Example 1

You can use the dataset by filtering the data and plotting the trends and proportions. This can allow you to ask questions about a larger picture rather than just a single month.

To illustrate this, we tried answering a simple question What are the different offenses listed and which offenses were the most common cause of complaints and arrests over the whole time period?

We filter the dataset and visualise it using Tableau.

You can interact with the following visualisation and fiddle around with it. You can filter for specific offenses or see the proportions for a specific month or set of months/years.

It is super exciting, because this allows us to make meaning out of the data in a new light. Give it a try!

These graphs offer a visual overview of arrest patterns recorded in the police ledger. The pie chart illustrates the total number of arrests during the documented period, while the line graph tracks how arrest numbers fluctuated for different crimes over time.

From these visualizations, it is clear that "drunkenness (simple)" and "noisy and disorderly persons" were the two most common reasons for arrests and complaints in North End during this time period. This observation raises several important questions:

• Why was drunkenness such a heavily policed offense in North End at the time?
• What kinds of behavior were classified as "noisy and disorderly" by the local police?
• Why did this category represent such a significant focus of policing?
• How did officers distinguish between "drunkenness" and "noisy and disorderly persons" when recording arrests and complaints?

These are just a few of the many questions prompted by the data. We encourage the users to explore further using the category and date filters located in the top left corner of the visualizations.

For more inspiration, check out our other example too.