The Data-Driven Guide to Crime in Milwaukee

The Data-Driven Guide to Crime in MilwaukeeWe explore over 600,000 incidents to reveal the intricacies of crime in one of America’s most dangerous citiesJUSTIN OLSONBlockedUnblockFollowFollowingMar 20Milwaukee at Night.

Photo by Kayle KaupangerMilwaukee is the largest city in Wisconsin and home of Harley Davidson Motor Company, The Milwaukee Art Museum, and is well-known for its Breweries.

But more importantly, it is notorious for having high levels of crime.

Milwaukee has been ranked as one of the most dangerous cities in America.

Crime analytics websites indicate that Milwaukee is more dangerous than 96–97% of the United States and more dangerous than 99% of Wisconsin.

Utilizing the publicly available WIBR Crime Data from The City of Milwaukee Open Data Portal, I capture and evaluate 666,790 crime incidents considered Group A Offenses that occurred from March 2005 through December 2018.

To the best of my knowledge, this work is the first public exploration and analysis of this information.

This is a comprehensive guide which includes: I) a detailed assessment of the relationship between crime rates and time, II) an evaluation of weapon used in crimes, and finally, III) a geospatial analysis that demonstrates where crime has occurred across the city.

Disclaimer: The following data and figures represent crimes that were reported.

According to The Pew Research Center, most crimes are not reported to the police (here).

Thus, care should be taken when interpreting the results.

Time-Based VisualizationsWhen Crimes OccurThe following results are indicative of when the crimes were reported, not when the crimes were committed.

There is likely to be variability between when the crime occurred and when it was reported, please keep this in mind while reading.

Daily Crime Reporting Peaks at 4:00 pmAccording to Total Crime Reports by Hour of the Day in Milwaukee 2005–2018 (above), crime rates are at their lowest in the early morning between 2:00 am and 6:00 am, a time when many individuals may be sleeping.

Between 6:00–8:00 am, when many people wake up, we see a rapid increase in crime reports.

Crime reporting then remains elevated throughout the day, reaching its maximum at 4:00 pm.

In Crime Type by Hour of the Day, theft accounts for the majority of crimes reported between 8:00 am to 6:00 pm.

Crime reports for criminal damage, locked vehicle entry, and vehicle theft share a similar pattern, with a sharp spike in reports occurring at 8:00 am.

Unlike other crime patterns that peak in the morning or mid-day, assault offense and robbery reporting are low in the morning and peak in the late evening.

The above figure indicates a slight variation in crime reports across the week.

To test whether the amount of crime reported is related to the day of the week, a one-way analysis of variance (ANOVA) was performed on the data.

The test yielded a p-value of 0.

287, which did not break the pre-defined significance threshold (p < 0.


Thus, the number of crimes reported is not related to the day of the week.

Crime Rates Across the YearIt is a well-known fact that crime rates change with the seasons (read more here & here).

Additionally, locations that experience the greatest changes in weather also experience a more drastic increase in property-related offenses in the summer months (read more here).

However, these ‘seasonal’ changes in crime rate appear to be completely explained in terms of social interactions (read more here).

Thus, we should be mindful that changes in crime rates are unlikely to be due directly to changes in weather or temperature.

Total Crime Rates by Month in Milwaukee (2006–2008) demonstrates a strong relationship between the total number of reported crimes and the month of the year.

A low in crime reports occurred in February and the high appears in July and August.

Let’s get an idea for how individual crimes contribute to this trend:In Crime Rates by Month for Milwaukee, we develop an idea for how individual crimes fluctuate across the months.

Theft, assault offense, criminal damage, burglary, vehicle theft, and robbery peak in July and August, while locked vehicle entry peaks between September and October.

In order to examine fluctuations in crime rate occurring in-between each month, here is a visualization with finer granularity:How to Read the Figure: the columns and rows are grouped into months and years, respectively (see the top and right graph headings).

The small individual columns labeled on the bottom of the graph each represents the day of the week.

The individual rows labeled on the bottom of the graph represent the week of the month.

Each small colored square represents a single day and is colored according to the total amount of crime reports made that day.

This heatmap enables the visualization of trends at a week-by-week and day-by-day level.

The seasonal crime peak in July and August appear to be the result of consistent levels of crime across these two months, except in the year 2014 where the peak occurred in late July and early August.

For nearly every month, the monthly minimum value (the darkest purple square) falls within the first week of the month, and this trend holds true for the 2005–2013 data (unpublished results).

Total Reported Crime by Day of the Month confirms the trend we observed in the previous figure, with monthly lows typically occurring on the fourth day of the month, closely followed by the second.

While crime reporting is highly variable, it generally increases across the month.

A Downward Trend in CrimeThere has been a steady decrease in total crime reporting shortly after its peak in 2006.

In 2018, the total reported crime was down nearly 40% compared to 2006 levels.

However, this trend is not unique to Milwaukee.

According to The Pew Research Center, crime levels in the United States have been falling drastically since the early 1990s (read more here).

In Total Crime Reports per Year by Crime Type Crimes, we see a clear and steady decrease in theft and criminal damage across time.

Conversely, the number of reports of assault offense has increased since 2006, when total crime reporting was much higher.

Despite substantial changes in the total amount of crime reported, sexual offense, arson, and homicide levels appear constant over the years.

Weapons-based FindingsWeapon UseOut of the 667,025 crimes reported considered in this analysis, 277,580 reported weapon use.

However, in over 100,000 of these cases, the weapon used was classified as ‘unknown’.

This leaves approximately 175,000 cases of confirmed weapon use to analyze.

In order to identify the prevalence of weapon use by weapon type, 915 different classifications for ‘weapon used’ were condensed into like groupings and the results were filtered yield weapons used in 100 or more incidents between 2005 and 2018.

Total Weapon Use in Crime for Milwaukee 2005–2018, shows that the top 3 weapons used are ‘hands’, ‘handgun’, and ‘gun’.

To investigate weapon use in relation to crime type, weapons were plotted in a bar graph according to their record of use in crime:To be concise, only weapons used in 1,000 or more incidents were included.

The weapons used for homicide, locked vehicle entry, and vehicle theft do not make the list due to the limited number of incidents.

In Weapon Use by Crime Type, ‘hands’ are the weapon used most frequently in assault offense, burglary, sex offense, and theft.

’Handgun’ has been the primary weapon used in robbery and is the second-most weapon used in assault offenses involving weapons.

A Milwaukee city street.

Photo by Lucas LudwigVisualizing location-based DataIn order to conduct a geospatial analysis of crime, Milwaukee crime data for the year 2018 was selected and cleaned the data to remove missing and incomplete location values.

The data was then exported location data to Texas A & M GeoServices, who donated their world-class, state-of-the-art geocoding services to this project.

The calculated latitude and longitude coordinates were received from Texas A & M GeoServices and the results were combined with the existing data.

Then, location-based (geospatial) crime maps of Milwaukee were created.

Note: the location data may represent where the crime occurred or where the crime was reported.

Identifying crime ‘Hotspots’To develop our intuition for areas where many crimes occurred in 2018, a density-based map was created in which the area is divided into hexagons with a radius of 0.

5 miles (0.

8047 Km).

Each hexagon is color-coded according to crime density, the where lowest-density regions are white and the highest-density regions are purple:Density map of crime reported in Milwaukee in 2018.

Note: not all data is visible.

Click here to interact with the map and explore the full data set.

Click here to interact with a 3-dimensional version of the map.

Crime rates tend to increase as we move towards the center of the city.

In particular, two continuous high-density (purple) regions stand out, one slightly north-west of the center of the city, and the other slightly south-west of the center.

To better visualize the prevalence of crime by crime type, a mapping was produced with the hexagons colored according to the crime most prevalent in that area:Prevalence of Crime by Crime Type for Milwaukee in 2018.

Hexagons are colored according to the crime that is most prevalent within it.

Interact with the map here.

In the above mapping, we see that assault offense is the most prevalent crime across Milwaukee for 2018.

We also notice that locked vehicle entry is prevalent on the east side of the city, above and below the Port of Milwaukee.

Identifying Location-based ClustersPotentially the most meaningful analysis we can conduct is to identify specific regions that experience the highest amounts of crime.

While our density map approximates this, I approached this question in a more scientific manner.

In order to identify location-based clusters (groupings) of crime, the supervised machine learning algorithm: Ordering points to identify the clustering structure (OPTICS) was implemented.

OPTICS is a density-based clustering algorithm that allows us to accurately identify clusters, even though geographic features such as roads, lakes, and neighborhoods may influence where crime has occurred.

Read more about OPTICS here & here.

Points with low reachability distance (located in ‘valleys’) are grouped together into clusters (represented by color).

High-density regions were searched on the basis of containing 1,000 or more crimes (minPts = 1000) that occurred within close reachability distance to one another (contrast parameter xi = 0.

0037) were identified.

OPTICS was set to identify clusters of 1,000 or more crimes occurring The reachability plot and convex cluster hulls plots that justify our clustering selection are available above and below, respectively.

A summary of the 2018 crime data’s spatial distribution.

Finally, we plot the clusters to a map of Milwaukee:The results of OPTICS-defined clusters mapped to Milwaukee.

Visit the interactive map here.

The above figure displays four OPTICS-defined crime clusters in Milwaukee for 2018.

Cluster 1 is comprised of faint maroon points and contains all of the points analyzed.

Note, not all points are visible from this image, as this image is focused to emphasize the 3 clusters of interest (red, orange, and yellow).

The red cluster represents the area where nearly 1,800 crimes occurred, the orange area encapsulates the area where over 2,500 crimes took place, and the yellow area encapsulates where ~5,100 crimes happened (see Table 1 for details).

The location icons represent the approximate centers for each cluster.

To give one a better idea of where these central points are located, centers were matched to a local identifier and the results are available in Table 1.

Table 1: Clusters, number of crime incidents for 2018, & local identifier representing the cluster center.

For a map view, click the cluster number here: 1, 2, 3, & 4.

ConclusionThis analysis of over 600,000 crimes reported in Milwaukee between 2005 and 2018 indicates that documented crime has been aggressively declining over the past thirteen years, largely due to decreases in theft.

However, despite this trend reports of assault have been increasing.

Historically, crime demonstrates a yearly low in February and peaks in July and August.

Twenty-four hour trends in reported crime indicate elevated levels between 8:00 am and 5:00 pm, while no relationship bewteen crime and day of the week was observed.

Geospatial analyses map 2018 crime data to Milwaukee and demonstrate that assault is the most prevalent crime across the majority of the city.

Finally, we report on three high-crime regions of Milwaukee as identified by OPTICS clustering.

Milwaukee Skyline at Sunset.

Photo Credit: Steve.

Photo modified to fit the page.

AcknowledgmentsA sincere thank you to Charin Polpanumas for his mentorship in data science and review of this project (check out his phenomenal work here).

Thank you to Texas A & M Geoservices for contributing their geocoding services to this project.

Article by Justin OlsonEmail: jsolson4@wisc.

eduFind the code in my GitHub Repository.

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