setwd("C:/Users/leoto/OneDrive/Documents/598/Lab 2")
dat<- read.csv("Crime_Data.csv")I downloaded and used the Seattle crime data set from Seattle Open Data. The dataset records and logs unique events of an instance of a crime reported by a member of the community or a detected by a police in the field. The dataset can help us tell the type of reported crimes being committed in Seattle. This information can be used to help the city assess their strategy and resources to combat specific types of crimes.
The dataset ontains over 520,179 rows and 11 columns. Each column signify different variables like Report number, Occured time, Reported time, Primary offense description, Sector, Neighborhood, Occured date, Reported date, Crime subcategory, precint, and Beat.
head(dat)## Report.Number Occurred.Date Occurred.Time Reported.Date Reported.Time
## 1 1.975e+12 12/16/1975 900 12/16/1975 1500
## 2 1.976e+12 01/01/1976 1 01/31/1976 2359
## 3 1.979e+12 01/28/1979 1600 02/09/1979 1430
## 4 1.981e+13 08/22/1981 2029 08/22/1981 2030
## 5 1.981e+12 02/14/1981 2000 02/15/1981 435
## 6 1.988e+13 09/29/1988 155 09/29/1988 155
## Crime.Subcategory Primary.Offense.Description Precinct Sector Beat
## 1 BURGLARY-RESIDENTIAL BURGLARY-FORCE-RES SOUTH R R3
## 2 SEX OFFENSE-OTHER SEXOFF-INDECENT LIBERTIES UNKNOWN
## 3 CAR PROWL THEFT-CARPROWL EAST G G2
## 4 HOMICIDE HOMICIDE-PREMEDITATED-WEAPON SOUTH S S2
## 5 BURGLARY-RESIDENTIAL BURGLARY-FORCE-RES SOUTHWEST W W3
## 6 MOTOR VEHICLE THEFT VEH-THEFT-AUTO WEST M M2
## Neighborhood
## 1 LAKEWOOD/SEWARD PARK
## 2 UNKNOWN
## 3 CENTRAL AREA/SQUIRE PARK
## 4 BRIGHTON/DUNLAP
## 5 ROXHILL/WESTWOOD/ARBOR HEIGHTS
## 6 SLU/CASCADEdim(dat)## [1] 520179 11names(dat)## [1] "Report.Number" "Occurred.Date"
## [3] "Occurred.Time" "Reported.Date"
## [5] "Reported.Time" "Crime.Subcategory"
## [7] "Primary.Offense.Description" "Precinct"
## [9] "Sector" "Beat"
## [11] "Neighborhood"summary(dat)## Report.Number Occurred.Date Occurred.Time
## Min. :2.008e+08 07/01/2017: 199 Min. : 0
## 1st Qu.:2.008e+13 05/26/2017: 193 1st Qu.: 900
## Median :2.012e+13 01/20/2016: 186 Median :1500
## Mean :1.632e+13 12/01/2015: 184 Mean :1359
## 3rd Qu.:2.015e+13 07/19/2018: 183 3rd Qu.:1920
## Max. :2.019e+13 11/25/2015: 182 Max. :2359
## (Other) :519052 NA's :2
## Reported.Date Reported.Time Crime.Subcategory
## 12/31/2008: 238 Min. : 0 CAR PROWL :147379
## 03/31/2014: 196 1st Qu.: 950 THEFT-ALL OTHER : 54076
## 10/10/2018: 196 Median :1407 THEFT-SHOPLIFT : 48303
## 06/18/2018: 195 Mean :1354 BURGLARY-RESIDENTIAL: 46663
## 05/12/2014: 193 3rd Qu.:1817 MOTOR VEHICLE THEFT : 43295
## 07/05/2016: 193 Max. :2359 BURGLARY-COMMERCIAL : 23353
## (Other) :518968 NA's :2 (Other) :157110
## Primary.Offense.Description Precinct Sector
## THEFT-CARPROWL :130510 : 6 M : 42720
## THEFT-SHOPLIFT : 48303 EAST : 77035 U : 40389
## THEFT-OTH : 46978 NORTH :167203 K : 37751
## VEH-THEFT-AUTO : 37645 SOUTH : 73970 B : 37664
## BURGLARY-FORCE-RES: 27903 SOUTHWEST: 48977 D : 35259
## THEFT-BUILDING : 21295 UNKNOWN : 3323 E : 34831
## (Other) :207545 WEST :149665 (Other):291565
## Beat Neighborhood
## K3 : 16822 DOWNTOWN COMMERCIAL: 48615
## U1 : 14880 NORTHGATE : 30649
## M1 : 14472 CAPITOL HILL : 30569
## L2 : 14435 QUEEN ANNE : 27194
## Q3 : 14220 SLU/CASCADE : 23216
## M2 : 14164 UNIVERSITY : 20696
## (Other):431186 (Other) :339240I would like to gain a better understanding on how to create different breakdowns of crimes committed. Many of the primary offense description report similar offenses. I would like to create additional categories to group similar offenses together.
table(dat$Primary.Offense.Description)##
## ADULT-VULNERABLE-FINANCIAL ADULT-VULNERABLE-NEGLECT
## 303 174
## ADULT-VULNERABLE-PHYSICAL ABUSE ARSON-BUSINESS
## 93 150
## ARSON-OTHER ARSON-RESIDENCE
## 462 215
## ARSON-VEHICLE ASSLT-AGG-BODYFORCE
## 249 3628
## ASSLT-AGG-CHILD-BODYFORCE ASSLT-AGG-DV-BODYFORCE
## 142 2738
## ASSLT-AGG-DV-GUN ASSLT-AGG-DV-WEAPON
## 209 3929
## ASSLT-AGG-GUN ASSLT-AGG-POLICE-BODYFORCE
## 1668 88
## ASSLT-AGG-POLICE-GUN ASSLT-AGG-POLICE-WEAPON
## 26 291
## ASSLT-AGG-WEAPON BURGLARY-FORCE-NONRES
## 9641 15033
## BURGLARY-FORCE-RES BURGLARY-NOFORCE-NONRES
## 27903 8320
## BURGLARY-NOFORCE-RES BURGLARY-OTHER
## 18760 148
## BURGLARY-SECURE PARKING-NONRES BURGLARY-SECURE PARKING-RES
## 1151 8760
## CHILD-ABANDON CHILD-ABUSED-NOFORCE
## 334 166
## CHILD-ENDANGERMENT CHILD-HARBOR MINOR
## 553 16
## CHILD-NEGLECT CHILD-OTHER
## 337 4580
## DISORDERLY CONDUCT DUI-DRUGS
## 283 1225
## DUI-LIQUOR ENDANGERMENT
## 11416 142
## GAMBLE-BETTING GAMBLE-OPERATE
## 13 4
## HARBOR - BOATING UNDER INFLUENCE HOMICIDE-NEG-MANS-BODYFORCE
## 109 2
## HOMICIDE-NEG-MANS-GUN HOMICIDE-NEG-MANS-VEHICLE
## 1 2
## HOMICIDE-NEG-MANS-WEAPON HOMICIDE-PREMEDITATED-BODYFORCE
## 1 36
## HOMICIDE-PREMEDITATED-GUN HOMICIDE-PREMEDITATED-WEAPON
## 156 77
## HUMAN-TRAFFICKING-SEX INTERFERE WITH REPORT-DV
## 15 123
## LIQUOR LAW VIOLATION LOITERING
## 1649 90
## NARC-DISTRIBUTE-HALLUCINOGEN NARC-DRUG TRAFFIC LOITERING
## 12 423
## NARC-EQUIPMENT/PARAPHENALIA NARC-FORGERY-PRESCRIPTION
## 1801 300
## NARC-FRAUD-PRESCRIPTION NARC-MANUFACTURE-HALLUCINOGEN
## 113 1
## NARC-MANUFACTURE-METH NARC-MANUFACTURE-OTHER
## 5 45
## NARC-POSSESS-AMPHETAMINE NARC-POSSESS-BARBITUATE
## 395 5
## NARC-POSSESS-COCAINE NARC-POSSESS-HALLUCINOGEN
## 3341 68
## NARC-POSSESS-HEROIN NARC-POSSESS-MARIJU
## 1744 1835
## NARC-POSSESS-METH NARC-POSSESS-OPIUM
## 1550 11
## NARC-POSSESS-OTHER NARC-POSSESS-PILL/TABLET
## 219 352
## NARC-POSSESS-PRESCRIPTION NARC-POSSESS-SYNTHETIC
## 108 15
## NARC-PRODUCE-MARIJU NARC-SELL-AMPHETAMINE
## 106 150
## NARC-SELL-BARBITUATE NARC-SELL-COCAINE
## 1 2887
## NARC-SELL-HALLUCINOGEN NARC-SELL-HEROIN
## 20 628
## NARC-SELL-MARIJU NARC-SELL-METH
## 494 332
## NARC-SELL-OPIUM NARC-SELL-OTHER
## 5 80
## NARC-SELL-PILL/TABLET NARC-SELL-PRESCRIPTION
## 165 30
## NARC-SELL-SYNTHETIC NARC-SMUGGLE-COCAINE
## 12 8
## NARC-SMUGGLE-HEROIN NARC-SMUGGLE-MARIJU
## 1 20
## NARC-SMUGGLE-METH NARC-SMUGGLE-OTHER
## 8 2
## PORNOGRAPHY-OBSCENE MATERIAL PROSTITUTION
## 188 1798
## PROSTITUTION-ASSIST-PROMOTE PROSTITUTION LOITERING
## 143 320
## PROSTITUTION PATRONIZING RAPE-GUN
## 1248 34
## RAPE-OTHER RAPE-STRONGARM
## 44 1383
## RAPE-WEAPON ROBBERY-BANK-BODYFORCE
## 95 133
## ROBBERY-BANK-GUN ROBBERY-BANK-OTHER
## 118 53
## ROBBERY-BANK-WEAPON ROBBERY-BUSINESS-BODYFORCE
## 39 2632
## ROBBERY-BUSINESS-GUN ROBBERY-BUSINESS-WEAPON
## 637 1003
## ROBBERY-OTHER ROBBERY-RESIDENCE-BODYFORCE
## 114 546
## ROBBERY-RESIDENCE-GUN ROBBERY-RESIDENCE-WEAPON
## 300 208
## ROBBERY-STREET-BODYFORCE ROBBERY-STREET-GUN
## 8066 1926
## ROBBERY-STREET-WEAPON SEX ABUSE MINOR-COMMERCIAL
## 1835 64
## SEX ABUSE MINOR-PROMO COMMERC SEXOFF-INDECENT EXPOSURE
## 18 823
## SEXOFF-INDECENT LIBERTIES SEXOFF-LEWD CONDUCT
## 2003 730
## SEXOFF-OTHER SEXOFF-OTHER OBJECT
## 2632 97
## SEXOFF-PEEPER SEXOFF-SODOMY
## 142 344
## THEFT-AUTO PARTS THEFT-AUTOACC
## 1005 8341
## THEFT-BICYCLE THEFT-BOAT
## 11013 194
## THEFT-BUILDING THEFT-CARPROWL
## 21295 130510
## THEFT-COINOP THEFT-LICENSE PLATE
## 280 7523
## THEFT-MAIL THEFT-OTH
## 3542 46978
## THEFT-PKPOCKET THEFT-PRSNATCH
## 2524 558
## THEFT-SHOPLIFT TRESPASS
## 48303 17448
## VEH-THEFT-AUTO VEH-THEFT-BUS
## 37645 2
## VEH-THEFT-HVYEQUIP VEH-THEFT-MTRCYCLE
## 26 2035
## VEH-THEFT-OTHVEH VEH-THEFT-RECREATION VEH
## 52 41
## VEH-THEFT-TRAILER VEH-THEFT-TRUCK
## 419 3075
## WEAPON-CONCEALED WEAPON-DISCHARGE
## 308 975
## WEAPON-POSSESSION WEAPON-UNLAWFUL USE
## 2618 1050I currently do not use any application that records active data. The applications I currently use do not provide a way to export the data so I will need to either record the information manually or find other applications that are able to export datasets.