nesting scale_manual caracteristics in ggplot
Hi:
The problem is that you use different sets of labels in each
scale_*_manual. To get all of the scales to merge into one, you need
to have the same title, same breaks and same labels for the legend.
This gets you a single legend:
ggplot(data = df, aes(x = year, y = total, colour = treatment,
linetype=treatment)) +
geom_point(aes(shape = treatment)) +
facet_wrap(~country) +
scale_colour_manual(breaks=c('A','B','C','D','E','F','G'),
values=c('A'='black','B'='black', 'C'='grey',
'D'='grey','E'='red','F'='grey', 'G'='red'),
labels=c('A: Line 1','B: Line 2','C: Line3','D: Line 4',
'E: Line 5','F: Line 6','G: Line 7')) +
scale_linetype_manual(breaks=c('A','B','C','D','E','F','G'),
values=c('A'='solid','B'='dotted', 'C'='solid','D'='dashed',
'E'='dashed','F'='dotted', 'G'='dotted'),
labels=c('A: Line 1','B: Line 2','C: Line3','D: Line 4',
'E: Line 5','F: Line 6','G: Line 7')) +
scale_shape_manual(breaks=c('A','B','C','D','E','F','G'),
labels=c('A: Line 1','B: Line 2','C: Line3','D: Line 4',
'E: Line 5','F: Line 6','G: Line 7'),
values = c(0, 1, 2, 3, 4, 5, 6)) +
theme_bw() +
geom_abline(aes(intercept = Intercept, slope = Slope,
colour = treatment, linetype=treatment),
data = lines)
In your original, you had different line numbers as labels in
scale_colour_manual() and scale_shape_manual(). If you want to
maintain that, then you'll have to have separate legends for color and
shape.
HTH,
Dennis
On Tue, Nov 8, 2011 at 11:22 AM, Sigrid <s.stenerud at gmail.com> wrote:
Hi there,
I am having a little problem with combining three scale_manual commands in a
facet plot. ?I am not able to combine the three different characteristics,
instead ending up with three different descriptions next to the graph for
the same geom. ?I would like to see two separate labels (not three); one
describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I
want a combination of color, line type and symbol. ?How do I do this?
Here are my codes (Feel free to modify the example to make it easier to work
with. I was not able to do this while keeping the problem I wanted help
with)
df <-structure(list(year = 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, 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,
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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), treatment =
structure(c(1L,
1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L,
6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L,
5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L,
3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L,
1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L,
7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L,
5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 2L,
2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L,
7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L,
6L, 6L, 6L, 7L, 7L, 7L), .Label = c("A", "B", "C", "D", "E",
"F", "G"), class = "factor"), total = c(135L, 118L, 121L, 64L,
53L, 49L, 178L, 123L, 128L, 127L, 62L, 129L, 126L, 99L, 183L,
45L, 57L, 45L, 72L, 30L, 71L, 123L, 89L, 102L, 60L, 44L, 59L,
124L, 145L, 126L, 103L, 67L, 97L, 66L, 76L, 108L, 36L, 48L, 41L,
69L, 47L, 57L, 167L, 136L, 176L, 85L, 36L, 82L, 222L, 149L, 171L,
145L, 122L, 192L, 136L, 164L, 154L, 46L, 57L, 57L, 70L, 55L,
102L, 111L, 152L, 204L, 41L, 46L, 103L, 156L, 148L, 155L, 103L,
124L, 176L, 111L, 142L, 187L, 43L, 52L, 75L, 64L, 91L, 78L, 196L,
314L, 265L, 44L, 39L, 98L, 197L, 273L, 274L, 89L, 91L, 74L, 91L,
112L, 98L, 140L, 90L, 121L, 120L, 161L, 83L, 230L, 266L, 282L,
35L, 53L, 57L, 315L, 332L, 202L, 90L, 79L, 89L, 67L, 116L, 109L,
44L, 68L, 75L, 29L, 52L, 52L, 253L, 203L, 87L, 105L, 234L, 152L,
247L, 243L, 144L, 167L, 165L, 95L, 300L, 128L, 125L, 84L, 183L,
88L, 153L, 185L, 175L, 226L, 216L, 118L, 118L, 94L, 224L, 259L,
176L, 175L, 147L, 197L, 141L, 176L, 187L, 87L, 92L, 148L, 86L,
139L, 122L), country = structure(c(2L, 2L, 2L, 2L, 2L, 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, 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, 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, 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, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), .Label = c("high", "low"), class = "factor")), .Names = c("year",
"treatment", "total", "country"), class = "data.frame", row.names = c(NA,
-167L))
lines <- structure(list(`Line #` = 1:14, country = structure(c(2L, 2L, 2L,
2L,2L,2L,2L,1L, 1L,1L,1L,1L,1L,1L), .Label = c("high", "low"), class =
"factor"),treatment = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L,1L, 2L,
3L,4L,5L,6L,7L), .Label = c("A", "B", "C","D", "E", "F","G","H" ), class =
"factor"), Intercept = c(81.47, 31.809,69.892,82.059,106.392,45.059,38.809,
67.024, 17.357, 105.107,79.191,91.357,5.691,24.357), Slope = c(47.267,
20.234,33.717,14.667,13.434,25.817,21.967, 47.267, 20.234,
33.717,14.667,13.434,25.817,21.967)), .Names = c("Line #", "country",
"treatment", "Intercept", "Slope"), class = "data.frame", row.names = c(NA,
-14L))
ggplot(data = df, aes(x = year, y = total, colour = treatment,
linetype=treatment)) +
? ? ? ?geom_point(aes(shape = treatment)) +
? ? ?facet_wrap(~country) +
? ? ? ?scale_colour_manual(breaks=c('A','B','C','D','E','F','G'),
values=c('A'='black','B'='black', 'C'='grey','D'='grey',
'E'='red','F'='grey', 'G'='red'), ?labels=c('A: Line 1','B: Line 2','C:
Line3','D: Line 4',
? ? ? ? ? ? ? ? ? ? ? ?'E: Line 5 ','F:Line 6','G:Line 7'))+
scale_linetype_manual(breaks=c('A','B','C','D','E','F','G'),
values=c('A'='solid','B'='dotted', 'C'='solid','D'='dashed',
'E'='dashed','F'='dotted', 'G'='dotted'))+
? ? ? ?scale_shape_manual(breaks=c('A','B','C','D','E','F','G'),
? ? ? ? ? ? ? ?labels=c('A: Line 8','B: Line 9','C: Line 10','D: Line 11',
? ? ? ? ? ? ? ? ? ? ? ?'E: Line 12 ','F:Line 13','G:Line 14'),
? ? ? ? ? ? ? ?values = c(0, 1, 2, 3, 4, 5, 6)) +
? ? ? ?theme_bw()+ geom_abline(aes(intercept = Intercept, slope = Slope,
colour = treatment, linetype=treatment), data = lines)
Thank you,
Sigrid
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