Top Banner
CRIME DATA OF CHICAGO CITY
15

Data Management project @ ISB - Crime data of Chicago city

May 12, 2015

Download

Data & Analytics

Rohit Kumar
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: Data Management project @ ISB - Crime data of Chicago city

CRIME DATA OF

CHICAGO CITY

Page 2: Data Management project @ ISB - Crime data of Chicago city

METHODOLOGY USED

• Most of the variable were categorical in nature which are to aggregated to perform the clustering analysis .

• The data is then uploaded into the database and aggregated by DISTRICT , WARD and COMMUNITY AREA

to find the count of crimes by categories, following which the hierarchal clustering is performed

• Tools used :

• TERADATA

• TABLEAU

• SPOTFIRE

Page 3: Data Management project @ ISB - Crime data of Chicago city

CLUSTERING THE CRIME TYPES

CLUSTER-1

SUM_LIQUOR_LAW_VIOLATION

SUM_INTIMIDATION

SUM_PUBLIC_PEACE_VIOLION

CLUSTER-4

SUM_NON_CRIMINAL_SUB_SPECI

CLUSTER-2

SUM_ARSON

SUM_KIDNAPPING

SUM_OTHER_OFFENSE

SUM_CRIMINAL_DAMAGE

SUM_BURGLARY

SUM_SEX_OFFENSE

SUM_OFFENSE_INVOL_CHLDRN

SUM_MOTOR_VEHICLE_THEFT

SUM_OBSCENITY

CLUSTER-3

SUM_NARCOTICS

SUM_PROSTITUTION

SUM_ASSAULT

SUM_WITH_PUBLIC_OFFICER

SUM_ROBBERY

SUM_GAMBLING

SUM_CRIM_SEXUAL_ASSAULT

SUM_HOMICIDE

SUM_BATTERY

SUM_INTER_WITH_PUB_OFFICER

SUM_WEAPONS_VIOLATION

CLUSTER-5

SUM_CRIMINAL_TRESPASS

SUM_STALKING

SUM_OTHER_NARCOTIC_VIOLATION

SUM_PUBLIC_INDECENCY

SUM_DECEP_PRACT

SUM_THEFT

SUM_NON_CRIMINAL

Page 4: Data Management project @ ISB - Crime data of Chicago city

INSIGHT: WHERE MALE TO FEMALE RATIO IS LESS, THERE ARE MORE CRIMES COMMITTED.

MAP SHOWING MALE TO FEMALE RATIOBUBBLE SIZE SHOWS SUM OF TOTAL NUMBER OF CRIMES COMMITTED

Page 5: Data Management project @ ISB - Crime data of Chicago city

MAP SHOWING DISTRIBUTION OF THE HOUSE HOLD INCOME

INSIGHT: WHERE HOUSE HOLD INCOME IS LOW, CRIMES ARE MORE

Page 6: Data Management project @ ISB - Crime data of Chicago city

MAP SHOWING DISTRIBUTION OF THE PER CAPITA INCOME

INSIGHT: WHERE PER CAPITA IS MORE, MORE THEFTS WERE COMMITTED

Page 7: Data Management project @ ISB - Crime data of Chicago city

MAP SHOWING MALE TO FEMALE RATIOBUBBLE SIZE SHOWS SUM OF HOMICIDES WITH DISTRICT NUMBERS

INSIGHT: WHERE MALE TO FEMALE RATIO IS LESS, HOMICIDES ARE MORE

Page 8: Data Management project @ ISB - Crime data of Chicago city

MAP SHOWING MALE TO FEMALE RATIOBUBBLE SIZE SHOWS SUM OF CRIME - PROSTITUTION.

INSIGHT: WHERE MALE TO FEMALE RATIO IS LESS, PROSTITUTION IS MORE

Page 9: Data Management project @ ISB - Crime data of Chicago city

HEAT MAP – DISTRICT

INSIGHT: ON CLUSTERING THE COUNT OF CRIMES, WE OBSERVE THAT DISTRICTS ARE GETTING CLUSTERED INTO 3 CATEGORIES –HIGH, INTERMEDIATE AND LOW. AREA

INSIGHT: WE SEE THAT FEW DISTRICTS IN THE TOP TWO CLUSTERS HAVE INVERSE PATTERN ON FEW VARIABLES.

PARALLEL COORDINATE – DISTRICT

THE SAME PATTERN CAN BE OBSERVED FOR WARD AND COMMUNITY AREA

Page 10: Data Management project @ ISB - Crime data of Chicago city

FUTURE SCOPE OF STUDY

• Application of Dummy Variables can be explored

• Association rules among crime types can be applied

• Location type based clustering can be performed

• Network analysis – To identify (closeness )distance between two crimes

Page 11: Data Management project @ ISB - Crime data of Chicago city

APPENDICES

Page 12: Data Management project @ ISB - Crime data of Chicago city

HEAT MAP – COMMUNITY AREA

Page 13: Data Management project @ ISB - Crime data of Chicago city

HEAT MAP – WARD

Page 14: Data Management project @ ISB - Crime data of Chicago city

PARALLEL COORDINATE – COMMUNITY AREA

Page 15: Data Management project @ ISB - Crime data of Chicago city

PARALLEL COORDINATE– WARD