A series of interactive charts exploring crime data for the USA.
This page showcases some recent data visualisation work we have done at the Economics Observatory. We are committed to an approach that is based on accuracy, openness, and transparency. We believe this is a critical ingredient for both economic research and effective policy design. Here at ECO, we want to keep learning, improving and innovating in the way we present our data.
All these visualisations are interactive. Please use this touchscreen (or your mouse) to explore the charts and learn about how they were designed and built.
Figure 1: Economic metrics, by US state
Source: FRED
This first chart plots a range of economic metrics over a state map of the US (see Figure 1). Using the dropdown menu, you can toggle between measures and see the trends across the country. Note the economic might of California (home to Silicon Valley and several wealthy cities) in comparison to states like Louisiana and Mississippi in the South.
Figure 2: Crime statistics, by US state
Source: FBI, 2019
Next, we show a map of different crimes across the country. Again, you can toggle between the crime types using the dropdown menu to see which type of offences are found most frequently in each state. Alaska and New Mexico stand out in terms of violent crime, but Louisiana has the highest rate of homicide (based on FBI data from 2019). Note: we used 2019 data to avoid the effects of Covid-19 on crime.
Figure 3: Crime rates vs income, by US state
Sources: FRED, FBI
What about plotting the data against each other? This final chart combines the datasets and plots different crime type rates (y axis) against a state's median household income (x axis). The idea here is to get a picture of how relative prosperity and crime rates/types might be correlated.
By toggling through the crime types, you can find outliers. For example, both Alaska and Hawaii appear to have surprisingly large arson rates.
Of course, there are numerous factors that affect crime. This is simply one example of how we can use data visualisation to spot patterns.
Where can I find out more?
- All the code and underlying data can be found via Joshua Hellings' GitHub account.
- Our data visualisation principles can be be found here.
