I want to arrange the plot below so that 'group' is arranged in descending order by 'Distance' within Community (Out, In).
I've tried using dplyr::arrange and tidytext::reorder_within(group, -value, MPA_type), but neither of these work - ggplot continues to default to sorted by group name in descending order (see legend). If facetwrap is part of the solution, I'd prefer to have the labels at the bottom as in the example figure, rather than the typical facet header.
Here is my data:
sig_distance <- structure(list(Var1 = structure(c(2L, 2L, 5L, 5L, 2L, 2L, 5L,
5L, 2L, 2L, 5L, 5L, 2L, 2L, 5L, 5L, 2L, 2L, 5L, 5L), .Label = c("ref after",
"ref before", "ref during", "smr after", "smr before", "smr during"
), class = "factor"), Var2 = structure(c(1L, 3L, 4L, 6L, 1L,
3L, 4L, 6L, 1L, 3L, 4L, 6L, 1L, 3L, 4L, 6L, 1L, 3L, 4L, 6L), .Label = c("ref after",
"ref before", "ref during", "smr after", "smr before", "smr during"
), class = "factor"), value = c(0.0781171338765429, 0.070131485880327,
0.124219180798504, 0.0642584499973571, 0.16882716299913, 0.123057288279708,
0.185404402405965, 0.113660097900038, 0.14628853013894, 0.106462687516074,
0.179579889492142, 0.146317072898829, 0.163284273893779, 0.130083096905712,
0.0991349070859965, 0.106610448830353, 0.0499622399107518, 0.0563330614755333,
0.0391975833642552, 0.0435817314833789), MPA = structure(c(3L,
2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L,
2L, 4L, 1L), .Label = c("MPA___before-to-during", "Reference___before-to-during",
"Reference___before-to-after", "MPA___before-to-after"), scores = structure(c(`MPA___before-to-after` = 0.125507192629372,
`MPA___before-to-during` = 0.0948855602219911, `Reference___before-to-after` = 0.121295868163829,
`Reference___before-to-during` = 0.0972135240114708), .Dim = 4L, .Dimnames = list(
c("MPA___before-to-after", "MPA___before-to-during", "Reference___before-to-after",
"Reference___before-to-during"))), class = "factor"), name = c("sd_ref_pooled_before_after",
"sd_ref_pooled_before_during", "sd_smr_pooled_before_after",
"sd_smr_pooled_before_during", "sd_ref_pooled_before_after",
"sd_ref_pooled_before_during", "sd_smr_pooled_before_after",
"sd_smr_pooled_before_during", "sd_ref_pooled_before_after",
"sd_ref_pooled_before_during", "sd_smr_pooled_before_after",
"sd_smr_pooled_before_during", "sd_ref_pooled_before_after",
"sd_ref_pooled_before_during", "sd_smr_pooled_before_after",
"sd_smr_pooled_before_during", "sd_ref_pooled_before_after",
"sd_ref_pooled_before_during", "sd_smr_pooled_before_after",
"sd_smr_pooled_before_during"), sd_pooled = c(0.0640133632403095,
0.059224209496302, 0.0418411590759088, 0.0420366263878186, 0.0697371748889264,
0.0713939572229526, 0.0662209469675998, 0.0673861920919254, 0.0952259175162696,
0.0973881903133112, 0.104688903793631, 0.104123442035945, 0.0831395386888112,
0.0736773344066338, 0.0870890086043125, 0.082205340195828, 0.0622386704700814,
0.0506360166386964, 0.0776340589400514, 0.057490214920967), group = structure(c(1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 2L,
2L, 2L, 2L), .Label = c("Group 5", "Group 4", "Group 3", "Group 2",
"Group 1"), class = "factor"), period = structure(c(1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L), .Label = c("Before-to-after", "Before-to-during"), class = "factor"),
MPA_type = structure(c(1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L), .Label = c("Out",
"In"), class = "factor"), Df = c(1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), SumOfSqs = c(0.644667474362213,
0.163718859184403, 0.531883138574452, 0.172377817596512,
1.36062525175964, 0.561260198791761, 1.26106114133322, 0.478287656340437,
1.12522630961807, 0.502450621711331, 0.779126478533436, 0.349888339609262,
0.64822862542131, 0.198815304465667, 0.329502905266225, 0.124876688005652,
0.197752601704789, 0.10862759418973, 0.142471900603864, 0.0840130152284379
), R2 = c(0.190110542714351, 0.0631029576320754, 0.217228522650464,
0.089364183731598, 0.076782933708657, 0.0349456770960147,
0.0732327885619086, 0.0303186954655169, 0.0788241854776924,
0.0376889492950336, 0.0656167575864088, 0.0312644101580068,
0.288412156204619, 0.123882033933067, 0.158350315762715,
0.0838360162000489, 0.0226863909348303, 0.0137219062151816,
0.0222248102598127, 0.0150399647150649), F = c(9.62419276009816,
2.4247130389196, 11.3779943270621, 3.53281801227694, 10.4792794679964,
4.27290961706825, 9.00823614929462, 3.37679925864692, 10.610568411745,
4.50397942095095, 7.93538804068383, 3.45325589560756, 6.07961811151075,
1.83818447230295, 2.44585620771756, 1.18959949296437, 3.29624747150235,
1.85040460507006, 2.25026799494279, 1.42007459023087), `p-val` = c(0.001,
0.05, 0.001, 0.006, 0.001, 0.001, 0.001, 0.002, 0.001, 0.001,
0.001, 0.005, 0.001, 0.076, 0.017, 0.31, 0.005, 0.069, 0.037,
0.195), sig = c("*", "", "*", "*", "*", "*", "*", "*", "*",
"*", "*", "*", "*", "", "*", "", "*", "", "*", "")), row.names = c(NA,
-20L), class = "data.frame")
Plotting code:
p1 <-
sig_distance %>%
rename("Period"=period)%>%
filter(Period == "Before-to-during")%>%
mutate(group = factor(group))%>%
arrange(MPA_type, -value, group)%>%
ggplot(aes(x=reorder(MPA_type, -value), y=value, color=group,
#shape=group,
#fill=MPA_type
))+
geom_point(position = position_dodge(width=0.8),
size=3)+
geom_errorbar(aes(ymin=value-sd_pooled,
ymax = value+sd_pooled), stat="identity",
position = position_dodge(width=0.8), size=0.3, width=.3)+
#add significance level
geom_text(aes(label=sig), size=5, vjust=-0.01,
position = position_dodge(width=0.8),
show.legend = FALSE)+
ylab("Distance (Bray-Curtis)")+
xlab("Community")+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
legend.key=element_blank())
