r - 将网格一侧的 R 图的轴对齐

Question

我有 6 个要在网格上一起绘制的图。我能够绘制 3 个主要对齐的图，以便 y 轴都从这样的同一点开始:



但是在我将第二列图添加到网格(三角形)后，我失去了第一列中的对齐方式。所以它看起来有点像这样:



这是绘制此网格的代码。我一直在使用 align 参数和一些宽度，但没有运气将它们全部一起工作:

plot_grid(pq1_plop, pq1_status, pq2_plop, pq2_status, pq3_plop, pq3_status, 
          align = "hv", 
          nrow = 3, 
          ncol = 2,
          rel_widths = c(10, 1)
          )

有没有办法用左侧的轴对齐来绘制这些？
绘图数据:

> dput(pq1_agged)
structure(list(mean_name = structure(2:6, .Label = c("", "Arrival Logistics and Greetings", 
"Organization of Activity", "Schedule and Offering", "Space Adequacy", 
"Transitions"), class = "factor"), mean_2018 = c(3.60416668653488, 
3.31623927752177, 2.75, 3.125, 3.55555558204651), SY_mean = c(3.3468468479208, 
3.62688970565796, 3.24204542961988, 3.58294574604478, 0), PSELI_mean = c(3.38333333333333, 
3.65522875505335, 3.08235294678632, 3.53529411203721, 0), mean_2017 = c(3.625, 
3.75000002980232, 3.02499997615814, 3.59166663885117, 4), aptsayoy = c("apt", 
"apt", "apt", "apt", "apt"), status = c(2, 2, 2, 2, 2)), row.names = c(NA, 
-5L), class = "data.frame")
> dput(pq2_agged)
structure(list(mean_name = structure(c(2L, 3L, 4L, 11L, 6L, 7L, 
8L, 9L, 10L), .Label = c("", "Helps Youth Socially", "Informal Time: Staff Performance", 
"Social-Emotional Environment", "Staff Build Relationships and Support Individual Youth", 
"Staff Positively Guide Behavior", "Supportive Adults Present", 
"Supportive Social Environment", "Youth Relations with Adults", 
"Youth Relations with Peers", "Staff Build Relationships & Support Individual Youth"
), class = "factor"), mean_2018 = c(NaN, 3.625, 3.19385969011407, 
3.16666666666667, 3.390625, NaN, NaN, 3.19999996821086, 3), SY_mean = c(0, 
3.48106062412262, 3.72575757720254, 3.41504833864611, 3.69877295267014, 
0, 0, 3.32984494885733, 3.62687339339145), PSELI_mean = c(3.45057719920105, 
3.40740741623773, 3.74117646497839, 3.49967318422654, 3.59940157217138, 
3.55519480519481, 3.58463203390955, 3.48692812639124, 3.60947714132421
), mean_2017 = c(NaN, 3.16666674613953, 3.58333335424724, 3.3905701888235, 
3.66687555062143, NaN, NaN, 3.53654969365973, 3.64473684837944
), aptsayoy = c("sayoy", "apt", "apt", "apt", "apt", "sayoy", 
"sayoy", "apt", "apt"), status = c(NA, 6, 2, 2, 2, NA, NA, 2, 
2)), row.names = c(NA, -9L), class = "data.frame")
> dput(pq3_agged)
structure(list(mean_name = structure(2:14, .Label = c("", "Helps Youth Academically", 
"Homework Organization", "Informal Time: Youth Engagement and Behavior", 
"Level of Youth Participation", "Nature of Activity", "Opportunities for Leadership and Responsibility", 
"Staff Effectively Manage HW Time", "Staff Promote Engagement and Stimulate Thinking", 
"Staff Provide Individualized HW Support", "Youth Enjoy and Feel Engaged", 
"Youth Feel Challenged", "Youth Have Choice and Autonomy", "Youth Participation in HW Time"
), class = "factor"), mean_2018 = c(NaN, 3.16666666666667, 3.54464280605316, 
2.62666670481364, 2.03333330154419, NaN, 3.33333337306976, 2.43095239003499, 
3.10000002384186, NaN, NaN, NaN, 2.5), SY_mean = c(2.36415087054335, 
2.36415087054335, 2.36415087054335, 2.36415087054335, 2.36415087054335, 
2.36415087054335, 2.36415087054335, 2.36415087054335, 2.36415087054335, 
2.36415087054335, 2.36415087054335, 2.36415087054335, 2.36415087054335
), PSELI_mean = c(2.69552668942001, 0, 3.60119046105279, 3.10980392904843, 
2.78676470588235, 2.29307360050482, 0, 3.16247088768903, 0, 3.83008658008658, 
3.48051948851837, 2.43499278093313, 0), mean_2017 = c(NaN, 3.5, 
3.57142853736877, 3.22543858226977, 2.04495615080783, NaN, 3.61111108462016, 
2.82832081066935, 3.30000003178914, NaN, NaN, NaN, 3), aptsayoy = c("sayoy", 
"apt", "apt", "apt", "apt", "sayoy", "apt", "apt", "apt", "sayoy", 
"sayoy", "sayoy", "apt"), status = c(NA, 2, 2, 2, 2, NA, 2, 2, 
2, NA, NA, NA, 2)), row.names = 2:14, class = "data.frame")

然后这里是我创建的图:

library(stringr)
library(cowplot)
pq1_plop <-  ggplot(pq1_agged, aes(y=mean_name, x=mean_2018)) + 
  geom_vline(xintercept = 3, size = 0.5, color = "#00C4F3") + #Benchmark static line
  geom_text(data=data.frame(x=3,y=5), aes(x, y), label="Benchmark", hjust=1, vjust=-.2, colour="#4c4c4c") +
  geom_point(aes(x = SY_mean), color="#FD5B14", fill="#FD5B14", size=4, pch=3) + 
  geom_point(aes(x = PSELI_mean), color="#2B85BA", fill="#2B85BA", size=4, pch=3) +
  geom_point(aes(x = mean_2017), color="#BCA8DC", fill="#BCA8DC", size=4, pch=16) + 
  geom_point(color="#612CB5", fill="#612CB5", size=4, pch=16) + 
  #guides(fill=TRUE) + 
  #guides(colour = "colorbar", size = "legend", shape = "legend") + 
  #xlim(1, 4) +
  #xlab("Average Score") +
  ylab("Program Organization \n & Structure") + 
  scale_y_discrete(labels = function(mean_2018) str_wrap(mean_2018, width = 60)) +
  scale_x_continuous(sec.axis = dup_axis(), lim = c(1, 4)) + 
  theme_bw() + 
  theme(legend.text = element_text(colour="black", size = 8),
        legend.position="middle",
        axis.title.x =element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        #axis.line.x.top = element_blank(),
        #axis.text.x.top = element_text(size=8),
        axis.title.y = element_text(angle = 0, vjust = 0.5),
        panel.grid.minor.x = element_line(colour = "#cccccc",
                                          linetype = "solid"),
        panel.grid.major.x = element_line(colour = "#b2b2b2",
                                          linetype = "solid"),
        panel.grid.major.y = element_line(colour = "#7f7f7f",
                                          linetype = "solid"),
        panel.border = element_blank()
  )

pq2_plop <-  ggplot(pq2_agged, aes(y=mean_name, x=mean_2018)) + 
  geom_vline(xintercept = 3, size = 0.5, color = "#00C4F3") + #Benchmark static line
  geom_point(aes(x = SY_mean), color="#FD5B14", fill="#FD5B14", size=4, pch=3) + 
  geom_point(aes(x = PSELI_mean), color="#2B85BA", fill="#2B85BA", size=4, pch=3) +
  geom_point(aes(x = mean_2017), color="#BCA8DC", fill="#BCA8DC", size=4, pch=16) +
  geom_point(color="#612CB5", fill="#612CB5", size=4, pch=16) + 
  #guides(fill=NA) + 
  #guides(colour = "colorbar", size = "legend", shape = "legend") + 
  xlim(1, 4) +
  #xlab("Average Score") +
  ylab("Supportive Environment") + 
  scale_y_discrete(labels = function(mean_2018) str_wrap(mean_2018, width = 60)) + 
  theme_bw() + 
  theme(legend.text = element_text(colour="black",size=10),
        legend.position="middle",
        axis.title.x = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        axis.line.x  = element_blank(),
        axis.title.y = element_text(angle = 0, vjust = 0.5),
        panel.grid.minor.x = element_line(colour = "#cccccc",
                                          linetype = "solid"),
        panel.grid.major.x = element_line(colour = "#b2b2b2",
                                          linetype = "solid"),
        panel.grid.major.y = element_line(colour = "#7f7f7f",
                                          linetype = "solid"),
        panel.border = element_blank()
  )

pq3_plop <-  ggplot(data = pq3_agged, aes(y=mean_name, x=mean_2018,fill='lightgreen')) + 
  geom_vline(xintercept = 3, size = 0.5, color = "#00C4F3") + #Benchmark static line
  geom_point(aes(x = SY_mean), color="#FD5B14", fill="#FD5B14", size=4, pch=3) + 
  geom_point(aes(x = PSELI_mean), color="#2B85BA", fill="#2B85BA", size=4, pch=3) +
  geom_point(aes(x = mean_2017), color="#BCA8DC", fill="#BCA8DC", size=4, pch=16) +
  geom_point(color="#612CB5", fill="#612CB5", size=4, pch=16) + 
  #guides(fill = guide_legend(reverse=TRUE)) + 
  #guides(colour = "colorbar", size = "legend", shape = "legend") + 
  xlim(1, 4) +
  #xlab("Average Score") +
  ylab("Engagement in Activities \n and Learning") + 
  scale_fill_identity(name = 'the fill', guide = 'legend', labels = c('m1')) +
  scale_colour_manual(name = 'the colour', 
                      values =c('black'='black','red'='red'), 
                      labels = c('c2','c1')) + 
  scale_y_discrete(labels = function(mean_2018) str_wrap(mean_2018, width = 60)) + 
  theme_bw() + 
  theme(legend.text = element_text(colour="black",size=10),
        legend.position="top",
        legend.background = element_rect(fill = "blue"),
        axis.title.x = element_blank(),
        #axis.line.x = element_blank(),
        axis.text.x = element_text(size = 8), 
        axis.title.y = element_text(angle = 0, vjust = 0.5), 
        panel.grid.minor.x = element_line(colour = "#cccccc",
                                          linetype = "solid"),
        panel.grid.major.x = element_line(colour = "#b2b2b2",
                                          linetype = "solid"),
        panel.grid.major.y = element_line(colour = "#7f7f7f",
                                          linetype = "solid"),
        panel.border = element_blank()
  )


#Start plotting
pq1_status <- ggplot(pq1_agged, aes(x = "", y = mean_name)) + 
  geom_point(aes(fill = as.factor(status), color = as.factor(status), shape = as.factor(status)), size = 2, show.legend = FALSE) +
  scale_shape_manual(values = c("2" = 25, "6" = 24, "8" = 15)) +
  theme_bw() + 
  scale_fill_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) +
  scale_color_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) + 
  xlab(NULL) +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank(),
        axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.ticks.y=element_blank(),
        panel.border = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank()
  )

pq2_status <- ggplot(pq2_agged, aes(x = "", y = mean_name)) + 
  geom_point(aes(fill = as.factor(status), color = as.factor(status), shape = as.factor(status)), size = 2, show.legend = FALSE) +
  scale_shape_manual(values = c("2" = 25, "6" = 24, "8" = 15)) +
  theme_bw() + 
  scale_fill_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) +
  scale_color_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) +  
  xlab(NULL) +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank(),
        axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.ticks.y=element_blank(),
        panel.border = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank()
  )

pq3_status <- ggplot(pq3_agged, aes(x = "", y = mean_name)) + 
  geom_point(aes(fill = as.factor(status), color = as.factor(status), shape = as.factor(status)), size = 2, show.legend = FALSE) +
  scale_shape_manual(values = c("2" = 25, "6" = 24, "8" = 15)) +
  theme_bw() + 
  scale_fill_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) +
  scale_color_manual(values = c("2" = "red", "6" = "green", "8" = "grey")) + 
  xlab(NULL) +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank(),
        axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.ticks.y=element_blank(),
        panel.border = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank()
  )

Answer 1

您可以使用 patchwork .目前有几个包可以对齐绘图(例如， cowplot 、 egg 、 ggpubr )，但是对于这种更复杂的情况，只有 patchwork为我工作(它相对易于使用；语法很直观)。

# devtools::install_github("thomasp85/patchwork")
library(patchwork)

pq1_plop + pq1_status + pq2_plop + pq2_status + pq3_plop + pq3_status +
plot_layout(ncol = 2, widths = c(10, 1))

与 patchwork您只需添加 ( + ) 一个 ggplot2绘制到另一个并最终指定布局(使用 plot_layout )。