1. Learn
    2. /
  2. Courses
    3. /
  3. Case Study: Analyzing City Time Series Data in R

Exercise

Visualize flight data

Now that you have a grip on your data, the next step is to visualize trends in your data over time. In this exercise, you'll plot the flights_xts data over time using a few different methods for plotting time series data.

Often the simplest way to plot xts objects is to use plot.xts(), which requires only a single argument for the y-axis in the plot. The x-axis is supplied by the time index in your xts object.

For more complicated plots, you may want to use plot.zoo(), which allows you to include multiple columns of data. In particular, the plot.type argument allows you to specify whether you'd like your data to appear in a single panel ("single") or multiple panels ("multiple"). This can be useful when comparing multiple columns of data over time.

Instructions

100 XP
  • Use plot.xts() to view the total monthly flights into BOS (total_flights) over time. This command only requires you to specify the data for the y-axis, although you do need to be specific about which column of data you want to plot.
  • Use another call to plot.xts() to produce a plot of monthly delayed flights into BOS over time.
  • Generate a plot of all four time series columns in flights_xts using plot.zoo(). Set the plot.type argument to "multiple" to produce a plot with four different panels. Leave the ylab argument as is.
  • Put all four plots on a single panel using another call to plot.zoo(). Leave the lty argument and the legend function as they are.