将R的轴对齐在网格的一侧

Question

我有6个情节,我试图在网格上一起绘制.我能够绘制出3个主要对齐良好的对齐,以便y轴全部在同一点开始,如下所示:

但是在我将第二列图表添加到网格(三角形)后,我在第一列中丢失了对齐.所以看起来有点像这样:

这是绘制此网格的代码.我一直在使用align参数和一点宽度,但没有运气让它们一起工作:

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)
          )

有没有办法在左侧轴对齐的情况下绘制这些图？情节数据:

> 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")

接下来是我创建的图:

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

你可以用patchwork.目前,有一对夫妇可以对齐地块包(例如,. ,cowplot,egg,ggpubr但这个更复杂的情况下,只),patchwork工作对我来说(和它的相对易用;语法是直观).

# 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))

有了patchwork你只需要添加(+)一个ggplot2情节到另一个,并在末尾指定布局(使用plot_layout).

Answer 2

一般来说，它可能是一个带有以下内容的单行代码cowplot：

plot_grid(pq1_plop, pq1_status, pq2_plop, pq2_status, pq3_plop, pq3_status,
          ncol = 2, nrow = 3, align = "v")

但是因为你的*_status绘图有点不正常，我们需要构建一个嵌套的绘图网格：

plot_grid(plot_grid(pq1_plop, pq2_plop, pq3_plop, 
                    ncol = 1, rel_heights = c(5, 9, 13), align = "v"), 
          plot_grid(pq1_status, pq2_status, pq3_status, 
                    ncol = 1, rel_heights = c(5, 9, 13)), 
          nrow = 1, rel_widths = c(10, 1))

owplot 的美妙之处在于您可以轻松定义相对宽度和高度（无需深入研究对象和单位）。这样，我们可以强制每个图中水平线之间的间隔大小大致相同。

patchwork与：相同

pq1_plop + pq1_status + pq2_plop + pq2_status + pq3_plop + pq3_status +
    plot_layout(ncol = 2, widths = c(10, 1), heights = c(5, 9, 13))