如何在ggplot中以每组的误差线绘制点？

Rollo99

我有以下数据框：


mlt = structure(list(V1 = c("Female > 55", "Male > 55", "Finance Industry", 
"South"), climatechange = c(0.116, 0.093, -0.186, 0.311), `SE climatechange` = c(0.299720594648884, 
0.209685397712576, 0.198822469025311, 0.220794746780239), housing = c(-0.223, 
0.288, -0.063, -0.401), `SE housing` = c(0.240842826106496, 0.262613125585529, 
0.233796203318591, 0.112279926339202), macro = c(-0.219, -0.243, 
0.252, 0.058), `SE macro` = c(0.167027449787956, 0.109527362813708, 
0.225740740488032, 0.139837005156927), `pension and savings` = c(0.287, 
0.815, 0.348, -0.611), `SE pension and savings` = c(0.278129111903788, 
0.26508680711124, 0.250889015745089, 0.0571662145564419)), row.names = c(NA, 
-4L), class = "data.frame")

View(df)

数据框有4个主题，每个主题都有相应的标准误差。到目前为止，我只绘制了第一个主题：

mlt1 = mlt[,c(1:3)]

ggplot(mlt1, aes(V1, climatechange,
                 ymin = climatechange - 1.96*`SE climatechange`, ymax= climatechange + 1.96*`SE climatechange`)) +
  scale_x_discrete('') +
  scale_y_continuous('Marginal Effect \n',limits=c(-1,1)) +
  theme_classic() +
  theme(panel.border = element_rect(fill=NA)) + geom_errorbar(aes(x = V1, y = climatechange),
                                                              size=0.8,width=.2, col = "#0072B2") + 
  geom_point(aes(fill=factor(climatechange)), size=5, shape = 21) +
  scale_fill_manual(values=c(rep("#0072B2",13))) + 
  geom_hline(yintercept=0, col = "grey")  + theme(legend.position="none") + theme(axis.text = element_text(color = "black", size = 12),
                                                       axis.title = element_text(size = 12)) + labs(title="Climate Change") +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
  theme(axis.text.x = element_text(angle = 45, hjust = 0.5, vjust = 0.5))

不过，我想做的就是得到一个看起来像这样的图：

在这里，而不是A，B...。我有四个主题，每个主题都显示相应的变量。环顾四周，我发现有人使用过：facet_grid(.~Test, space = "free_x", shrink = T, scales = "free_x")。然而; 我不确定如何应用于我的数据集。

谁能帮我？

谢谢！

安德鲁·巴克斯特

要做到所有四个-首先你需要转动几次，使数据帧整洁（即创建一个列measure（主题），mean和SE），然后创建数据帧由测量变量刻面：

mlt %>% 
  pivot_longer(2:9, 
               names_to = c("measure"), 
               values_to = "est") %>%
  mutate(stat = ifelse(str_detect(measure, "^SE"), "SE", "mean"),
         measure = str_extract(measure, "\\w*$")) %>% 
  pivot_wider(names_from = "stat",
              values_from = "est", 
              id_col = c(V1, measure)) %>% 
  ggplot(aes(x = V1, mean,
             ymin = mean - 1.96*SE,
             ymax = mean + 1.96*SE)) +
  scale_x_discrete('') +
  scale_y_continuous('Marginal Effect \n', 
                     # limits=c(-1,1)
  ) +
  coord_cartesian(ylim = c(-1, 1)) +
  theme_classic() +
  theme(panel.border = element_rect(fill=NA)) + 
  geom_errorbar(size=0.8,width=.2, col = "#0072B2") + 
  geom_point(size=5, shape = 21) +
  scale_fill_manual(values=c(rep("#0072B2",13))) + 
  geom_hline(yintercept=0, col = "grey")  + 
  theme(legend.position="none") + 
  theme(axis.text = element_text(color = "black", size = 12),
        axis.title = element_text(size = 12)) + labs(title="Climate Change") +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
  theme(axis.text.x = element_text(angle = 45, hjust = 0.5, vjust = 0.5)) +
  facet_wrap(~measure, nrow = 1)