First things first

We begin by loading the required libraries we will use throughout the course. We reload these libraries later when we run the functions inside them, but putting them at the top of the project gives us a chance to see all of them in one place, and install any libraries we don't already have using install.packages.

# let's set some options for how things look on the console
options(max.print = 1000, # limit how much data is shown on the console
        scipen = 999, # don't use scientific notation for numbers
        width = 90, # width of the screen should be 80 characters long
        digits = 3, # round all numbers to 3 decimal places when displaying them
        warn = -1) # suppress warnings (you normally don't do this in development!)

library(dplyr) # for fast data manipulation/processing/summarizing
options(dplyr.print_max = 20) # limit how much data `dplyr` shows by default
options(dplyr.width = Inf) # make `dplyr` show all columns of a dataset
library(stringr) # for working with strings
library(lubridate) # for working with date variables
Sys.setenv(TZ = "US/Eastern") # not important for this dataset
library(ggplot2) # for creating plots
library(ggrepel) # avoid text overlap in plots
library(tidyr) # for reshaping data
library(seriation) # package for reordering a distance matrix

library(rgeos) # GIS library
library(maptools)

library(profr) # profiling tool
library(microbenchmark) # benchmarking tool

In the next chapter, we deal with our first challenge: loading the data into R.