Crime in LA – Looking at Child Kidnappings Around Schools

What kind of crimes target children within 500 meters of schools in settings outside of the home? To look at this question, I began by augmenting the data.

Step 1Augmenting the data

The data set contains lat/lon coordinates for all crimes, so the first thing I needed was the location of all schools in LA. I grabbed this data set from GeoHub (

Step 2Preparing the data in Alteryx

The crime data set contains a list of MO codes for each crime (modus operandi, describing features of the assailant and/or how they carried out the crime). To use this for analysis, these were separated out into different rows, and I created a second table linking each crime ID to a list of MO codes.

For the main crime table itself, just a few adjustments were needed. First, a conversion of dates from strings and the addition of a spatial point.

Finally, the school data set. I created a spatial point for each school and a 500m buffer around it. Once this was done, the 3 tables (crime details 2020-23, crime MO codes, schools) were output and imported into Tableau.

Step 3Joining the spatial elements in Tableau

Before doing any analysis, the tables needed to be joined. The crime and MO tables were joined on the crime ID using a relationship.

For the schools, I used an intersects join on the location point of each crime and the buffer area of the schools. Now, this was going to create multiple joins in the result, so in future steps, I needed to be careful to use a count distinct of crime IDs rather than any regular counts or sums of figures.

Final StepPutting it all together

To narrow the analysis down, I looked only at Central LA areas, for crimes against school-aged children (ages 5-18), crimes committed outside of the home, and for the following specific crimes of concern:

  • Child Stealing
  • Kidnapping
  • Kidnapping (grand attempt)
  • Lewd acts with a child
  • Rape – attempted
  • Rape – forcible
  • Stalking

The first chart I wanted to create was to give an impression of crime density around schools. I used the school buffer zone as a spatial element and the count of crimes in its area as a focal point here.

Next, taking a look at the severity of each crime in terms of weapon use. This might help us narrow down areas that are particularly dangerous. The solid shapes below indicate weapon use. What we see is a loose concentration of weapon use in the middle part of central LA.

Next, racial and age targeting. What is the demographic profile of child crimes in these areas of LA? While the racial demographics may reflect the suburban demographics of each area, one thing to note is that with black/Hispanic children they tend to be affected at a broader range of ages than white children.

I added a few more charts to produce the final dashboard v1.0:

What we can further see from breaking down the crimes by hour of day is that:

  • most child crimes are committed by strangers
  • a disturbing number of rapes are committed and attempted during school hours, begging the question of student safety.

Looking at all 3 maps together, we can also see that there are some areas with low crime counts but those crimes are violent rapes using weapons. This gives us a picture of not just concentration but severity of areas for crime – it may be better to focus resources on these areas rather than the other areas where more crimes occur but with less severity.

The Data School
Author: The Data School