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Crime is a common social problem in the modern human societies. It has a lot to do with economy, culture, politics, technology, and people’s happiness. In this project, you will be provided the crime data in the DC area from 2008 to 2017. More complete data can be downloaded from the above website. You can play with these data and uncover much underlying information using data mining techniques. In the following, let us give you some explanations about the data.
All statistics presented here are based on preliminary DC criminal code offense definitions. All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications.
On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.
Feature description:
1) NEIGHBORHOOD_CLUSTER
– what neighborhood cluster the case belongs to
– Example: cluster 21
2) CENSUS_TRACT
part of block group index Example: 008702
3) offensegroup
– what offense group the case belongs to
– Example: property
4) LONGITUDE
– longitude
– Example: -77.0035742966363
5) END_DATE
– what date the case ended at
– Example: 2017-04-29T08:00:23.000
6) offense-text
– text form offense info
– Example: theft f/auto
7) SHIFT
– the shift of the case report time
– Example: day, evening, midnight
8) YBLOCK
– block y index
– Example: 138139
9) DISTRICT
– district index
– Example: 5
10) WARD
– one kind of geographic info
– Example: 5
11) YEAR
– year
– Example: 2017
12) offensekey
– offense group | offense
– Example: property|theft f/auto
13) BID
one kind of geographic info
Examples: noma, adams morgan, downtown 14) sector
– sector index
– Example: 5D1
15) PSA
– Police Station Area index
– Example: 502 16) ucr-rank
– UCR-Rank (crime severity rank) of 1-9
– Example: 7
17) BLOCK_GROUP
– block group index
– Example: 008702 2
18) VOTING_PRECINCT
– one kind of geographic info
– Example: precinct 75
19) XBLOCK
– block x index
– Example: 399690
20) BLOCK
– block info of the case
– Example: 150 - 299 block of q street ne
21) START_DATE
– case start date
– Example: 2017-04-29T01:30:14.000
22) CCN
– Criminal Case Number
– Example: 17070672
23) OFFENSE
– what kind of offense
– Example: theft f/auto
24) OCTO_RECORD_ID
Office of the Chief Technology Officer (OCTO) record id Example: 17070672-01 25) ANC
– one kind of geographic info
– Example: 5E
26) REPORT_DAT
– case report date
– Example: 2017-04-29T13:49:31.000Z
27) METHOD
– what method is used in the case
– Examples: gun, others
28) location
– (latitude, longitude)
– Example: "38.911121322949178,-77.003576581965632" 29) LATITUDE
– latitude
– Example: 38.9111135327066
Supplementary materials:
You may also want to know the relationship between the criminal circumstances and the economics in DC. Here we also provide you the housing data in DC with geographic information and other housing related information. You can combine the two datasets by connecting their geographic information and time information. Then you will find the relationship between the crimes and the housing prices. This may help you to dig into more details about the economic behavior and the social behavior. In the following, we will show you the feature description of the housing data.
‘DC_Properties.csv’:
1) BATHRM
– Number of Full Bathrooms
– Example: 4 2) HF_BATHRM
– Number of Half Bathrooms (no bathtub or shower)
– Example: 0 3) HEAT
Heating
Example: Warm Cool 4) AC
– Cooling
– Example: Y
5) NUM_UNITS
– Number of Units
– Example: 2.0
6) ROOMS
– Number of Rooms
– Example: 8
7) BEDRM
– Number of Bedrooms
– Example: 4 8) AYB
– The earliest time the main portion of the building was built
– Example: 1910.0 9) YR_RMDL
– Year structure was remodeled
– Example: 1988.0 10) EYB
– The year an improvement was built more recent than actual year built
– Example: 1972 11) STORIES
– Number of stories in primary dwelling
– Example: 3.0 12) SALEDATE
– Date of most recent sale
– Example: 2003-11-25 00:00:00
13) PRICE
– Price of most recent sale
– Example: 1095000.0
14) QUALIFIED
Qualified
Example: Q
15) SALE_NUM
– Sale Number
– Example: 1
16) GBA
– Gross building area in square feet
– Example: 2522.0
17) BLDG_NUM
– Building Number on Property
– Example: 1
18) STYLE
– Style
– Example: 3 Story
19) STRUCT
– Structure
– Example: Row Inside
20) GRADE
– Grade
– Example: Very Good
21) CNDTN
– Condition
– Example: Good
22) EXTWALL
– Extrerior wall
– Example: Common Brick
23) ROOF
– Roof type
– Example: Built Up
24) INTWALL
– Interior wall
– Example: Hardwood
25) KITCHENS
Number of kitchens
Example: 2.0
26) FIREPLACES
– Number of fireplaces
– Example: 5
27) USECODE
– Property use code
– Example: 24
28) LANDAREA
– Land area of property in square feet
– Example: 1680
29) GIS_LAST_MOD_DTTM
– Last Modified Date
– Example: 2018-07-22 18:01:43
30) SOURCE
– Raw Data Source
– Example: Residential
31) CMPLX_NUM
– Complex number
– Example: 1066.0
32) LIVING_GBA
– Gross building area in square feet
– Example: 888.0
33) FULLADDRESS
– Full Street Address
– Example: 1748 SWANN STREET NW
34) CITY
– City
– Example: WASHINGTON
35) STATE
– State
– Example: DC
36) ZIPCODE
Zip Code
Example: 20009.0 37) NATIONALGRID
– Address location national grid coordinate spatial address
– Example: 18S UJ 23061 09289 38) LATITUDE
– Latitude
– Example: 38.91468021 39) LONGITUDE
– Longitude
– Example: -77.04083204
40) ASSESSMENT_NBHD
– Neighborhood ID
– Example: Old City 2
41) ASSESSMENT_SUBNBHD
– Subneighborhood ID
– Example: 040 D Old City 2 42) CENSUS_TRACT – Census tract
– Example: 4201.0
43) CENSUS_BLOCK
– Census block
– Example: 004201 2006 44) WARD
– Ward (District is divided into eight wards, each with approximately 75,000 residents)
– Example: Ward 2
45) SQUARE
– Square (from SSL)
– Example: 0152
46) X
– longitude
– Example: -77.04042907495098
47) Y
latitude
– Example: 38.914881109044266 48) QUADRANT
– City quadrant (NE,SE,SW,NW)
– Example: NW