I am really stumped at the moment about how to solve a particular problem. I have many time series like this:
This represents the number of hours a person spends on a website each day throughout the year. Any days where they are not seen to be using the website have zero values, rather than missing values.
What I really want to do is to calculate a metric telling me to what extent there is a consistent "1 hour per day, once per week" pattern, or, say a "10 minutes a day 6 times per week" pattern and I have written some code that produces this pattern. I don't have any background really in machine learning or deep learning, but I have looked into some techniques from spectral analysis and time series. I also found a technique called "Dynamic Time Warping" which I could in theory use to find out how much of a cost there is in mapping this time series onto the "ideal" one (representing the usage patterns I just mentioned).
I tried plotting the periodogram and correlogram, but there seems to be very little correlation indicating periodicity of any kind:
Can anyone shed some light onto how I could use certain techniques to get the information I need, or any introductory texts on periodicity detection or data mining for those who have never really used it before?