These examples show made-up data (except figure 2) to help you understand the reports. We’re only showing the made-up absolute visitor numbers (the orange charts) in this page to help you learn. We don't share absolute visitor numbers in the reports.
Gaps and spikes
You might see data gaps for some categories in your region. These gaps are intentional and happen because the data doesn’t meet the quality and privacy threshold—when there isn’t enough data to ensure anonymity.
Figure 1. The privacy threshold removes days with low visitors
Figure 1 shows what happens when the available data for a day (the orange chart) doesn’t meet the privacy threshold. On these days, the report doesn’t include the calculation for that day (the blue graph) so you see a gap.
When one (or more) of the categories has gaps, a report shows the following:
- An asterisk (*) next to a category name means the percentage change is the last-recorded date and not the report date.
- A Not enough data for this date message.
You should treat gaps as true unknowns and don't assume that a gap means places weren’t busy.
Spiky graphs show large day-to-day changes. In many regions, you can see this clearly in the Parks category—visitors to parks are heavily influenced by the weather. Consider affirming this with other data sources that show temperature, precipitation, and wind speeds for the same period. Because park visits are normally very variable, you can expect more dramatic changes.
Expectations
Vacations and public holidays can help you understand what your community looks like when people don’t go to places of work.
Figure 2. How a public holiday can appear similar to community responses to COVID-19
In figure 2, you can see that March 12 was a widely celebrated public holiday in this region. Workplace and Residential changes are a little different from the community’s response to COVID-19 but give an idea of the scale of the change. You’ll need to apply your local knowledge, but holidays provide a very specific point of comparison
Small residential changes
The Residential category shows a change in duration—the other categories measure a change in total visitors. Because people already spend much of the day at places of residence (even on workdays), the capacity for change isn’t so large.
Figure 3. There are only 24 hours in a day, so percentage changes are limited
In figure 3, the orange chart shows the average duration (hours) spent in places of residence. People typically work for 8 hours a day. Because there are only 24 hours in a day, the largest change possible on a working day might only be +50% and even less on weekends.
You shouldn’t compare the change in Residential with other categories because they have different units of measurement.
Weekends
Remember that these mobility reports show relative changes, and not absolute visitors or duration. For example, if few people normally visit places of work on a Sunday, you wouldn’t expect to see large changes to Sunday visitors as your community responds to COVID-19.
Figure 4. Lower weekend visitors to places of work, show as smaller changes
In figure 4, the orange chart shows (made-up) visitor numbers and the blue graph shows how total visitors compare to the baseline for that day of the week. As the weekend visitors decrease to more realistic values, you can see the following happen:
- The relative change becomes smaller—shown as the 3 blue peaks.
- Even though there are less people visiting places of work for the last 3 weekends, the change is still lower.
The graph doesn’t show that more people are working weekends than weekdays. Only that the change from normal is smaller.
Be mindful that not everyone works Monday to Friday, with some regional differences in workweeks and some people working on weekends.