This report explores changes in unique alleged-offender counts in Victoria over the ten years ending June 2017 to June 2026. Using Victorian crime statistics, four interactive visualisations examine trends across offence categories, changes in alleged-offender counts, differences by Indigenous status, and the composition of offences over time.
The aim is to identify important patterns and communicate them through clear, interactive charts. The figures represent alleged offenders, not proven convictions, and should be interpreted accordingly.
The first visualisation compares three offence subdivisions: assault and related offences, robbery, and burglary/break and enter. It shows the percentage change in unique alleged-offender counts relative to 2017.
Assault and related offences increased by approximately 18.6% between 2017 and 2026. Robbery showed greater year-to-year fluctuations, while burglary/break and enter declined by approximately 22.9%. These patterns suggest that different offence categories have followed substantially different trajectories.
The second visualisation compares percentage changes in alleged-offender counts across 22 offence subdivisions between 2017 and 2026. The horizontal bar chart distinguishes increasing and decreasing categories, making it easier to identify the largest changes.
Cultivating or manufacturing drugs recorded the largest percentage increase at approximately 82.2%, followed by abduction and related offences combined with blackmail and extortion at approximately 60.8%.
In contrast, disorderly and offensive conduct showed the largest decline at approximately 84.0%, while drug use and possession decreased by approximately 30.5%.
These findings demonstrate that changes in alleged-offender counts vary considerably across offence categories. Percentage changes should also be interpreted alongside actual counts, particularly for categories with relatively small starting values.
The third visualisation examines changes in alleged-offender counts among Aboriginal and/or Torres Strait Islander people and non-Indigenous people in Victoria between 2017 and 2026.
The interactive line chart compares trends across the two groups, highlighting differences in their recorded counts over time.
Alleged-offender counts for Aboriginal and/or Torres Strait Islander people increased from 4,452 in 2017 to 5,837 in 2026, representing an increase of approximately 31.1%.
In comparison, non-Indigenous alleged-offender counts decreased slightly from 72,137 in 2017 to 71,422 in 2026, a decline of approximately 1.0%.
Non-Indigenous counts remained substantially higher throughout the period. However, the two groups followed different trends, with Indigenous counts generally increasing while non-Indigenous counts fluctuated.
These figures represent recorded alleged-offender counts rather than population-adjusted offending rates. Differences in population size, reporting practices and other contextual factors must be considered when interpreting the results.
The fourth visualisation examines how the percentage distribution of alleged-offender counts across six major offence divisions changed in Victoria between 2017 and 2026.
The interactive 100% stacked bar chart shows the relative contribution of each offence division to the annual total, allowing comparisons of changes in offence composition over time.
Crimes against the person represented the largest share of alleged-offender counts throughout the period, increasing from approximately 42.0% in 2017 to around 50% in 2026.
Property and deception offences remained another major category, although their relative contribution decreased over the decade.
The composition also fluctuated in 2021 and 2022, with noticeable changes in the proportions of other offences and justice procedures offences.
Overall, the visualisation suggests a gradual shift towards a greater share of alleged-offender counts associated with crimes against the person. These percentages represent the distribution of recorded counts rather than changes in overall crime rates.
This report examined changes in unique alleged-offender counts in Victoria between 2017 and 2026 using four interactive visualisations.
The analysis revealed several important patterns. Assault and related offences increased over the decade, while burglary and drug-related offences showed declines in certain categories. The comparison across offence subdivisions highlighted substantial differences in the direction and magnitude of change.
The analysis by Indigenous status showed different trends between Aboriginal and/or Torres Strait Islander people and non-Indigenous people. Additionally, the composition of alleged-offender counts shifted towards a greater proportion associated with crimes against the person.
Overall, these findings demonstrate the value of interactive visualisations for exploring complex crime statistics. However, alleged-offender counts should not be interpreted as conviction numbers or population-adjusted crime rates.
Data source: Crime Statistics Agency Victoria, Unique Alleged Offenders data tables.
Geographical coverage: Victoria, Australia.
Time period: Years ending June 2017 to June 2026.
Tools: R, RStudio, dplyr, plotly, R Markdown and htmltools.
The original dataset was imported into RStudio and cleaned to extract relevant offence divisions, subdivisions, Indigenous status categories and yearly alleged-offender counts.
The analysis involved calculating percentage changes relative to 2017, comparing offence categories, summarising alleged-offender counts by Indigenous status, and calculating annual percentage distributions across major offence divisions.
Four interactive visualisations were developed using Plotly and incorporated into an HTML report using R Markdown.
The analysis uses recorded alleged-offender counts and does not establish causal relationships. Changes may be influenced by reporting practices, policing activity, population changes and other contextual factors.
Furthermore, percentage comparisons involving categories with small initial counts should be interpreted carefully. Indigenous-status comparisons are based on counts rather than population-adjusted rates, and records with unknown Indigenous status may affect the interpretation of group totals.