I have multiple dataframes each representing traffic speed for each day of the year (366 dataframes for 366 days of the year). The raws of the dataframe are timestamp from 00:00 to 23:55 at 5 minute intervals and the columns are mileposts at 0.5 mile intervals and the entries are speed of traffic corresponding to the specific time and milepost.
I want to group days of similar traffic conditions to examine daily traffic patterns/variations, which is standard for traffic analysis at a macro level, e.g., examining traffic patterns during weekdays and weekends.
To do this, I will have to measure similarity of the dataframes and apply clustering algorithms. Any idea on how to calculate similarity of dataframes and cluster them? Any R package that can do this?