R GGPLOT - Add Averages of Each Series Contained in Facet Wrap - r

Question

I have a dataset described as follows: I used 3 different standards, that I loaded 3 different times into the test apparatus where I took 10 measurements for each combination of standard & loading. I have been able to plot the data where I depict each loading as a different series and I do a facet wrap based on the standard. I now want to add the average of each loading for each standard to the chart and I cannot seem to do so.
My data first (LatexStandards_GammaSummary):
structure(list(Standard = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L), .Label = c("0.5 µm", "1 µm", "4 µm"), class = "factor"),
Loading = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L), .Label = c("L1", "L2", "L3"), class = "factor"),
Gamma = c(0.66716, 0.67899, 0.67286, 0.67527, 0.67327, 0.67396,
0.68518, 0.66993, 0.65695, 0.67583, 0.68428, 0.68807, 0.68862,
0.67403, 0.68282, 0.69051, 0.68571, 0.67531, 0.68146, 0.68367,
0.68348, 0.68344, 0.68768, 0.68189, 0.68253, 0.6836, 0.68388,
0.68645, 0.67551, 0.67897, 0.62186, 0.63639, 0.62981, 0.63896,
0.61639, 0.62586, 0.6226, 0.63984, 0.63112, 0.63279, 0.61764,
0.63829, 0.62712, 0.62563, 0.62233, 0.63423, 0.62621, 0.62251,
0.6287, 0.6375, 0.62774, 0.64823, 0.62692, 0.63093, 0.6223,
0.62713, 0.62279, 0.63341, 0.63451, 0.63072, 0.61586, 0.71059,
0.7198, 0.57358, 0.66188, 0.7624, 0.71269, 0.74395, 0.75922,
0.70551, 0.535, 0.59343, 0.62455, 0.72823, 0.65101, 0.56216,
0.5248, 0.54717, 0.6283, 0.63807, 0.53681, 0.54385, 0.58027,
0.69051, 0.70548, 0.61578, 0.65215, 0.68302, 0.72091, 0.58527
)), .Names = c("Standard", "Loading", "Gamma"), class = "data.frame", row.names = c(NA,
-90L))
The code I use to produce the original facet wrap ggplot:
# input data
inpdata <- LatexStandards_GammaSummary
# basic plot set up
plotout<-ggplot(data=inpdata,aes(x=Loading,y=Gamma))
# data sets
dataset1<-geom_point(aes(color=Loading),
position = "jitter")
wrapon<-facet_wrap(~Standard)
# axis labels
xlbl <- xlab("")
ylbl <- ylab("g")
# theme mods
basetheme <- theme_bw()
# x axis
theme_xaxis <- theme(
axis.title.x = element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank()
)
number_format_xaxis <- ""
# y axis
theme_yaxis <- theme(
axis.title.y=element_text(family="GreekC",size=14)
)
number_format_yaxis <- function(x){format(x,digits=1,nsmall=1,scientific=FALSE)}
scale_yaxis <- scale_y_continuous(labels=number_format_yaxis,limits=c(0.4,0.9))
# legend
theme_legend <- theme(
legend.position = "bottom",
legend.margin = unit(-0.5,"cm"),
legend.key = element_blank(),
legend.text = element_text(size = 14),
legend.title = element_text(size = 14, face = "plain")
)
# wrapping items
theme_wrapping = theme(
strip.background = element_blank(),
strip.text = element_text(size = 14)
)
# panel items
theme_panel = theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank()
)
plotout<-plotout +
dataset1 +
wrapon +
xlbl +
ylbl +
basetheme +
theme_xaxis +
theme_yaxis +
scale_yaxis +
theme_legend +
theme_wrapping +
theme_panel
plotout
Thank you for your help!

Answer 1

You will likely be best served by generating the summary data yourself, then plotting it. Using dplyr, here is an approach to calculate the averages:
avgLines <-
inpdata %>%
group_by(Standard, Loading) %>%
summarise(Gamma = mean(Gamma))
Which gives:
Standard Loading Gamma
1 0.5 µm L1 0.672940
2 0.5 µm L2 0.683448
3 0.5 µm L3 0.682743
4 1 µm L1 0.629562
5 1 µm L2 0.628016
6 1 µm L3 0.630468
7 4 µm L1 0.696548
8 4 µm L2 0.603272
9 4 µm L3 0.631405
Then, we can add this to the plot object you generated, setting the range of the segment you want to include (the facet_wrap from your plot object is applied here as well):
plotout +
geom_segment(
aes(y = Gamma
, yend = Gamma
, color=Loading
, x = as.numeric(Loading) - 0.5
, xend = as.numeric(Loading) + 0.5
)
, data = avgLines)
(Of note, much of the theme setting you included is not required for a minimally working plot -- you may have gotten quicker responses if you had trimmed the example down to just the portions relevant to what you wanted to generate.)