Bicycle Rentals

Data Computing

Computing project

In this project, you’ll examine some factors that may influence the use of bicycles in a bike-renting program. The data come from Washington, DC and cover the last quarter of 2014.

We will use the “Trips-history” data file You can access the data like this.

data_site <- 
  "http://tiny.cc/dcf/2014-Q4-Trips-History-Data-Small.rds" 
Trips <- readRDS(gzcon(url(data_site)))

Important: To avoid repeatedly re-reading the files, start the above chunk with {r cache = TRUE} rather than the usual {r}.

The Trips data table is a random subset of 10,000 trips from the full quarterly data. Start with this small data table to develop your analysis commands. When you have this working well, you can access the full data set of more than 600,000 events by removing -Small from the name of the data_site.

Time of day

It’s natural to expect that bikes are rented more at some times of day than others. The variable sdate gives the time (including the date) that the rental started.

Make these plots and interpret them:

  1. A density plot of the events versus sdate. Use ggplot() and geom_density().

  2. A density plot of the events versus time of day. You can use lubridate::hour(), and lubridate::minute() to extract the hour of the day and minute within the hour from sdate, e.g.

    Trips %>% 
  mutate(time_of_day = 
       lubridate::hour(sdate) + 
         lubridate::minute(sdate) / 60) %>%
  ... further processing ...

  3. Facet (2) by day of the week. (Use lubridate::wday() to generate day of the week. Use + facet_wrap( ~ day_of_week) to perform the faceting.)

  4. Set the fill aesthetic for geom_density() to the client variable.1 client describes whether the renter is a regular user (level Registered) or has not joined the bike-rental organization (Causal). You may also want to set the alpha for transparency and color=NA to suppress the outline of the density function.

  5. Same as (4) but using geom_density() with the argument position = position_stack().

  1. Rather than faceting on day of the week, consider creating a new faceting variable like this:

    mutate(wday = ifelse(lubridate::wday(sdate) %in% c(1,7), "weekend", "weekday"))