.6 139766.7 38.92576 -77.06863 SpeedHump_83
## 84 2 FY-08 400656.8 139685.8 38.92505 -76.99243 SpeedHump_84
## 85 1 FY-07 397905.0 139683.6 38.92503 -77.02416 SpeedHump_85
## 86 2 FY-07 397905.0 139683.6 38.92503 -77.02416 SpeedHump_86
## 87 3 FY-09 397861.1 139586.2 38.92415 -77.02467 SpeedHump_87
## 88 2 FY-09 400749.9 139515.4 38.92351 -76.99135 SpeedHump_88
## 89 3 FY-09 401178.2 139487.6 38.92326 -76.98641 SpeedHump_89
## 90 3 FY-09 401178.2 139487.6 38.92326 -76.98641 SpeedHump_90
## 91 3 FY-09 401219.2 139383.9 38.92233 -76.98594 SpeedHump_91
## 92 2 FY-07 401279.6 139330.9 38.92185 -76.98524 SpeedHump_92
## 93 2 FY-08 401501.5 139260.1 38.92121 -76.98269 SpeedHump_93
## 94 1 FY-09 401398.6 139226.6 38.92091 -76.98387 SpeedHump_94
## 95 1 FY-08 401442.3 139182.9 38.92052 -76.98337 SpeedHump_95
## 96 2 FY-08 398885.8 139151.4 38.92023 -77.01285 SpeedHump_96
## 97 2 FY-08 399081.1 139151.1 38.92023 -77.01060 SpeedHump_97
## 98 2 FY-09 398710.2 139151.0 38.92023 -77.01487 SpeedHump_98
## 99 1 FY-09 399886.8 139033.8 38.91917 -77.00131 SpeedHump_99
## 100 3 FY-09 399886.8 139033.8 38.91917 -77.00131 SpeedHump_100
## 101 1 FY-08 399886.8 139033.8 38.91917 -77.00131 SpeedHump_101
## 102 2 FY-09 395359.1 138924.2 38.91817 -77.05352 SpeedHump_102
## 103 2 FY-09 395679.9 138872.9 38.91771 -77.04981 SpeedHump_103
## 104 1 FY-08 399558.5 138791.9 38.91699 -77.00509 SpeedHump_104
## 105 1 FY-08 399558.5 138791.9 38.91699 -77.00509 SpeedHump_105
## 106 3 FY-08 398877.3 138655.2 38.91576 -77.01295 SpeedHump_106
## 107 3 FY-08 399271.5 138550.9 38.91482 -77.00840 SpeedHump_107
## 108 2 FY-09 402326.9 138468.3 38.91408 -76.97317 SpeedHump_108
## 109 2 FY-07 399296.9 138468.1 38.91408 -77.00811 SpeedHump_109
## 110 2 FY-08 398923.3 138453.6 38.91395 -77.01241 SpeedHump_110
## 111 3 FY-09 401196.9 138410.4 38.91356 -76.98620 SpeedHump_111
## 112 1 FY-08 398862.0 138386.7 38.91334 -77.01312 SpeedHump_112
## 113 2 FY-08 398901.1 138365.9 38.91316 -77.01267 SpeedHump_113
## 114 2 FY-08 398906.1 138327.0 38.91281 -77.01261 SpeedHump_114
## 115 4 FY-08 396108.2 138305.5 38.91260 -77.04487 SpeedHump_115
## 116 2 FY-08 399453.6 138238.5 38.91201 -77.00630 SpeedHump_116
## 117 2 FY-08 399453.6 138238.5 38.91201 -77.00630 SpeedHump_117
## 118 1 FY-08 399337.0 138221.1 38.91185 -77.00764 SpeedHump_118
## 119 4 FY-09 401137.4 138159.3 38.91130 -76.98689 SpeedHump_119
## 120 2 FY-08 399465.0 138105.8 38.91081 -77.00617 SpeedHump_120
## 121 2 FY-09 405079.8 137995.4 38.90981 -76.94143 SpeedHump_121
## 122 2 FY-08 396784.6 137912.5 38.90907 -77.03707 SpeedHump_122
## 123 3 FY-09 398608.7 137857.0 38.90857 -77.01604 SpeedHump_123
## 124 2 FY-09 398357.5 137708.9 38.90724 -77.01894 SpeedHump_124
## 125 3 FY-09 398477.3 137708.6 38.90723 -77.01756 SpeedHump_125
## 126 6 FY-08 398803.1 137691.6 38.90708 -77.01380 SpeedHump_126
## 127 10 FY-09 404935.5 137653.1 38.90672 -76.94310 SpeedHump_127
## 128 3 FY-09 400135.1 137531.7 38.90564 -76.99844 SpeedHump_128
## 129 3 FY-09 405455.4 137517.8 38.90550 -76.93710 SpeedHump_129
## 130 1 FY-08 398442.0 137507.7 38.90542 -77.01796 SpeedHump_130
## 131 3 FY-09 400166.4 137473.2 38.90512 -76.99808 SpeedHump_131
## 132 3 FY-09 402063.1 137457.1 38.90497 -76.97621 SpeedHump_132
## 133 3 FY-09 400135.1 137393.6 38.90440 -76.99844 SpeedHump_133
## 134 3 FY-09 402062.8 137390.2 38.90437 -76.97622 SpeedHump_134
## 135 3 FY-09 405417.2 137333.3 38.90384 -76.93755 SpeedHump_135
## 136 2 FY-07 405944.3 137094.1 38.90168 -76.93147 SpeedHump_136
## 137 3 FY-09 406551.8 137090.9 38.90165 -76.92447 SpeedHump_137
## 138 1 FY-08 401410.3 137034.0 38.90116 -76.98374 SpeedHump_138
## 139 1 FY-08 401410.3 137034.0 38.90116 -76.98374 SpeedHump_139
## 140 5 FY-08 402582.3 136976.5 38.90064 -76.97023 SpeedHump_140
## 141 3 FY-09 406059.0 136949.8 38.90038 -76.93015 SpeedHump_141
## 142 3 FY-08 406497.9 136895.9 38.89989 -76.92509 SpeedHump_142
## 143 3 FY-08 406781.9 136871.8 38.89967 -76.92182 SpeedHump_143
## 144 6 FY-07 404839.1 136857.9 38.89956 -76.94421 SpeedHump_144
## 145 1 FY-07 401472.9 136733.8 38.89845 -76.98302 SpeedHump_145
## 146 2 FY-08 401418.1 136649.2 38.89769 -76.98365 SpeedHump_146
## 147 3 FY-07 402507.0 136489.8 38.89625 -76.97110 SpeedHump_147
## 148 1 FY-08 405839.3 136486.8 38.89621 -76.93269 SpeedHump_148
## 149 4 FY-08 405704.1 136435.1 38.89575 -76.93425 SpeedHump_149
## 150 4 FY-07 405700.2 136400.3 38.89543 -76.93429 SpeedHump_150
## 151 2 FY-09 407013.9 136378.3 38.89522 -76.91915 SpeedHump_151
## 152 2 FY-08 402045.8 136376.9 38.89524 -76.97642 SpeedHump_152
## 153 2 FY-08 403733.8 136345.9 38.89495 -76.95696 SpeedHump_153
## 154 2 FY-09 406908.5 136244.3 38.89402 -76.92036 SpeedHump_154
## 155 2 FY-09 403890.5 136215.6 38.89378 -76.95515 SpeedHump_155
## 156 2 FY-09 403890.5 136215.6 38.89378 -76.95515 SpeedHump_156
## 157 2 FY-08 403523.8 136211.5 38.89374 -76.95938 SpeedHump_157
## 158 1 FY-08 407251.7 136207.8 38.89369 -76.91641 SpeedHump_158
## 159 1 FY-09 407311.2 136120.1 38.89290 -76.91572 SpeedHump_159
## 160 1 FY-08 407430.0 136119.7 38.89289 -76.91435 SpeedHump_160
## 161 1 FY-09 407608.6 136068.8 38.89243 -76.91230 SpeedHump_161
## 162 3 FY-09 406620.8 136049.8 38.89227 -76.92368 SpeedHump_162
## 163 2 FY-09 406722.2 136027.6 38.89207 -76.92251 SpeedHump_163
## 164 1 FY-08 401298.3 136024.0 38.89206 -76.98503 SpeedHump_164
## 165 4 FY-09 406537.3 136014.1 38.89195 -76.92464 SpeedHump_165
## 166 2 FY-09 405692.4 136007.0 38.89189 -76.93438 SpeedHump_166
## 167 3 FY-07 407041.3 135914.0 38.89104 -76.91884 SpeedHump_167
## 168 3 FY-09 406686.3 135884.1 38.89078 -76.92293 SpeedHump_168
## 169 2 FY-09 406332.4 135883.9 38.89078 -76.92701 SpeedHump_169
## 170 3 FY-09 406550.8 135883.7 38.89077 -76.92449 SpeedHump_170
## 171 3 FY-09 406550.8 135883.7 38.89077 -76.92449 SpeedHump_171
## 172 2 FY-09 407163.8 135613.1 38.88833 -76.91743 SpeedHump_172
## 173 4 FY-09 406635.1 135586.6 38.88810 -76.92352 SpeedHump_173
## 174 3 FY-09 406436.3 135496.2 38.88728 -76.92581 SpeedHump_174
## 175 4 FY-09 406768.2 135487.6 38.88720 -76.92199 SpeedHump_175
## 176 3 FY-08 401822.4 135486.7 38.88722 -76.97899 SpeedHump_176
## 177 4 FY-08 404658.7 135478.0 38.88713 -76.94630 SpeedHump_177
## 178 2 FY-08 405941.8 135443.7 38.88681 -76.93151 SpeedHump_178
## 179 2 FY-08 406004.2 135348.4 38.88595 -76.93080 SpeedHump_179
## 180 2 FY-08 406127.2 135335.2 38.88583 -76.92938 SpeedHump_180
## 181 2 FY-09 404700.4 135315.3 38.88566 -76.94582 SpeedHump_181
## 182 3 FY-08 405917.4 135293.5 38.88546 -76.93180 SpeedHump_182
## 183 2 FY-09 406518.1 135268.4 38.88523 -76.92487 SpeedHump_183
## 184 2 FY-09 406518.1 135268.4 38.88523 -76.92487 SpeedHump_184
## 185 2 FY-07 405515.7 135061.5 38.88337 -76.93643 SpeedHump_185
## 186 2 FY-09 406609.4 135043.9 38.88321 -76.92382 SpeedHump_186
## 187 2 FY-07 406576.7 135025.9 38.88305 -76.92420 SpeedHump_187
## 188 6 FY-08 401274.7 135021.0 38.88302 -76.98531 SpeedHump_188
## 189 1 FY-08 401274.7 135021.0 38.88302 -76.98531 SpeedHump_189
## 190 3 FY-09 403415.8 135000.9 38.88284 -76.96063 SpeedHump_190
## 191 4 FY-09 405012.7 134726.0 38.88035 -76.94223 SpeedHump_191
## 192 4 FY-09 405012.7 134726.0 38.88035 -76.94223 SpeedHump_192
## 193 2 FY-09 404952.2 134725.8 38.88035 -76.94293 SpeedHump_193
## 194 2 FY-07 405989.8 134636.5 38.87954 -76.93097 SpeedHump_194
## 195 2 FY-08 401038.1 134574.3 38.87900 -76.98804 SpeedHump_195
## 196 2 FY-08 400930.3 134551.1 38.87879 -76.98928 SpeedHump_196
## 197 3 FY-09 405693.3 134537.8 38.87865 -76.93439 SpeedHump_197
## 198 3 FY-09 405806.8 134537.8 38.87865 -76.93308 SpeedHump_198
## 199 3 FY-09 405552.6 134517.3 38.87847 -76.93601 SpeedHump_199
## 200 3 FY-08 406159.1 134516.2 38.87846 -76.92902 SpeedHump_200
## 201 3 FY-09 405737.0 134321.5 38.87671 -76.93388 SpeedHump_201
## 202 3 FY-09 403087.1 134285.6 38.87640 -76.96442 SpeedHump_202
## 203 3 FY-09 403251.7 134270.8 38.87626 -76.96253 SpeedHump_203
## 204 2 FY-09 403163.2 134087.2 38.87461 -76.96355 SpeedHump_204
## 205 4 FY-08 402206.8 134033.9 38.87413 -76.97457 SpeedHump_205
## 206 5 FY-09 403547.9 133942.6 38.87330 -76.95911 SpeedHump_206
## 207 2 FY-07 402234.7 133910.1 38.87302 -76.97425 SpeedHump_207
## 208 4 FY-09 403234.1 133910.1 38.87301 -76.96273 SpeedHump_208
## 209 3 FY-09 403057.4 133798.6 38.87201 -76.96477 SpeedHump_209
## 210 1 FY-07 401604.9 133761.9 38.87168 -76.98151 SpeedHump_210
## 211 4 FY-08 403446.8 133758.5 38.87165 -76.96028 SpeedHump_211
## 212 3 FY-09 403275.1 133712.7 38.87123 -76.96226 SpeedHump_212
## 213 3 FY-09 404148.1 133701.6 38.87113 -76.95220 SpeedHump_213
## 214 6 FY-09 403787.6 133637.4 38.87055 -76.95635 SpeedHump_214
## 215 2 FY-09 402885.5 133587.9 38.87011 -76.96675 SpeedHump_215
## 216 5 FY-09 404220.0 133579.6 38.87003 -76.95137 SpeedHump_216
## 217 3 FY-07 401561.0 133498.3 38.86931 -76.98201 SpeedHump_217
## 218 5 FY-09 404040.1 133462.7 38.86898 -76.95344 SpeedHump_218
## 219 7 FY-09 404864.0 133432.6 38.86870 -76.94395 SpeedHump_219
## 220 2 FY-09 404649.6 133304.8 38.86755 -76.94642 SpeedHump_220
## 221 2 FY-08 401821.3 133094.1 38.86567 -76.97901 SpeedHump_221
## 222 3 FY-07 403343.1 133090.9 38.86563 -76.96148 SpeedHump_222
## 223 2 FY-09 404638.3 133082.2 38.86555 -76.94655 SpeedHump_223
## 224 2 FY-08 403225.1 132953.9 38.86440 -76.96284 SpeedHump_224
## 225 3 FY-07 403894.2 132785.3 38.86288 -76.95513 SpeedHump_225
## 226 2 FY-07 404087.2 132728.9 38.86237 -76.95291 SpeedHump_226
## 227 1 FY-09 404027.7 132696.3 38.86207 -76.95359 SpeedHump_227
## 228 2 FY-07 403710.0 132635.0 38.86152 -76.95725 SpeedHump_228
## 229 5 FY-07 403710.0 132635.0 38.86152 -76.95725 SpeedHump_229
## 230 1 FY-07 403702.7 132536.9 38.86064 -76.95734 SpeedHump_230
## 231 2 FY-08 403933.8 132529.9 38.86058 -76.95468 SpeedHump_231
## 232 4 FY-08 404088.8 132502.0 38.86032 -76.95289 SpeedHump_232
## 233 1 FY-08 402418.0 132495.2 38.86027 -76.97214 SpeedHump_233
## 234 3 FY-09 403962.0 132341.5 38.85888 -76.95435 SpeedHump_234
## 235 1 FY-09 401285.4 132171.5 38.85735 -76.98519 SpeedHump_235
## 236 1 FY-09 401285.4 132171.5 38.85735 -76.98519 SpeedHump_236
## 237 1 FY-09 401666.7 132160.6 38.85726 -76.98080 SpeedHump_237
## 238 1 FY-09 401666.7 132160.6 38.85726 -76.98080 SpeedHump_238
## 239 3 FY-08 400315.3 132090.6 38.85663 -76.99637 SpeedHump_239
## 240 2 FY-07 401417.4 132047.1 38.85623 -76.98367 SpeedHump_240
## 241 2 FY-08 401681.0 131928.0 38.85516 -76.98063 SpeedHump_241
## 242 3 FY-09 400906.6 131902.1 38.85493 -76.98956 SpeedHump_242
## 243 1 FY-07 401278.0 131483.2 38.85115 -76.98528 SpeedHump_243
## 244 4 FY-09 402093.9 131215.1 38.84874 -76.97588 SpeedHump_244
## 245 6 FY-07 399874.3 131207.4 38.84867 -77.00145 SpeedHump_245
## 246 3 FY-08 402596.9 131150.8 38.84816 -76.97008 SpeedHump_246
## 247 3 FY-07 402545.4 131094.3 38.84765 -76.97068 SpeedHump_247
## 248 3 FY-07 400183.1 131022.2 38.84700 -76.99789 SpeedHump_248
## 249 1 FY-08 400133.4 130948.3 38.84634 -76.99846 SpeedHump_249
## 250 3 FY-08 400011.0 130764.1 38.84468 -76.99987 SpeedHump_250
## 251 4 FY-09 399839.1 130708.0 38.84417 -77.00185 SpeedHump_251
## 252 4 FY-08 399695.6 130571.3 38.84294 -77.00351 SpeedHump_252
## 253 1 FY-09 400997.9 130226.0 38.83983 -76.98851 SpeedHump_253
## 254 3 FY-07 400453.0 130184.0 38.83945 -76.99478 SpeedHump_254
## 255 4 FY-09 400692.6 130157.4 38.83921 -76.99202 SpeedHump_255
## 256 2 FY-07 400430.4 130094.9 38.83865 -76.99504 SpeedHump_256
## 257 1 FY-09 400218.7 130020.8 38.83798 -76.99748 SpeedHump_257
## 258 1 FY-08 399908.3 129815.3 38.83613 -77.00106 SpeedHump_258
## 259 3 FY-07 400588.5 129470.0 38.83302 -76.99322 SpeedHump_259
## 260 3 FY-07 400297.8 129240.9 38.83096 -76.99657 SpeedHump_260
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## 263 3 FY-09 399420.8 128792.1 38.82691 -77.00667 SpeedHump_263
## 264 1 FY-09 399075.8 128696.7 38.82605 -77.01064 SpeedHump_264
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## 266 2 FY-07 400072.4 128540.9 38.82465 -76.99917 SpeedHump_266
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## 268 3 FY-09 400027.1 128460.1 38.82392 -76.99969 SpeedHump_268
## 269 2 FY-08 399228.0 128424.5 38.82360 -77.00889 SpeedHump_269
## SE_ANNO_CAD_DATA OBJECTID GLOBALID CREATOR
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## CREATED EDITOR EDITED
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## 269 NA DCGIS 2018/01/08 22:18:58+00dataset2 <- dataset[c("INSTALLYEAR", "WARD")]
dataset2 |>
count(INSTALLYEAR, WARD, sort = TRUE) ## INSTALLYEAR WARD n
## 1 FY-09 7 53
## 2 FY-08 5 29
## 3 FY-09 5 26
## 4 FY-08 7 22
## 5 FY-09 4 16
## 6 FY-07 7 15
## 7 FY-08 4 15
## 8 FY-09 8 15
## 9 FY-07 8 13
## 10 FY-08 8 12
## 11 FY-09 3 10
## 12 FY-07 1 6
## 13 FY-08 1 5
## 14 FY-08 6 5
## 15 FY-09 2 5
## 16 FY-07 4 4
## 17 FY-08 3 4
## 18 FY-07 5 3
## 19 FY-08 2 3
## 20 FY-09 1 3
## 21 FY-09 6 3
## 22 FY-07 3 2Create a table that shows the relationship between year installed and the ward.
table(dataset2$INSTALLYEAR, dataset2$WARD)##
## 1 2 3 4 5 6 7 8
## FY-07 6 0 2 4 3 0 15 13
## FY-08 5 3 4 15 29 5 22 12
## FY-09 3 5 10 16 26 3 53 15Finally, Explore the relationship between the count of speed humps and the wards they’re located.
wardvscount <-
dotchart(table(dataset$COUNT_, dataset$WARD))
## Conclusion In the analysis of my data, using a dotplot, I found that
there is very little to no correlation between the count of speed humps
and the ward they are located in. Since the data on the plot is too
scattered, I cannot claim causation that the ward speed humps are
located in has anything to do with how many speed humps are in their
locations. For the two way table I made to compare the year speed humps
were installed and their respective wards, there is no recognizable
pattern in any of the ward except 7 and 8, especially 7 where a
significant amount of speed humps were installed in 2009. Because of the
lack of pattern and association between the chosen variables, it is
appropriate to conclude there is little to no significance between the
number of speed humps and the ward they’re located. There also is no
visible trend in the year speed humps were installed and the ward they
were built in. In the future, I will pay more attention to each
individual variable. For example, I did not know this dataset only looks
at the years 2007-2009. I also found NA values within my chosen
variables that made it harder to compare my variables to one another. I
did like the website I chose my dataset from and chose the right types
of graphs for plotting my variables by quantitative and categorical.
Citations
Census Reporter (For D.C. wards) https://censusreporter.org/profiles/61000US11002-ward-2-dc/
chatgpt (FOR GRAPHING AND PLOTTING)
data.gov “Speed_Humps.csv” https://catalog.data.gov/dataset/speed-humps-a55ae
Hadley Wickham and Garrett Grolemund. “R for Data Science” https://r4ds.had.co.nz/index.html#welcome