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I am trying to add multiple shadows/rectangles over a ggplot2 graph. In this reproducible example, I am only adding 3, but I may need to add up to a hundred using the full data.

Here is a subset of my raw data - in a dataframe called temp - the dput is at the bottom of the question: 

 Season tier group value NA NA NA <NA> NA 99 1948 2 Wins 20 101 1948 2 Losses 17 NA.1 NA NA <NA> NA NA.2 NA NA <NA> NA 104 1951 2 Wins 21 106 1951 2 Losses 18 107 1952 2 Wins 23 109 1952 2 Losses 18 110 1953 2 Wins 25 112 1953 2 Losses 18 113 1954 2 Wins 26 115 1954 2 Losses 19 116 1955 2 Wins 26 118 1955 2 Losses 19 119 1956 2 Wins 26 121 1956 2 Losses 20 NA.3 NA NA <NA> NA 123 1958 1 Wins 27 125 1958 1 Losses 20 126 1959 1 Wins 27 128 1959 1 Losses 21 129 1960 1 Wins 28 131 1960 1 Losses 21 132 1961 1 Wins 30 134 1961 1 Losses 21 135 1962 1 Wins 30 137 1962 1 Losses 23 138 1963 1 Wins 31 140 1963 1 Losses 23 141 1964 1 Wins 32 143 1964 1 Losses 23 144 1965 1 Wins 34 146 1965 1 Losses 23 NA.4 NA NA <NA> NA

I can make a ggplot like this:

p <- ggplot(temp, aes(Season,value, color=group)) + geom_point(size=4, shape=19) + scale_color_manual(values=c("red", "gray55")) p

plot without shadows

Now, I want to add shadows. Each shadow will begin with the Season that begins a run of dates in the Season column and will end with the date/Season that is the last in a run of dates in the Season column. Finally, each shadow should be colored by the 'tier' variable. Green for 'tier==2' and blue for 'tier==1'.

I have used the rle function plus some extra script to extract the first observation after the end of a run of NAs in the Season variable, as well as to get the observation before the first NA in a run of NAs. I then just add and minus 0.5 respectively, which gives me another dataframe (tempindex) like this:

# xmin xmax ymin ymax #5 1947.5 1948.5 -Inf Inf #6 1950.5 1956.5 -Inf Inf #7 1957.5 1965.5 -Inf Inf

I could add the shadows manually like this:

t2.rect1 <- data.frame (xmin=1947.5, xmax=1948.5, ymin=-Inf, ymax=Inf) t2.rect2 <- data.frame (xmin=1950.5, xmax=1956.5, ymin=-Inf, ymax=Inf) t1.rect1 <- data.frame (xmin=1957.5, xmax=1965.5, ymin=-Inf, ymax=Inf) p + geom_rect(data=t2.rect1, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax), fill="green", alpha=0.1, inherit.aes = FALSE) + geom_rect(data=t2.rect2, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax), fill="green", alpha=0.1, inherit.aes = FALSE) + geom_rect(data=t1.rect1, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax), fill="blue", alpha=0.1, inherit.aes = FALSE)

which gives the desired output:

image with Shadows

However, I obviously don't want to be manually writing out this a hundred times for instances when I have lots of shadows/rectangles to apply. I am looking to see if I can do this in an automated fashion. I tried a for loop (without trying to adjust color by tier) very unsuccessfully...

grect <-vector("list", nrow(indextemp)) #vector for storing geom_rects for (i in 1:nrow(indextemp)){ grect[[i]] <- geom_rect(data=temp[i], aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax), alpha=0.1, inherit.aes = FALSE) }

This is obviously a non-starter. I wonder if anybody has any ideas?

dput for temp dataframe:

structure(list(Season = c(NA, 1948L, 1948L, NA, NA, 1951L, 1951L, 1952L, 1952L, 1953L, 1953L, 1954L, 1954L, 1955L, 1955L, 1956L, 1956L, NA, 1958L, 1958L, 1959L, 1959L, 1960L, 1960L, 1961L, 1961L, 1962L, 1962L, 1963L, 1963L, 1964L, 1964L, 1965L, 1965L, NA), tier = c(NA, 2L, 2L, NA, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA), group = structure(c(NA, 1L, 3L, NA, NA, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, NA, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, NA), .Label = c("Wins", "Draws", "Losses"), class = "factor"), value = c(NA, 20L, 17L, NA, NA, 21L, 18L, 23L, 18L, 25L, 18L, 26L, 19L, 26L, 19L, 26L, 20L, NA, 27L, 20L, 27L, 21L, 28L, 21L, 30L, 21L, 30L, 23L, 31L, 23L, 32L, 23L, 34L, 23L, NA)), .Names = c("Season", "tier", "group", "value"), row.names = c("NA", "99", "101", "NA.1", "NA.2", "104", "106", "107", "109", "110", "112", "113", "115", "116", "118", "119", "121", "NA.3", "123", "125", "126", "128", "129", "131", "132", "134", "135", "137", "138", "140", "141", "143", "144", "146", "NA.4"), class = "data.frame")

dput for tempindex dataframe:

structure(list(xmin = c(1947.5, 1950.5, 1957.5), xmax = c(1948.5, 1956.5, 1965.5), ymin = c(-Inf, -Inf, -Inf), ymax = c(Inf, Inf, Inf)), .Names = c("xmin", "xmax", "ymin", "ymax"), row.names = 5:7, class = "data.frame")
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2 Answers 2

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it's better to use only one layer, with suitable mapping,

tempindex <- transform(tempindex, id = 1:3, tier = c(1,1,2)) ggplot(temp, aes(Season,value, color=group)) + geom_rect(data=tempindex, inherit.aes=FALSE, aes(xmin=xmin,xmax=xmax,ymin=ymin,ymax=ymax, group=id, fill = factor(tier)), alpha=0.2)+ geom_point(size=4, shape=19) + scale_color_manual(values=c("red", "gray55"))+ scale_fill_manual(values=c("green", "blue")) + guides(fill="none")

enter image description here

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1 Comment

Indeed much better, adding many multiple geom_rect in different layers slows down for me rendering massively, at least in a Shiny application. Hope the comment is helpful for others at some point.
1

Another option (more straightforward avoiding creating auxiliary data.frames) could be that one:

ggplot(tmp, aes(Season,value, color = group)) + geom_point(size = 4, shape = 19) + scale_color_manual(values = c("red", "gray55")) + annotate("rect", xmin = c(1947.5, 1950.5, 1957.5), xmax = c(1948.5, 1956.5, 1965.5), ymin = -Inf, ymax = Inf, alpha = .1, fill = c("green", "green", "blue"))
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