Crime Trends in Victoria (2010–2024)
Srivani Pulla (s4187876)
Load Libraries and Import Datasets
# Load required libraries
library(tidyverse) # Data manipulation and visualization
library(plotly) # Interactive plots
library(lubridate) # Date and time handling
# Set working directory to your assignment folder
setwd("C:/Users/HP/Downloads/Assignment 3 - Storytelling with Open Data/")
# Read all four CSV files
table1 <- read.csv("incidents_by_offence.csv")
table2 <- read.csv("incidents_by_location.csv")
table3 <- read.csv("incidents_by_family_flag.csv")
table4 <- read.csv("incidents_by_charge_status.csv")
Introduction
Crime has a significant impact on
communities, affecting safety, resources, and social well-being. This
project analyzes publicly available data from the Crime Statistics
Agency to explore crime trends in Victoria from 2010 to 2024. Through
interactive visualizations, it examines overall crime patterns, top
offence divisions, regional distributions, family-related incidents, and
charge outcomes. The goal is to present insights in a way that goes
beyond raw numbers, helping the audience understand the social and
regional context behind the data and make informed
interpretations.
Overall Crime Trends (2010–2024)
This line chart
illustrates trends of various crime types in Victoria over time. Some
offences have increased steadily, others decreased, and some remained
stable. Understanding these patterns helps stakeholders identify areas
requiring attention and explore potential links to socio-economic or
legislative changes.
Top 5 Offence Divisions
This bar chart highlights the top
five offence divisions by total incidents. It shows which crimes are
most common in Victoria, helping authorities and communities prioritize
prevention efforts and allocate resources effectively. For example, a
high number of theft offences may suggest the need for community
awareness and prevention programs.
Crime by Region (Table 2)
This treemap illustrates how crime
incidents vary across offence types and regional groups in Victoria. The
size and arrangement of each block highlight which areas and offences
contribute most to overall crime levels. These insights can guide
data-driven policing decisions and help allocate resources more
effectively across different regions.
Family Incident Trends (Table 3)
This plot compares family-related
versus non-family incidents across years. Changes in family-related
incidents may indicate social issues such as domestic stress or gaps in
community support. Tracking these trends helps authorities and
organizations implement better interventions to protect vulnerable
populations.
Charge Status Overview (Table 4)
This stacked bar chart displays the
number of incidents that resulted in charges, offering an overview of
how outcomes differ across offence categories. Although total incident
numbers may vary yearly, the share of cases leading to charges reflects
the effectiveness of law enforcement and highlights areas where further
investigation or legal action may be needed.
Conclusion
This analysis highlights how
visualizing crime data can reveal important patterns and trends in
Victoria over the past decade. By examining offence types, regional
differences, family-related incidents, and charge outcomes, the project
provides a clear picture of how crime has evolved and where attention
may be needed. The findings can support law enforcement, policymakers,
and community organizations in making data-driven decisions. Overall,
the project demonstrates how combining accurate data with clear visual
storytelling can make complex trends understandable and
actionable.