In preparation for using some of our streamgraphs for production (PDF\/print) graphics, I ended up having to hand-edit labels in on one of the graphics in an Adobe product. This bumped up the priority on adding annotation functions to the streamgraph package (you really don’t want to have to hand-edit graphics if at all possible, trust me). To illustrate them, I’ll use unemployment data that I started gathering for a course I’m teaching in the Fall.<\/p>\n
We’ll start with the setup and initial data gathering:<\/p>\n
library(dplyr)\r\nlibrary(streamgraph)\r\nlibrary(pbapply)\r\n\r\nurl <- \"http:\/\/www.bls.gov\/lau\/ststdsadata.txt\"\r\ndat <- readLines(url)<\/pre>\nThis data is not exactly in a happy format (hit the URL in your browser and you'll see what I mean). It was definitely made for line printers\/human consumption and I feel bad for any human that has to stare at it. The function I'm using to extract data is not necessarily what I'd do to just read in the whole data, but it's more for teaching something else than optimization. It'll do for our purposes here:<\/p>\n
get_state_data <- function(state) {\r\n\r\n section <- paste(\"^%s| (\", paste0(month.name, sep=\"\", collapse=\"|\"), \")\\ +[[:digit:]]{4}\", sep=\"\", collapse=\"\")\r\n section <- sprintf(section, state)\r\n vals <- gsub(\"^\\ +|\\ +$\", \"\", grep(section, dat, value=TRUE))\r\n\r\n state_vals <- gsub(\"^.* \\\\.+\", \"\", vals[seq(from=2, to=length(vals), by=2)])\r\n\r\n cols <- read.table(text=state_vals)\r\n cols$month <- as.Date(sprintf(\"01 %s\", vals[seq(from=1, to=length(vals), by=2)]),\r\n format=\"%d %B %Y\")\r\n cols$state <- state\r\n\r\n cols %>%\r\n select(8:9, 1:8) %>%\r\n mutate(V1=as.numeric(gsub(\",\", \"\", V1)),\r\n V2=as.numeric(gsub(\",\", \"\", V2)),\r\n V4=as.numeric(gsub(\",\", \"\", V4)),\r\n V6=as.numeric(gsub(\",\", \"\", V6)),\r\n V3=V3\/100,\r\n V5=V5\/100,\r\n V7=V7\/100) %>%\r\n rename(civ_pop=V1,\r\n labor_force=V2, labor_force_pct=V3,\r\n employed=V4, employed_pct=V5,\r\n unemployed=V6, unemployed_pct=V7)\r\n\r\n}\r\n\r\nstate_unemployment <- bind_rows(pblapply(state.name, get_state_data))<\/pre>\nThis will give us a data frame for employment(\/unemployment) rates for all the (US) states. I only wanted to focus on New England and a few others for the course example, so this bit filters out them out:<\/p>\n
state_unemployment %>%\r\n filter(state %in% c(\"California\", \"Ohio\", \"Rhode Island\", \"Maine\",\r\n \"Massachusetts\", \"Connecticut\", \"Vermont\",\r\n \"New Hampshire\", \"Nebraska\")) -> some<\/pre>\nWith that setup out of the way, let me introduce the two new functions: `sg_add_marker` and `sg_annotate`. `sg_add_marker` adds a vertical, dotted line that spans the height of the graph and is placed at the designated spot on the x axis. You can add an optional label for the marker by specifying the y position, label text, color, size, space away from the line and how it's aligned - start (left), center (middle), right (end). This is primarily useful for placing the label on either side of the line.<\/p>\n
`sg_annotate` is for adding text anywhere on the streamgraph. The original use for it was to label streams, but you can use it any way you think would add meaning to your streamgraph. You can see them both in action below, where I plot the streamgraph for unemployment (%) for the selected states, then label the start of each recession since 1980 (with the peak national unemployment rate) with a marker and also label each stream:<\/p>\n
streamgraph(some, \"state\", \"unemployed_pct\", \"month\") %>%\r\n sg_axis_x(tick_interval=10, tick_units = \"year\", tick_format=\"%Y\") %>%\r\n sg_axis_y(0) %>%\r\n sg_add_marker(x=as.Date(\"1981-07-01\"), \"1981 (10.8%)\", anchor=\"end\") %>%\r\n sg_add_marker(x=as.Date(\"1990-07-01\"), \"1990 (7.8%)\", anchor=\"start\") %>%\r\n sg_add_marker(x=as.Date(\"2001-03-01\"), \"2001 (6.3%)\", anchor=\"end\") %>%\r\n sg_add_marker(x=as.Date(\"2007-12-01\"), \"2007 (10.1%)\", anchor=\"end\") %>%\r\n sg_annotate(label=\"Vermont\", x=as.Date(\"1978-04-01\"), y=0.6, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Maine\", x=as.Date(\"1978-03-01\"), y=0.30, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Nebraska\", x=as.Date(\"1977-06-01\"), y=0.41, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Massachusetts\", x=as.Date(\"1977-06-01\"), y=0.36, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"New Hampshire\", x=as.Date(\"1978-03-01\"), y=0.435, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"California\", x=as.Date(\"1978-02-01\"), y=0.175, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Rhode Island\", x=as.Date(\"1977-11-01\"), y=0.55, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Ohio\", x=as.Date(\"1978-06-01\"), y=0.485, color=\"#ffffff\") %>%\r\n sg_annotate(label=\"Connecticut\", x=as.Date(\"1978-01-01\"), y=0.235, color=\"#ffffff\") %>%\r\n sg_fill_tableau() %>%\r\n sg_legend(show=TRUE)<\/pre>\nSelected State Unemployment Figures Since 1976<\/b>