The park dataset contains information corresponding to the check-ins and movement of the visitors of a park during a weekend, in particular the weekend between the 6th and the 8th of June 2014.
A first analysis could include the amount of actions (considering check-ins and movements) and how it varies accross days (Friday 6.010.914, Saturday 9.078.623 and Sunday 10.932.426). However, there is apparently no change regarding their composition, the check-ins lie between 1.2% and 1.4% of the total actions per day, revealing a constant 'intensity' of our customers (Ratio Check-ins vs Movements).
A deeper analysis, shows graphically the paths followed by the visitors, which are on our three cases bounded by the established routes of the park. Given that there are no significant differences we only include one of the plots (Friday)
In addition we can observe an hourly distribution of the actions per day. This analysis shows us some differences between days that would be interesting to analyze in a deeper way. For instance, there is a clear decrease in movements during the lunchtime (we assume) on Fridays and Saturdays but it's not the case in Sundays.
It's worth to mention tha the routes' analysis was made considering a random sample of 10% of the actions on each day given that the whole dataset was too big to be processed entirely.
