# How to clean/analyze relative time series data

I'm relatively new to data science, and I decided to stretch a bit and try a project with time series data. I downloaded the Human Activity Recognition from Continuous Ambient Sensor Data Data Set, and read the first file into a Pandas dataframe.

That dataset contains relative time data:

   lastSensorEventHours  lastSensorEventSeconds  lastSensorDayOfWeek
0                  10.0                 38464.0                  4.0
1                  10.0                 38465.0                  4.0
2                  10.0                 38578.0                  4.0
3                  10.0                 38582.0                  4.0
4                  10.0                 38582.0                  4.0


I've done some work with absolute time series--for example, analyzing stock data, using the time/date data as the index. With this, I'm not even sure where to start. I'm thinking to group into last sensor event length of time, but I don't know how that could be valuable.

Can anyone recommend some methods for how to tackle this data as a time series problem?