This presentation explores trends in recorded offences in Victoria using the Crime Statistics Agency’s Year Ending December 2024 data. We examine how offence counts have evolved over time across major offence divisions, drill into subdivisions and subgroups for key categories, and highlight recent changes such as top-growing subdivisions. We also consider family-incident flags to understand patterns in personal offences. The goal is to provide clear insights into which types of offences are rising or falling, supporting informed discussion and decision-making.
path <- "data/offence.xlsx"
.excel_sheets(path)
to list all
sheet names in the workbook.print(sheets)
to confirm which sheets are available. This
lets us identify the correct sheet (e.g., “Table 01”) for further
reading.read_excel(path, sheet = "<sheet name>")
.We can compute for each Year and Division the total offence count and average (or aggregated) rate. For rate per 100k, it may be more accurate to compute a weighted average based on population, but since ABS already gives rate per 100k for each subgroup, and subdivisions vary in population weight, a simple mean might not reflect total rate. Instead, better to show total counts over years by division, or show the provided rate per 100k aggregated: but since “Rate per 100,000 population” in Table 01 is for that subgroup, summing rates is not directly meaningful. So for trend, use total counts (and optionally plot rate for Division if available separately).
Allow drilling into a single division, e.g., “A Crimes against the person”. You can filter and plot trends for its subdivisions.
For the most recent year, find which Subdivision or Subgroup had the highest counts.
Trends by Offence Division reveal how different categories of crime have evolved over time in Victoria.
“Crimes against the person” shows notable patterns in subdivisions such as Assault and Sexual offences.
Recent year highlights: top subdivisions and subgroups indicate where counts have risen or remained high.
Family Incident Flag analysis uncovers distinctions in personal offences flagged as family-related.
Insights support stakeholders in understanding emerging areas of concern and resource allocation.
Limitations: counts reflect recorded offences only; population changes and reporting behaviour are not adjusted here.