Further Tasks

The tasks below should be answered by creating your own .R script file.

The first step is to load into R all of the libraries you will need. This can be done by typing/copying and running the following code in your R script:

library(ggplot2)
library(nycflights13)
  1. From the flights data set, subset the data for the airline carrier JetBlue Airways and produce a scatterplot of their departure delays against arrival delays using ggplot. Interpret the scatterplot.

First subset the flights data for the carrier B6 using the same approach we used when creating the Alaska data set.

  1. Produce a histogram of the hourly temperature from Newark Liberty International (EWR) Airport in 2013 using ggplot. How does the temperature distribution compare with that from all airports in New York City in 2013?

Subset the weather data set so you are only looking at the hourly temperature levels for EWR airport.

  1. For John F. Kennedy Airport, produce boxplots (using a single ggplot command) of the hourly temperature for the months May, June, July, August and September. How does the hourly temperature change during this period?

You can subset data across multiple variables using the & (AND) and %in% (IN) operators. For example, flights[flights$carrier == "US" & flights$origin %in% c("LGA", "EWR"), ].

  1. Take a look at the mtcars data set within the datasets library relating to data extracted from the 1974 Motor Trend US magazine. Using ggplot, produce a faceted barplot of the categorical variables relating to the number of cylinders (cyl) and the automobiles transmission (am). Interpret the barplot.

Start by creating a table from cyl and am. Remember that ggplot requires data passed to it to be a data frame (see as.data.frame).

  1. Produce a linegraph of the hourly temperature at LAGuardia (LGA) Airport for the month of October 2013. Interpret the linegraph.

Subset the weather data set for LGA airport and the month October. See the hint for Task 3. -->