I'm trying to remove the redundant "pro/retro" labels on the second row of panels on my plot. However, I still want to keep the top row of panel labels intact. I've tried for the past hour to selectively remove the 1st strip on the 2nd panel row and I was wondering if anyone here knows how to do this. See below for technical details.
I have the following plot:
It was generated from the following data:
absBtwnDat <- structure(list(setSize = structure(c(1L, 2L, 3L, 4L, 5L, 6L,
7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L,
6L, 7L), .Label = c("2", "3", "4", "5", "6", "7", "8"), class = "factor"),
Measure = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L), .Label = c("Actual", "Predicted"), class = "factor"),
Location = structure(c(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, 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), .Label = c("fix", "forced"), class = "factor"),
JudgementType = 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, 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), .Label = c("pro", "retro"), class = "factor"),
Accuracy = c(1.91388888888889, 2.95555555555556, 3.74861111111111,
4.37777777777778, 4.21527777777778, 3.0875, 2.85277777777778,
2, 2.99444444444444, 4, 4.77222222222222, 5.24444444444444,
5.18472222222222, 5.20277777777778, 1.98888888888889, 3,
3.97222222222222, 4.85972222222222, 5.70555555555556, 6.56944444444444,
7.27222222222222, 2, 3, 3.99444444444444, 4.99444444444444,
5.86944444444444, 6.75555555555556, 7.57777777777778, 1.96111111111111,
2.97777777777778, 3.78333333333333, 3.97222222222222, 4.22361111111111,
3.64722222222222, 3.68888888888889, 2, 3, 3.97222222222222,
4.67777777777778, 5.26944444444444, 5.4625, 5.8, 2, 3, 3.98333333333333,
4.87777777777778, 5.73055555555556, 6.48333333333333, 7.62916666666667,
2, 3, 3.98333333333333, 4.96666666666667, 5.96944444444444,
6.94444444444444, 7.93333333333333), LL = c(1.85, 2.87777777777778,
3.59861111111111, 4.15555555555556, 3.78888888888889, 2.73055555555556,
2.55555555555556, 2, 2.96111111111111, 4, 4.64444444444444,
5.01666666666667, 4.88333333333333, 4.88611111111111, 1.91111111111111,
3, 3.89444444444444, 4.73611111111111, 5.47777777777778,
6.20277777777778, 6.71666666666667, 2, 3, 3.96666666666667,
4.95555555555556, 5.65096686319131, 6.48333333333333, 7.17222222222222,
1.86637442123568, 2.92222222222222, 3.65, 3.61666666666667,
3.88333333333333, 3.17092476055122, 3.18888888888889, 2,
3, 3.92222222222222, 4.49444444444444, 5.0375, 5.09444444444444,
5.40555555555556, 2, 3, 3.92777777777778, 4.72222222222222,
5.52777777777778, 6.24444444444444, 7.37361111111111, 2,
3, 3.95, 4.88888888888889, 5.93333333333333, 6.88333333333333,
7.73065763697428), UL = c(1.95555555555556, 2.98333333333333,
3.84444444444444, 4.56666666666667, 4.6, 3.43611111111111,
3.17916666666667, 2, 3, 4, 4.86111111111111, 5.42777777777778,
5.48656054159421, 5.58611111111111, 2, 3, 4, 4.93888888888889,
5.83888888888889, 6.76944444444444, 7.6, 2, 3, 4, 5, 5.94166666666667,
6.88888888888889, 7.78888888888889, 1.98888888888889, 2.99444444444444,
3.87777777777778, 4.22777777777778, 4.53611111111111, 4.19722222222222,
4.20555555555556, 2, 3, 3.98888888888889, 4.78333333333333,
5.45555555555556, 5.79583333333333, 6.16666666666667, 2,
3, 3.99444444444444, 4.95, 5.85972222222222, 6.67222222222222,
7.80138888888889, 2, 3, 3.99444444444444, 4.98888888888889,
5.9875, 6.97222222222222, 7.98333333333333)), .Names = c("setSize",
"Measure", "Location", "JudgementType", "Accuracy", "LL", "UL"
), row.names = c(NA, -56L), class = "data.frame")
I visualized it using using the following code:
library(ggplot2)
p1 <- ggplot(data = absBtwnDat, aes(x = as.numeric(as.character(setSize)),
y = Accuracy, group = Measure,
colour = Measure))+
geom_point()+
geom_line(aes(linetype = Measure))+
scale_x_continuous("Trial Set Size", breaks = 2:8)+
scale_y_continuous("Accuracy (# Correct)", breaks = 0:8, limits = c(0, 8))+
geom_errorbar(aes(ymin = LL, ymax = UL), width = .1, size = .75)+
scale_colour_grey(start = .8, end = .4)+
facet_wrap(~JudgementType+Location, dir = "v")+
theme(legend.position = "top")
Just to be certain, I've highlighted unwanted strip in the following image:
With this you'll only have one row of labels per panel, but they still include both words.
p1 <- ggplot(data = absBtwnDat,
aes(x = as.numeric(as.character(setSize)), y = Accuracy,
group = Measure,
colour = Measure))+
geom_point()+
geom_line(aes(linetype = Measure))+
scale_x_continuous("Trial Set Size", breaks = 2:8)+
scale_y_continuous("Accuracy (# Correct)",
breaks = 0:8, limits = c(0, 8))+
geom_errorbar(aes(ymin = LL, ymax = UL),
width = .1, size = .75)+
scale_colour_grey(start = .8, end = .4)+
facet_wrap(~JudgementType + Location,
dir = "v",
labeller = label_wrap_gen(multi_line=FALSE)) +
theme(legend.position = "top")
p1
Here is a possible solution:
g1 <- ggplotGrob(p1)
k <- which(g1$layout$name=="strip-t-1-2")
g1$grobs[[k]]$grobs[[1]]$children[[2]]$children[[1]]$label <- ""
g1$grobs[[k]]$grobs[[1]]$children[[1]]$gp$fill <- NA
k <- which(g1$layout$name=="strip-t-2-2")
g1$grobs[[k]]$grobs[[1]]$children[[2]]$children[[1]]$label <- ""
g1$grobs[[k]]$grobs[[1]]$children[[1]]$gp$fill <- NA
library(grid)
grid.draw(g1)
Related
Hello :) I am desperately trying to change the colors and font of my emmip plot (plot from the emmeans package in R) but none of my codes are working.
Currently my code for the plot looks like this:
emmip(Model, group ~ gend, CIs=TRUE, nuisance = c("known", "age_dup", "edu"),
xlab = "",
ylab = "Intention to use the platform")
I read in the manueal from the R-package that the code from emmip() can be combined with ggplot2 codes. But when I add the following two codes (that I successfully use in another ggplot) - nothing changes in my plot:
+ theme(text=element_text(family="serif", size=13)
+ scale_fill_brewer(palette="Blues"))
I varied them already, for example "," instead of "+"
Does anyone have an idea how I can make these two modifications work in emmip? Thank you all in advance!
Here is the dput of my data (first 30 rows):
structure(list(dv = c(1, 5, 5, 1, 3, 5, 2, 1, 5, 5, 2, 4, 6,
7, 3, 5, 5, 6, 7, 1, 7, 6, 2, 4, 7, 6, 5, 1, 6, 6), gend = structure(c(1L,
2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L), .Label = c("Male",
"Female"), class = "factor"), group = structure(c(5L, 3L, 5L,
3L, 2L, 1L, 3L, 4L, 2L, 1L, 3L, 2L, 3L, 3L, 4L, 4L, 2L, 4L, 5L,
5L, 1L, 4L, 1L, 4L, 2L, 1L, 2L, 3L, 1L, 4L), .Label = c("Default",
"Visual element", "Verbal content", "Visual design", "Combined",
"DesignZH"), class = "factor"), ISFregscores = c(0.984372106429775,
-0.383676865152824, -0.816194838031774, -0.408554787302724, -0.0416530380928891,
0.998088756156888, 0.216609251327447, 0.83416518546863, 1.00178246600492,
-0.496215251116934, -1.34559758838579, NA, 0.707838661016661,
1.05815783619489, -0.314855036376305, 0.617674358967702, -0.56862344822269,
0.0589354712707628, 0.31998903974822, -0.511084756816837, -0.171121724458495,
0.532699047600051, 0.196311893993997, -2.09902298349596, 1.04422334581248,
-0.132687312769232, 1.05733961165571, 0.541606480874359, 0.440296538856025,
0.895064902672922), age_dup = structure(c(2L, 1L, 1L, 2L, 1L,
2L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 1L, 2L, 3L,
1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L), .Label = c("under34", "age35_49",
"over50"), class = "factor"), edu = structure(c(5L, 4L, 5L, 2L,
5L, 5L, 5L, 5L, 5L, 4L, 5L, NA, 5L, 4L, 1L, 5L, 4L, 5L, 3L, 5L,
2L, 5L, 3L, 5L, 6L, 5L, 6L, 1L, 3L, 5L), .Label = c("oblig. Schulzeit",
"Berufsausbildung", "Berufsmatura", "Gymnasiale Matura", "BA/MA",
"Doktorat", "Andere"), class = "factor"), empl = structure(c(1L,
6L, 1L, 2L, 8L, 2L, 5L, 2L, 2L, 6L, 2L, NA, 1L, 1L, 6L, 2L, 6L,
1L, 1L, 4L, 2L, 6L, 1L, 1L, 3L, 6L, 2L, 2L, 4L, 1L), .Label = c("Privatsektor",
"öffentlicher Sektor", "Non-Profit Sektor", "selbstständig",
"Rentner/in", "Student/in", "Hausfrau/Hausmann", "arbeitssuchend"
), class = "factor"), civ_dup = structure(c(2L, 1L, 1L, 3L, 2L,
1L, 2L, 2L, 2L, 1L, 2L, NA, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 3L, 1L,
2L, 2L, 2L, 2L, 1L, 2L, 3L, 2L, 1L), .Label = c("single", "Partnerschaft",
"keine Angabe"), class = "factor"), kids = structure(c(2L, 1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, NA, 2L, 2L, 1L, 1L, 1L, 1L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("Nein",
"Ja"), class = "factor"), known = structure(c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 1L, 1L, NA, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L), .Label = c("Nein", "Ja"
), class = "factor"), device = structure(c(1L, 2L, 1L, 2L, 2L,
1L, 3L, 1L, 2L, 2L, 1L, NA, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L), .Label = c("Smartphone / Tablet iOS (iPhone/iPad)",
"Smartphone / Tablet (Android)", "Computer / Laptop"), class = "factor")), row.names = c(NA,
-30L), class = c("tbl_df", "tbl", "data.frame"))
And this is the code for my regression that I then use for the interaction (graph):
Model <- lm(dv ~ gend * group + ISFregscores + age_dup + edu + empl + civ_dup + kids + known + device, data=)
You've got the right approach to change the font but you also have to make sure the font is actually available to the graphics device. This step can be tricky; I use the showtext package which makes this a bit easier.
To change the color palette, specify the color scale (rather than the fill scale).
library("showtext")
#> Loading required package: sysfonts
#> Loading required package: showtextdb
library("emmeans")
library("tidyverse")
showtext_auto()
# 30 data points are too few to fit the original model, so I drop `device`
model <- lm(
dv ~ gend * group + ISFregscores + age_dup + edu + empl + civ_dup + kids + known,
data = data
)
p <- emmip(
model, group ~ gend,
CIs = TRUE,
nuisance = c("known", "age_dup", "edu"),
xlab = "",
ylab = "Intention to use the platform"
)
p +
scale_color_brewer(
palette = "Blues"
) +
guides(
color = guide_legend(title = "New Legend Title")
) +
theme(
text = element_text(family = "serif", face = "bold.italic", size = 16)
)
Created on 2023-01-11 with reprex v2.0.2
I have a dataframe tag, with 51X5 structure
structure(list(Tagging = 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, 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), .Label = c("CIRCLE CAMPIAGN",
"NATIONAL CAMPIAGN"), class = "factor"), Status = structure(c(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, 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), .Label = c("Negative", "Positive"), class = "factor"),
Month = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L), .Label = c("JUL",
"JUN", "MAY"), class = "factor"), Category = structure(c(1L,
4L, 6L, 1L, 2L, 4L, 6L, 1L, 2L, 4L, 5L, 6L, 1L, 2L, 4L, 5L,
6L, 1L, 2L, 4L, 5L, 6L, 1L, 2L, 4L, 6L, 1L, 4L, 6L, 2L, 3L,
4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L, 6L), .Label = c("Data", "Other", "Roaming",
"Unlimited", "VAS", "Voice"), class = "factor"), count = c(3L,
2L, 1L, 4L, 5L, 2L, 1L, 2L, 6L, 7L, 2L, 3L, 4L, 9L, 6L, 2L,
3L, 3L, 3L, 10L, 2L, 5L, 5L, 5L, 4L, 3L, 1L, 1L, 1L, 2L,
1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 4L, 1L, 1L, 3L, 3L, 2L,
1L, 1L, 1L, 3L, 4L, 2L)), class = "data.frame", row.names = c(NA,
-51L))
I want to create a bar plot (ggplot) to show bar graph with label on bar as sum of count of category month wise I am using below code
ggplot(data = tag, aes(x = Tagging, y = count, fill = Status)) +
geom_col() +
labs(x = "Tagging", y = "Count", title = "FlyTxt ROI", subtitle = "Statistics") +
geom_text(aes(label = count), color = "white", size = 3, position = position_stack(vjust = 0.5)) +
theme_minimal()+facet_wrap(~Month)
But I am getting split count values:
Help as I want only sum of count for each status
The problem is, that the information you show in the bar is accumulated by geom_col over all categories but the geom_text doesn't do that.
On option is to pre-summarize the data (to get rid of the category split) and then plot the graph.
library(tidyverse)
tag_sum <- tag %>%
group_by(Tagging, Status, Month) %>%
summarise(count_sm = sum(count))
ggplot(data = tag_sum, aes(x = Tagging, y = count_sm, fill = Status)) +
geom_col() +
geom_text(aes(label = count_sm), color = "white", size = 3,
position = position_stack(vjust = 0.5)) +
facet_wrap(~Month) +
labs(x = "Tagging", y = "Count", title = "FlyTxt ROI", subtitle = "Statistics") +
theme_minimal()
I have been struggling with ggplot to display these plots how I would like. My data have 2 factors, quarter and species. Station will be on the x-axis, value on the y-axis, and the constituent will be used with the facet_wrap. I want quarter differentiated with shapes, and species with colors.
The issue is I'm trying to replicate a figure done in SigmaPlot. It is 4x4 grid of plots, with the first two rows of the first column are empty, to allow for the placement of the legend. My original plan was to have two separate facets made using facet-wrap, and combine those, however, this doesn't maintain the 4x4 arrangement, it transforms it into a 1x2, which ruins alignment of plots and shrinks the larger faceted grid.
My next thought was to create each plot individually, then arrange them in a grid using cowplot. This presents the plots how I'd like them arranged, but I can't figure out how to have two y-axis labels, due to different units. One label would be centered on the two leftmost plots, and one centered on the left of the next column of 4 plots.
I'm trying to use this code (just copy the example data below, and run):
library(ggplot)
library(gridExtra)
test.data1 <- test.data[1:95, ]
test.data2 <- test.data[96:111, ]
testplot1 <- ggplot(test.data1, aes(Station, value)) +
geom_point(aes(shape = factor(quarter), fill = Species)) +
scale_shape_manual(values = c(21, 22)) +
labs(x = "Station", y = "Unit a", shape = "Sampling Quarter", fill = "Species") +
theme(legend.position = "none", legend.title = element_blank()) +
guides(fill = guide_legend(override.aes = list(shape = 21), nrow = 2, byrow = TRUE), shape = guide_legend(nrow = 2, byrow = TRUE)) +
facet_wrap( ~ constituent, ncol = 3, scales = "free_y")
testplot2 <- ggplot(test.data2, aes(Station, value)) +
geom_point(aes(shape = factor(quarter), fill = Species))
scale_shape_manual(values = c(21, 22)) +
labs(x = "Station", y = "Unit b", shape = "Sampling Quarter", fill = "Species") +
theme(legend.position = "top", legend.title = element_blank()) +
guides(fill = guide_legend(override.aes = list(shape = 21), nrow = 2, byrow = TRUE), shape = guide_legend(nrow = 2, byrow = TRUE)) +
facet_wrap( ~ constituent, ncol = 1, scales = "free_y")
grid.arrange(testplot2, testplot1, ncol = 2)
Which generates this:
But I want it to be arranged like this, where the XX and YY plots from above are normalized in size with the other plots (this was done using individual plots, and using plot_grid):
Example data from a larger set:
test.data <- structure(list(Station = structure(c(1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("StA", "StB"), class = "factor"),
CollectionDate = structure(c(3L, 2L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 1L, 3L, 2L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L, 1L), .Label = c("10/1/2017",
"10/16/2017", "4/1/2017"), class = "factor"), Species = structure(c(1L,
2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L,
1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L,
3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L,
2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L,
2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L,
1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L,
3L, 1L, 2L, 2L, 3L), .Label = c("SpA", "SpB", "SpC"), class = "factor"),
quarter = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("2017 Q2",
"2017 Q4"), class = "factor"), constituent = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L
), .Label = c("A", "B", "C", "D", "E", "F", "G", "H", "I",
"J", "K", "L", "XX", "YY"), class = "factor"), value = c(16,
35, 46, 23, 40, 19, 9, 50, 0.2, 1, 0.5698, 0.322, 1, 0.45,
0.322, 0.5, 16, 9, 6, 19, 14, 13, 16, 9, 0, 0.004, 0, 0.004,
1, 0.32, 1, 0.678, 0, 0.39, 0.23, 0, 0, 1.1, 0.5, 0.5, 9,
4.9, 7, 4.768, 9, 8.65, 4.768, 6.54, 195, 195, 46, 46, 124,
124, 218, 218, 2, 1, 1, 1, 1, 2, 1, 1, 0.1, 0.4, 0.22, 0.4,
0.22, 0.4, 0.22, 0.1, 0.99, 0.99, 1.2, 0.45, 0.765, 0.99,
0.99, 0.99, 0.99, 1.2, 4.3, 0.98, 0.99, 1.2, 1.2, 34, 34,
65, 98, 150, 34, 65, 65, 2, 0, 4, 1.3, 5, 3.3, 1.56, 1, 9,
0.36, 4, 4, 11, 2, 2.22, 11)), class = "data.frame", row.names = c(NA,
-111L))
Is there a way to make the thinner lines in the plot (those without an y axis tick label) appear closer to the lines above (those with a label) so as to better simulate pairs of baseline / actual bars of the same activity in a gantt chart?
See gantt chart examples here and here.
mdfr <- structure(list(name = structure(c(8L, 8L, 8L, 8L, 6L, 6L, 6L,
6L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 5L, 5L, 5L,
5L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 8L, 8L, 8L, 8L, 6L, 6L, 6L,
6L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 5L, 5L, 5L,
5L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L), .Label = c("100 A", "100 B",
"101 A", "101 B", "102 A", "102 B", "103 A", "103 B"), class = "factor"),
stadio = c(2, 4, 5, 7, 2, 4, 5, 7, 2, 4, 5, 7, 2, 4, 5, 7,
1, 3, 6, 8, 1, 3, 6, 8, 1, 3, 6, 8, 1, 3, 6, 8, 2, 4, 5,
7, 2, 4, 5, 7, 2, 4, 5, 7, 2, 4, 5, 7, 1, 3, 6, 8, 1, 3,
6, 8, 1, 3, 6, 8, 1, 3, 6, 8), variable = 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, 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, 2L, 2L), .Label = c("start_date", "end_date"), class = "factor"),
value = c("05/10/2012", "17/12/2012", "12/03/2012", "30/05/2013",
"10/01/2013", "14/10/2013", "24/10/2013", "10/01/2014", "30/09/2013",
"29/01/2014", "30/01/2014", "06/05/2014", "30/09/2013", "29/01/2014",
"30/01/2014", "06/05/2014", "05/10/2012", "17/12/2012", "12/03/2012",
"30/05/2013", "10/01/2013", "14/10/2013", "24/10/2013", "10/01/2014",
"30/09/2013", "29/01/2014", "30/01/2014", "05/06/2014", "30/09/2013",
"29/01/2014", "30/01/2014", "05/06/2014", "17/12/2012", "12/03/2012",
"30/05/2013", "30/05/2014", "14/10/2013", "24/10/2013", "10/01/2014",
"11/07/2014", "29/01/2014", "30/01/2014", "06/05/2014", "23/12/2014",
"29/01/2014", "30/01/2014", "06/05/2014", "23/12/2014", "17/12/2012",
"12/03/2012", "30/05/2013", "30/05/2014", "14/10/2013", "24/10/2013",
"10/01/2014", "11/07/2014", "29/01/2014", "30/01/2014", "05/06/2014",
"28/12/2014", "29/01/2014", "30/01/2014", "05/06/2014", "29/12/2014"
), rating = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 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, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("3",
"5"), class = "factor")), row.names = c(NA, -64L), .Names = c("name",
"stage", "variable", "value", "rating"), class = "data.frame")
names <- as.character(unique(mdfr$name))
names1 <- names[gsub("[^ B]","",names) == " B"]
names1 <- paste("No.",gsub("[ B]","",names1),sep="")
names2 <- rep("",length(names1))
new.names <- c(names1,names2)
ggplot(mdfr, aes(as.POSIXct(as.Date(value, "%d/%m/%Y")), name, colour = factor(stage))) +
geom_line(aes(size=rating)) +
labs(colour="(Baseline/Actual):", x = "", y = "") +
scale_colour_brewer(palette="RdYlGn",breaks = c("1", "3", "6","8"), guide = "none") +
scale_size_manual(breaks = levels(mdfr$rating), values = as.integer(levels(mdfr$rating)), guide = "none") +
scale_y_discrete(breaks=names, labels=new.names)
I would use facets to do this. Below you find a possible solution. This may not be the most elegant solution, but it lets you change the distance between thinner and thicker lines by changing the expand argument in scale_x_discrete.
# numbers to facet by (levels used for order of the facets)
mdfr$nr <- factor(paste0("No.", as.numeric(gsub("A|B", "", mdfr$name))),
levels=unique(paste0("No.", as.numeric(gsub("A|B", "", mdfr$name)))))
# recast your data
df <- dcast(mdfr, nr+stage+rating~variable)
# plot as before, switched x and y values
ggplot(df, aes(x=factor(rating),
ymin=as.POSIXct(as.Date(start_date, "%d/%m/%Y")),
ymax=as.POSIXct(as.Date(end_date, "%d/%m/%Y")),
color=factor(stage),
size=rating
)) +
geom_linerange() + # linerange instead of line
facet_grid(nr~., scales="free_x") + # faceting
coord_flip() + # flip coordinates back
scale_x_discrete(name="", breaks=NULL, expand=c(4,1)) + # use the expand variable to change the distances
scale_colour_brewer(palette="RdYlGn",breaks = c("1", "3", "6","8"), guide = "none") +
scale_size_manual(breaks = levels(mdfr$rating), values = as.integer(levels(mdfr$rating)), guide = "none")
I have a problem getting some words used in facet labels in italics. I use the following code to create new lines for the labels:
levels(length_subject$CONSTRUCTION) <-
c("THAT \n Extraposed", "THAT \n Post-predicate", "TO \n Extraposed \n for-subject", "TO \n Post-predicate \n for-subject", "THAT \n Extraposed \n that-omission", "THAT \n Post-predicate \n that-omission")
However, I want the words "that" and "for" to appear in italics. I've tried something like
"TO \n Extraposed \n (italics(for))-subject"
bit it doesn't work.
This is what the plots look like:
produced with the following code:
ggplot( length_subject, aes( x = SUBJECT ) ) +
geom_histogram(binwidth=.6, colour="black", fill="grey") +
ylab("Frequency") +
xlab("Subject length") +
scale_x_discrete(breaks=c(2,4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30)) + #
facet_grid( SUBJECT_TYPE~CONSTRUCTION, scales="free_x", space="free") +
theme(strip.text.x = element_text(size = 8))
Here is a reduced variant of the data:
structure(list(ID = structure(1:86, .Label = c("A05_122_01",
"A05_253_01", "A05_277_07", "A05_400_01", "A05_99_01", "A06_1076_01",
"A06_1261_01", "A06_1283_01", "A06_1283_02", "A06_1317_01", "A06_1326_01",
"A06_1389_01", "A06_1390_01", "A06_1437_01", "A06_1441_02", "A06_1441_03",
"A06_1442_03", "A06_1456_01", "A06_1461_01", "A06_830_01", "A06_868_01",
"A06_884_01", "A06_884_03", "A0K_1057_02", "A0K_1144_07", "A0K_1177_01",
"A0K_1190_03", "A0K_1214_03", "A0K_1216_01", "A0K_950_02", "A0K_986_01",
"A1A_102_02", "A1A_163_01", "A1A_199_01", "A1A_45_01", "A1A_97_01",
"A1B_1008_02", "A1B_1013_01", "A1B_1028_02", "A1B_1042_01", "A1B_1064_01",
"A1B_1126_03", "A1B_1152_01", "A1B_1174_01", "A1B_1271_01", "A1B_997_01",
"A1J_487_01", "A1J_544_02", "A1J_555_03", "A1J_569_01", "A1J_601_01",
"A1N_422_04", "A1N_70_02", "A1S_191_01", "A1S_329_01", "A1S_330_01",
"A1S_465_04", "A1Y_248_01", "A1Y_278_02", "A1Y_292_01", "A1Y_466_01",
"A1Y_521_01", "A1Y_612_01", "A1Y_634_01", "A26_139_03", "A26_142_01",
"A26_148_01", "A26_289_01", "A26_345_02", "A26_439_01", "A26_441_02",
"A26_463_01", "A28_171_01", "A28_244_01", "A28_245_01", "A28_30_01",
"A28_341_01", "A28_42_01", "A28_494_03", "A2A_301_01", "A2A_396_01",
"A2A_599_01", "A2A_637_01", "A2A_676_01", "A2E_22_01", "A2E_25_03"
), class = "factor"), SUBJECT = c(3L, 2L, 6L, 2L, 2L, 1L, 1L,
1L, 1L, 2L, 4L, 1L, 4L, 2L, 3L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 7L, 1L, 3L, 2L, 2L, 1L, 6L, 7L, 4L, 1L, 5L, 4L, 2L, 9L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 5L, 3L, 4L, 1L, 1L, 1L, 1L, 5L,
2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 5L, 2L, 1L, 2L, 2L, 1L, 7L, 1L,
4L, 1L, 2L, 1L, 1L, 3L, 1L, 13L, 2L, 1L, 1L, 1L, 3L, 1L, 1L),
CONSTRUCTION = structure(c(1L, 3L, 1L, 1L, 1L, 4L, 4L, 1L,
1L, 5L, 5L, 1L, 1L, 5L, 1L, 3L, 5L, 1L, 5L, 4L, 3L, 3L, 1L,
5L, 3L, 5L, 1L, 1L, 2L, 3L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 1L,
4L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 4L, 2L, 4L, 1L, 1L, 3L, 2L,
5L, 1L, 1L, 1L, 3L, 1L, 1L, 4L, 4L, 3L, 1L, 2L, 3L, 3L, 1L,
3L, 1L, 1L, 1L, 6L, 1L, 1L, 2L, 4L, 4L, 3L, 5L, 3L, 3L, 3L,
3L, 5L, 1L), .Label = c("THAT_EXT", "THAT_EXT_NT", "THAT_POST",
"THAT_POST_NT", "TO_EXT_FOR", "TO_POST_FOR"), class = "factor"),
SUBJECT_TYPE = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L,
1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L,
2L, 3L, 1L, 2L, 2L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 1L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L,
1L, 3L, 3L), .Label = c("NP", "PRO", "PROPER"), class = "factor")), .Names = c("ID",
"SUBJECT", "CONSTRUCTION", "SUBJECT_TYPE"), class = "data.frame", row.names = c(NA,
-86L))
To get italics, you need the formatting described in plotmath (and then for that to be parsed as an expression). However, the plotmath syntax does not have a line break operation. You can get something similar with atop, though. With your given example, you can set the labels to
levels(length_subject$CONSTRUCTION) <-
c("atop(textstyle('THAT'),textstyle('Extraposed'))",
"atop(textstyle('THAT'),textstyle('Post-predicate'))",
"atop(atop(textstyle('TO'),textstyle('Extraposed')),italic('for')*textstyle('-subject'))",
"atop(atop(textstyle('TO'),textstyle('Post-predicate')),italic('for')*textstyle('-subject'))",
"atop(atop(textstyle('THAT'),textstyle('Extraposed')),italic('that')*textstyle('-omission'))",
"atop(atop(textstyle('THAT'),textstyle('Post-predicate')),italic('that')*textstyle('-omission'))")
and then adding labeller=label_parsed to the facet_grid call
ggplot( length_subject, aes( x = SUBJECT ) ) +
geom_histogram(binwidth=.6, colour="black", fill="grey") +
ylab("Frequency") +
xlab("Subject length") +
scale_x_discrete(breaks=c(2,4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30)) + #
facet_grid( SUBJECT_TYPE~CONSTRUCTION, scales="free_x", space="free",
labeller=label_parsed) +
theme(strip.text.x = element_text(size = 8))
gives
It's not perfect (the spacing between lines is not the same, and the disparity would only get worse the more lines there are), but that is the only way I've found to combine the two (newlines in plotmath expressions).
Edit (2016)
With the new facet labelling system, this solution does not work anymore. The trick of inheriting from element_blank to make a custom grob is now explicitly disabled. I guess the lesson is to accept that some things cannot be done in ggplot2, by design, and not waste too much energy with workarounds that may get broken at any time in the future.
Original answer
You could try to create a suitable custom element to place in the theme settings. The theme design does not make it very easy, unfortunately,
require(ggplot2)
require(gridExtra) # tableGrob
element_grob.element_custom <- function(element, label="", ...) {
mytheme <- ttheme_minimal(core = list(fg_params = list(parse=TRUE)))
disect <- strsplit(label, "\\n")[[1]]
g1 <- tableGrob(as.matrix(disect), theme=mytheme)
# wrapping into a gTree only because grobHeight.gtable would be too tight
# cf. absolute.units() squashing textGrobs
gTree(children=gList(g1), height=sum(g1$heights),
cl = "custom_strip")
}
# gTrees don't know their size and ggplot would squash it, so give it room
grobHeight.custom_strip = heightDetails.custom_axis = function(x, ...)
x$height
# silly wrapper to fool ggplot2's inheritance check...
facet_custom <- function(...){
structure(
list(...), # this ... information is not used, btw
class = c("element_custom","element_blank", "element") # inheritance test workaround
)
}
title <- c("First~line \n italic('wait, a second')",
"this~is~boring",
"integral(f(x)*dx, a, b)")
iris2 <- iris
iris2$Species <- factor(iris$Species, labels=title)
ggplot(iris2, aes(Sepal.Length, Sepal.Width)) +
geom_line() + facet_grid(.~Species) +
theme(strip.text.x = facet_custom())
As several of you were looking for how to fix the spacing, I have found a solution.
Add a line with atop(scriptscriptstyle("") before the last line from 3 lines (making this 4) or any following lines and don't forget to add ) afterwards