Crime Analysis & Safety Report - City Des Peres, MO

Okay, based on the provided crime data and my knowledge base, here's an analysis presented as a crime data expert would deliver: *Crime Data Analysis for an Unidentified Missouri City** The dataset reveals a total crime count of 156 incidents within a specific geographic area identified by the GEOID "16000US2919270." This GEOID corresponds to a location within the state of Missouri (based on the "29" in the GEOID). Without additional data linking the GEOID to a specific city, I can only provide a general analysis. *Crime Category Breakdown:** The most prevalent crime category is property crime, accounting for 131 incidents. Within this category, Larceny/Theft Offenses are the most frequent (101 incidents), followed by Stolen Property Offenses (27 incidents). Motor Vehicle Theft and Destruction/Damage/Vandalism of Property are relatively low, each with only 1 incident. Burglary/Breaking & Entering also has a low count of 1 incident. Assault is the second most prevalent crime category, with 11 incidents, all classified as Assault Offenses. The "others" category accounts for 14 incidents. Embezzlement is the most frequent subcategory within "others" (10 incidents), followed by Counterfeiting/Forgery and Fraud Offenses, each with 2 incidents. *Inferences and Potential Insights:** The high proportion of Larceny/Theft Offenses within property crime suggests potential issues related to petty theft, shoplifting, or theft from vehicles. The significant number of Stolen Property Offenses could indicate an active market for stolen goods within or near this area. The low incidence of violent crimes like assault is a positive indicator, but the property crime rate warrants attention. The embezzlement cases suggest potential white-collar crime issues within the community. *Need for Further Data:** To provide a more comprehensive analysis, the following information is crucial: **City Name:** Identifying the city associated with the GEOID is essential for context. **Population:** Knowing the population allows for calculating crime rates per 100,000 residents, which is a standardized measure for comparing crime levels across different areas. **Median Income:** This provides socioeconomic context. Areas with lower median incomes may experience higher rates of certain types of crime. **Crime Rate per 100k:** This is the standardized measure for comparing crime levels across different areas. **Safety Score/Grade:** A safety score or grade (if available from a source like Niche or AreaVibes) would provide a relative assessment of safety compared to other locations. **Violent Crime Rate:** This is the number of violent crimes per 100,000 residents. **Property Crime Rate:** This is the number of property crimes per 100,000 residents. **Crime Map Data:** Visualizing crime incidents on a map would help identify hotspots and patterns. **Zip Codes Data:** Knowing the zip codes within the GEOID would allow for more granular analysis. With this additional data, I could calculate crime rates, compare them to state and national averages, identify trends, and provide more targeted recommendations for crime prevention strategies.