README.md
In angusmoore/arphit: RBA-style R Plots

arphit

arphit is a ggplot-inspired R package to easily create RBA-style graphs in R. Once you have your data, you can quickly create a plot with:

arphitgg(data, agg_aes(x=date,y=x1)) + agg_line()

arphit is also customisable. You can create complex charts, with multiple panels, bars, titles, annotations, shading, sources and footnotes:

arphitgg(data, agg_aes(x = date), layout = "2b2") +
  agg_col(agg_aes(y=x1), panel = "1") +
  agg_line(agg_aes(y=x2), panel = "2") +
  agg_line(agg_aes(y=x3), panel = "3") +
  agg_line(agg_aes(y=x4), panel = "3") +
  agg_line(agg_aes(y=x4), panel = "4") +
  agg_title("arphit Makes Graphs in R") +
  agg_units("index", panel = "1") +
  agg_units("ppt", panel = "2") +
  agg_units("$", panel = "3") +
  agg_units("'000", panel = "4") +
  agg_shading(from = x4, to = x3) +
  agg_label("A label", x = 2001.5, y = 1, panel = "1", colour = "red") +
  agg_abline(x = 2002, panel = "2") +
  agg_bgshading(y1 = -1, y2 = 3, panel = "4")

arphit also has a quick plotting function, which plots all (or a subset of) the columns in your data. This is particularly helpful for time series data, or other 'wide' data:

data <- ts(data.frame(y=rnorm(10)), frequency = 4, start = 200)
agg_qplot(data)

Installation and getting started

Install the latest stable release of arphit using the R remotes package:

library(remotes)
install_github("angusmoore/arphit", ref = "stable", build = TRUE, build_opts =  c("--no-resave-data", "--no-manual"))

You may need to first install the remotes package if you don't already have it (install.packages("remotes")).

Installing may fail if remotes cannot correctly determine your proxy server. If so, you'll get one of the following error message when you try to install:

Installation failed: Timeout was reached: Connection timed out after 10000 milliseconds

Failed to connect to api.github.com port 443: Timed out

If you get this message, try setting your proxy server with the following command, and then running the install again:

Sys.setenv(https_proxy = curl::ie_get_proxy_for_url("https://www.google.com"))

(For more detail see getting started guide.)

The very first step to using arphit is to import it into your workspace:

library(arphit)

The second step is to get some data. For these simple examples, we'll randomly construct three years worth of quarterly time series data, starting from Q1 2000:

data <- data.frame(date = seq.Date(from = as.Date("2001-01-01"),
                                   by = "quarter",
                                   length.out = 10),
                   x1 = rnorm(10),
                   x2 = rnorm(10),
                   x3 = rnorm(10, sd = 10),
                   x4 = rnorm(10, sd = 5))

To make a simple line plot, all we need to do is specify the x and y variables and tell arphit we want a layer:

arphitgg(data, agg_aes(x=date, y = x1)) + agg_line()

That chart is serviceable, but not very well labelled. Let's make it a bit nicer, by putting each of the four series into its own panel, and giving the graph and panels titles, and a source.

arphitgg(data, layout = "2b2") +
  agg_line(agg_aes(x=date, y = x1), panel = "1") + 
  agg_line(agg_aes(x=date, y = x2), panel = "2") + 
  agg_line(agg_aes(x=date, y = x3), panel = "3") + 
  agg_line(agg_aes(x=date, y = x4), panel = "4") + 
  agg_title("A Randomly Created Graph") +
  agg_subtitle("A short example") + 
  agg_units("index") + 
  agg_title("Panel 1", panel = "1") + 
  agg_title("Panel 2", panel = "2") + 
  agg_title("Panel 3", panel = "3") + 
  agg_title("Panel 4", panel = "4") + 
  agg_source("Randomly generated data")

The getting started vignette provides more introduction on how to create graphs in arphit. arphit has a lot of plotting options to control how your chart looks. These are all explained, with examples, in the plotting options vignette.

Documentation

The getting started guide is a good place to start. A list of all the plotting options and examples of how to use them can be found in the plotting options vignette. It is more detailed than the getting started guide.

Package documentation can be found here. It is technical and in most cases will be less useful than the plotting options vignette.

If these sources don't answer your problems, or you encounter a bug, please open an issue (see below).