Visualization of Chicago Crimes Dataset
Added on 2022-11-28
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Project Name: Statistical Analysis and Visualization
Task: Conduct Visualization of the Chicago Crimes Dataset and Report On
the Results?
Student Name:
Lecturer:
School:
Course Name:
Unit Code:
Due Date:
Task: Conduct Visualization of the Chicago Crimes Dataset and Report On
the Results?
Student Name:
Lecturer:
School:
Course Name:
Unit Code:
Due Date:
Dashboard
The following dashboard outlines the summary of the results obtained from our visualization
project:
The following dashboard outlines the summary of the results obtained from our visualization
project:
Introduction
Background
In today’s society, we can only understand with little extent the effect of crime on the society.
Most of the paper focus on the relationship between crime and several other factors such as
economic or psychological consequences of crime.
Several studies attempt to explain what triggers an individual to engage in criminal activities. In
a journal article published in Jama Network on the factors that are posited to trigger violent
domestic crimes, the authors note that, “...Absolute and relative risks of violence are increased
in patients with psychotic disorders, but the contribution of triggers for violent acts to these risks
is uncertain” [1]. Moreover, patients who are diagnosed with schizophrenia spectrum aa well as
bipolar disorders tend to have more records of criminal convictions when compared to the
criminal record convictions of the general population. In contrast to this supposition, another
author argues that, a people who commit crime do so because it is all they want to do and it’s a
matter of choices [2].
Crime in Chicago
Illinois, Chicago features among the top 20 states with most violent crimes in the United States
recording up to 1097 cases in a list where Missouri has the most violent crimes i.e. 2082 [3]. In
relation to this statistics, a considerable amount of national attention has been drawn towards
Chicago in the recent years given that, “Chicago remains more dangerous than most other large
cities in the U.S” [4]. As such, statistics indicate that 68% of adult residents in Chicago would
prefer that the police to increase the time they spend in their area which is relatively higher than
statistics recorded in other areas where only a maximum of 54% of “Fragile community”
residents nationally would like police to increase time spent in their neighborhoods [4].
The question of crime in Chicago is quite disturbing to most of the locals. In particular,
approximately 47% of black residents in Chicago’s fragile communities report that they have
either witnessed or been in a crime situation [4].
By 2016, Chicago saw a spike in gun related violence which were mostly concentrated in:
Austin, Garfield Park, North and South Lawndale, Englewood, and West Pullman neighborhoods
[5]. In their article, Stef and Sykes note that factors such as Racial segregation, wealth inequality,
Background
In today’s society, we can only understand with little extent the effect of crime on the society.
Most of the paper focus on the relationship between crime and several other factors such as
economic or psychological consequences of crime.
Several studies attempt to explain what triggers an individual to engage in criminal activities. In
a journal article published in Jama Network on the factors that are posited to trigger violent
domestic crimes, the authors note that, “...Absolute and relative risks of violence are increased
in patients with psychotic disorders, but the contribution of triggers for violent acts to these risks
is uncertain” [1]. Moreover, patients who are diagnosed with schizophrenia spectrum aa well as
bipolar disorders tend to have more records of criminal convictions when compared to the
criminal record convictions of the general population. In contrast to this supposition, another
author argues that, a people who commit crime do so because it is all they want to do and it’s a
matter of choices [2].
Crime in Chicago
Illinois, Chicago features among the top 20 states with most violent crimes in the United States
recording up to 1097 cases in a list where Missouri has the most violent crimes i.e. 2082 [3]. In
relation to this statistics, a considerable amount of national attention has been drawn towards
Chicago in the recent years given that, “Chicago remains more dangerous than most other large
cities in the U.S” [4]. As such, statistics indicate that 68% of adult residents in Chicago would
prefer that the police to increase the time they spend in their area which is relatively higher than
statistics recorded in other areas where only a maximum of 54% of “Fragile community”
residents nationally would like police to increase time spent in their neighborhoods [4].
The question of crime in Chicago is quite disturbing to most of the locals. In particular,
approximately 47% of black residents in Chicago’s fragile communities report that they have
either witnessed or been in a crime situation [4].
By 2016, Chicago saw a spike in gun related violence which were mostly concentrated in:
Austin, Garfield Park, North and South Lawndale, Englewood, and West Pullman neighborhoods
[5]. In their article, Stef and Sykes note that factors such as Racial segregation, wealth inequality,
increased number of gangs alongside the inability of local law authorities to solve crimes have
among the key factors that have fueled the ever increasing incidences of gun violence epidemic
in the City [6].
Relationship Between Crime and Other Issues in The Society
To understand the concept of crimes in the society, let us first explore the theorized relationships
that exist between crime and issues related with life in a given society including: poverty,
unemployment rate, economic growth, income inequality, etcetera.
Crime and Poverty
Past studies related to the relationship between crime and poverty have been attributed as
phenomenal by both sociologists, humanists, and historians alike. Throughout history as well as
the world’s numerous societies, “...there has always been a traditional measure of deviance
through relative income gaps. Both poverty and crime as well as their connections are heavily
weighed topics of political and social discourse” [7].
According to Cuthbertson, in the United Kingdom, poor persons have twice the probability of
being attacked by buglers or rapists with the probability going up to thrice as likely to be victims
of attacks, robbery and car crime. These statistics are justified by the fact that approximately
three and a half more criminals live in the 20% most deprived areas compared to the 20% less
deprived areas [8]. In an article by Mohammed Imran on whether poverty leads to crime, the
author notes that, “positive co-integrating of the relationship between poverty and property crime
shows that poverty ultimately leads property crime in long run in the USA” [9]
Crime and Economic growth
When the aspect of crime is often examined, the question as to whether it affects a region’s
economic growth usually crops up. Claudio Detotto and Edoardo Otranto correctly identify
crime as some form of tax that is levied on a country’s or state’s entire economy in that crime
acts as a sure way to discourage any form of domestic or foreign investments [10].
From an economic point of view, Becker (1968) posits that using the utility theory, the choice of
an individual to take part in crime can be analyzed. Generally, the theory utilizes the hypothesis
which assumes that an individual is a rational utility which decides whether or not they want to
participate in a given criminal activity through conducting weightage of the pros and cons that
among the key factors that have fueled the ever increasing incidences of gun violence epidemic
in the City [6].
Relationship Between Crime and Other Issues in The Society
To understand the concept of crimes in the society, let us first explore the theorized relationships
that exist between crime and issues related with life in a given society including: poverty,
unemployment rate, economic growth, income inequality, etcetera.
Crime and Poverty
Past studies related to the relationship between crime and poverty have been attributed as
phenomenal by both sociologists, humanists, and historians alike. Throughout history as well as
the world’s numerous societies, “...there has always been a traditional measure of deviance
through relative income gaps. Both poverty and crime as well as their connections are heavily
weighed topics of political and social discourse” [7].
According to Cuthbertson, in the United Kingdom, poor persons have twice the probability of
being attacked by buglers or rapists with the probability going up to thrice as likely to be victims
of attacks, robbery and car crime. These statistics are justified by the fact that approximately
three and a half more criminals live in the 20% most deprived areas compared to the 20% less
deprived areas [8]. In an article by Mohammed Imran on whether poverty leads to crime, the
author notes that, “positive co-integrating of the relationship between poverty and property crime
shows that poverty ultimately leads property crime in long run in the USA” [9]
Crime and Economic growth
When the aspect of crime is often examined, the question as to whether it affects a region’s
economic growth usually crops up. Claudio Detotto and Edoardo Otranto correctly identify
crime as some form of tax that is levied on a country’s or state’s entire economy in that crime
acts as a sure way to discourage any form of domestic or foreign investments [10].
From an economic point of view, Becker (1968) posits that using the utility theory, the choice of
an individual to take part in crime can be analyzed. Generally, the theory utilizes the hypothesis
which assumes that an individual is a rational utility which decides whether or not they want to
participate in a given criminal activity through conducting weightage of the pros and cons that
results in engaging the crime [11]. In the paper, the authors argue that, “...the damage caused by
crime affects the individual, communities and society welfare negatively, which can hinder the
creation and maintenance of a developed and well-functioning country economy.” [11]
Crime and Unemployment rate
Another aspect that we seek to examine is the relationship between crime and unemployment
rate. Amongst many scholars, the relationship between lack and readiness to commit crime is
often a positive one. In a paper on the effect of unemployment on United States crime rates, it is
noted that the effect of enumerated attributes such as unemployment rate on crime rates are
positive using both simple and multiple linear regression models [12].
In this regard, it is crucial that we understand the relationship between steady income and the
incentive to commit crime. In doing so, one can draw conclusions ads to whether wealthy parts
of a city are more or less likely to have more incidences of crime or even wealthy and not so
wealthy states.
Objective of Study
Given the above introduction, we can subsequently draw this study’s objectives. Therefore, by
the end of our study we aim to:
i. Explore the crime trends between 2008 and 2018
ii. Examine the visual relationship between crime and various factors such as
unemployment, economic growth, and poverty
iii. Explore the trend of crime alongside these factors between the years 2008-2018.
To enable us address our study objective we will seek to answer the following questions using
evidence from our data exploration and analysis.
Study Questions
i. What is the trend of crime across the focus years i.e. 2008-2018?
ii. Does unemployment rate affect crime rates in Chicago?
iii. Does Crime rates affect economic growth in Chicago?
iv. Is there a visible distribution in unemployment rates across the communities in Chicago
city?
v. Is there a visible distribution of poverty levels across different communities?
crime affects the individual, communities and society welfare negatively, which can hinder the
creation and maintenance of a developed and well-functioning country economy.” [11]
Crime and Unemployment rate
Another aspect that we seek to examine is the relationship between crime and unemployment
rate. Amongst many scholars, the relationship between lack and readiness to commit crime is
often a positive one. In a paper on the effect of unemployment on United States crime rates, it is
noted that the effect of enumerated attributes such as unemployment rate on crime rates are
positive using both simple and multiple linear regression models [12].
In this regard, it is crucial that we understand the relationship between steady income and the
incentive to commit crime. In doing so, one can draw conclusions ads to whether wealthy parts
of a city are more or less likely to have more incidences of crime or even wealthy and not so
wealthy states.
Objective of Study
Given the above introduction, we can subsequently draw this study’s objectives. Therefore, by
the end of our study we aim to:
i. Explore the crime trends between 2008 and 2018
ii. Examine the visual relationship between crime and various factors such as
unemployment, economic growth, and poverty
iii. Explore the trend of crime alongside these factors between the years 2008-2018.
To enable us address our study objective we will seek to answer the following questions using
evidence from our data exploration and analysis.
Study Questions
i. What is the trend of crime across the focus years i.e. 2008-2018?
ii. Does unemployment rate affect crime rates in Chicago?
iii. Does Crime rates affect economic growth in Chicago?
iv. Is there a visible distribution in unemployment rates across the communities in Chicago
city?
v. Is there a visible distribution of poverty levels across different communities?
vi. Does poverty show any relationship with crime rates in Chicago?
vii. Is there any correlation between the attributes in the dataset and the category of crimes?
In the course of our analysis we hope to unravel more insightful relationships between crime and
other factors, all of which will be reported in the results section.
Data
Given the nature of this study, we will use a secondary data source to conduct our exploratory
visual analysis. In particular, we will use two datasets. One for basic analysis and another for
advanced analysis. Ideally we will conduct the following activities for basic and advanced
visualization.
This project utilizes data obtained from Kaggle website as well as that scrapped from the city of
Chicago data repository. Basically, “The dataset reflects reported incidents of crime (with the
exception of murders where data exists for each victim) that occurred in the City of Chicago
from 2001 to 2017, as for data records of the year 2018, we scrap it from the city of Chicago data
repository. However, the whole dataset can be extracted from the Chicago Police Department’s
CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the
privacy of crime victims, addresses are shown at the block level only and specific locations are
not identified” [13].
Original Dataset
The following information was obtained from the visualization plan we had prepared earlier.
Generally, the dataset had 6,906, 330 observations and 22 attributes including observation ID.
The attributes in the data are:
ID - Unique number identifying the crime record.
Case Number – A unique incident number which is recorded by the Chicago Police Department
(Records Division Number)
Date – Specific date and sometimes time in which the crime occurred.
Block – a prepared address where the crime occurred which places the incident on a block same
as the true address.
vii. Is there any correlation between the attributes in the dataset and the category of crimes?
In the course of our analysis we hope to unravel more insightful relationships between crime and
other factors, all of which will be reported in the results section.
Data
Given the nature of this study, we will use a secondary data source to conduct our exploratory
visual analysis. In particular, we will use two datasets. One for basic analysis and another for
advanced analysis. Ideally we will conduct the following activities for basic and advanced
visualization.
This project utilizes data obtained from Kaggle website as well as that scrapped from the city of
Chicago data repository. Basically, “The dataset reflects reported incidents of crime (with the
exception of murders where data exists for each victim) that occurred in the City of Chicago
from 2001 to 2017, as for data records of the year 2018, we scrap it from the city of Chicago data
repository. However, the whole dataset can be extracted from the Chicago Police Department’s
CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the
privacy of crime victims, addresses are shown at the block level only and specific locations are
not identified” [13].
Original Dataset
The following information was obtained from the visualization plan we had prepared earlier.
Generally, the dataset had 6,906, 330 observations and 22 attributes including observation ID.
The attributes in the data are:
ID - Unique number identifying the crime record.
Case Number – A unique incident number which is recorded by the Chicago Police Department
(Records Division Number)
Date – Specific date and sometimes time in which the crime occurred.
Block – a prepared address where the crime occurred which places the incident on a block same
as the true address.
IUCR - An Illinois Uniform Crime Reporting code which has direct linkage to the Primary Type
and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e.
Primary Type - The primary description of the IUCR code.
Description - The secondary description of the IUCR code, a subcategory of the primary
description.
Location Description – provides basic description of the location where the crime took place.
Arrest –a binary entry taking two entries where True indicates that an arrest was made in
relation to the incident while false indicates no arrest was made.
Domestic - a binary entry taking two entries where True indicates the crime committed is
domestic related and false it was not domestic related.
Beat – an entry showing the beat in which the crime occurred. By defining a beat, we imply, “...
the smallest police geographic area where each beat has dedicated police beat car. Three to five
beats make up a police sector, and three sectors make up a police district.” The Chicago Police
Department has 22 police districts/Communities. See the beats at
https://data.cityofchicago.org/d/aerh-rz74.
District/Community – an entry which shows the district in which the crime occurred. More
information on the districts/communities can be obtained from
https://data.cityofchicago.org/d/fthy-xz3r.
Ward – a ward is a City Council district in which the reported crime supposedly occurred. Also
see more on wards at https://data.cityofchicago.org/d/sp34-6z76.
Community Area – code which shows the community area in which the incident took place.
Generally, Chicago has 77 known community areas. To explore more on communities navigate
to https://data.cityofchicago.org/d/cauq-8yn6.
FBI Code – shows the classification of the reported crime as defined by the FBI's National
Incident-Based Reporting System (NIBRS).
X Coordinate – identifies a specific location’s x coordinate in which the crime occurred using
the “State Plane Illinois East NAD 1983 projection. In reality, this location is partially different
and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e.
Primary Type - The primary description of the IUCR code.
Description - The secondary description of the IUCR code, a subcategory of the primary
description.
Location Description – provides basic description of the location where the crime took place.
Arrest –a binary entry taking two entries where True indicates that an arrest was made in
relation to the incident while false indicates no arrest was made.
Domestic - a binary entry taking two entries where True indicates the crime committed is
domestic related and false it was not domestic related.
Beat – an entry showing the beat in which the crime occurred. By defining a beat, we imply, “...
the smallest police geographic area where each beat has dedicated police beat car. Three to five
beats make up a police sector, and three sectors make up a police district.” The Chicago Police
Department has 22 police districts/Communities. See the beats at
https://data.cityofchicago.org/d/aerh-rz74.
District/Community – an entry which shows the district in which the crime occurred. More
information on the districts/communities can be obtained from
https://data.cityofchicago.org/d/fthy-xz3r.
Ward – a ward is a City Council district in which the reported crime supposedly occurred. Also
see more on wards at https://data.cityofchicago.org/d/sp34-6z76.
Community Area – code which shows the community area in which the incident took place.
Generally, Chicago has 77 known community areas. To explore more on communities navigate
to https://data.cityofchicago.org/d/cauq-8yn6.
FBI Code – shows the classification of the reported crime as defined by the FBI's National
Incident-Based Reporting System (NIBRS).
X Coordinate – identifies a specific location’s x coordinate in which the crime occurred using
the “State Plane Illinois East NAD 1983 projection. In reality, this location is partially different
from the actual location due to partial redaction.” It however falls on the same block as the actual
location.
Y Coordinate - identifies a specific location’s y coordinate in which the crime occurred using
the “State Plane Illinois East NAD 1983 projection. In reality, this location is partially different
from the actual location due to partial redaction.” It however falls on the same block as the actual
location.
Year – indicates the year in which the crime occurred.
Updated On – gives the recent Date and time when the given record was updated
Latitude – this gives latitude value of the crime’s location. This might be slightly different from
the actual location given that it is obtained through partial redaction but nevertheless lies on the
same block as the actual incident location.
Longitude - this gives the longitude of the crime’s location. This might be slightly different from
the actual location given that it is obtained through partial redaction but nevertheless lies on the
same block as the actual incident location.
Location - exact location in which the crime occurred, it gives both the latitude and longitude
allowing for exact mapping and conduction of several geographic operations on the Chicago data
portal. This location is might be different from the actual location for partial redaction. It
nevertheless falls on the same block.
Economic and Crimes data
The crimes economic data is obtained contains 10 attributes with 78 observations including:
Community Area, Community Area Name, Assault (Homicide), Firearm-related, Below Poverty
Level, Crowded Housing, Dependency, No High School Diploma, Per Capita Income,
Unemployment. This dataset is obtained from:
https://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/37256/versions/V1
Basic visualization
Under basic visualization, we will explore trend of different reported crimes over the time-period
specified in the preceding section. In addition, we will explore the distribution of various aspects
as presented in the dataset. The objective of basic visualization is to enable us understand the
location.
Y Coordinate - identifies a specific location’s y coordinate in which the crime occurred using
the “State Plane Illinois East NAD 1983 projection. In reality, this location is partially different
from the actual location due to partial redaction.” It however falls on the same block as the actual
location.
Year – indicates the year in which the crime occurred.
Updated On – gives the recent Date and time when the given record was updated
Latitude – this gives latitude value of the crime’s location. This might be slightly different from
the actual location given that it is obtained through partial redaction but nevertheless lies on the
same block as the actual incident location.
Longitude - this gives the longitude of the crime’s location. This might be slightly different from
the actual location given that it is obtained through partial redaction but nevertheless lies on the
same block as the actual incident location.
Location - exact location in which the crime occurred, it gives both the latitude and longitude
allowing for exact mapping and conduction of several geographic operations on the Chicago data
portal. This location is might be different from the actual location for partial redaction. It
nevertheless falls on the same block.
Economic and Crimes data
The crimes economic data is obtained contains 10 attributes with 78 observations including:
Community Area, Community Area Name, Assault (Homicide), Firearm-related, Below Poverty
Level, Crowded Housing, Dependency, No High School Diploma, Per Capita Income,
Unemployment. This dataset is obtained from:
https://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/37256/versions/V1
Basic visualization
Under basic visualization, we will explore trend of different reported crimes over the time-period
specified in the preceding section. In addition, we will explore the distribution of various aspects
as presented in the dataset. The objective of basic visualization is to enable us understand the
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