如何使用 map 和 ggplot 为每个图表添加自定义标题？

Question

我有一个数据集，我想通过使用 purrr 中的 map() 为每个具有适当标题的变量制作简单的条形图。

我的数据集有 4 个变量，我有一个带有 4 个标题的向量。如何通过这些标题，以便 R 输出一个具有适当标题的图？对于我的最终结果，我想要 4 个地块，每个地块都有适当的标题（而不是 16 个地块，每个地块都是标题和地块的可能排列）。

我试过查看这个answer，但我的标题包含在另一个向量中。这个post 让我尽我所能。

这是我的数据和标题向量：

library(dplyr)
test <- tibble(s1 = c("Agree", "Neutral", "Strongly Disagree"),
               s2rl = c("Agree", "Neutral", "Strongly Disagree"),
               f1 = c("Strongly Agree", "Disagree", "Strongly Disagree"),
               f2rl = c("Strongly Agree", "Disagree", "Strongly Disagree"))

titles <- c("S1 results", "Results for S2RL", "Fiscal Results for F1", "Financial Status of F2RL")

这是我正在构建的自定义函数，它需要 2 个输入、变量和标题（数据集是硬编码的），以及我的地图函数不起作用：

library(purrr)
library(dplyr)
library(ggplot2)

my_plots = function(variable) {
  test %>%
    count({{variable}}) %>%
    mutate(percent = 100*(n / sum(n, na.rm = T))) %>%
    ggplot(aes(x = {{variable}}, y = percent, fill = {{variable}})) + 
    geom_bar(stat = "identity") +
    ylab("Percentage") +
    ggtitle(paste(title, "N =", n)) +
    coord_flip() +
    theme_minimal() +
    scale_fill_manual(values = c("Strongly disagree" = "#CA001B", "Disagree" = "#1D28B0", "Neutral" = "#D71DA4", "Agree" = "#00A3AD", "Strongly agree" = "#FF8200")) +
    scale_x_discrete(labels = c("Strongly disagree" = "Strongly\nDisagree", "Disagree" = "Disagree", "Neutral" = "Neutral", "Agree" = "Agree", "Strongly agree" = "Strongly\nAgree"), drop = FALSE) + 
    theme(axis.title.y = element_blank(),
          axis.text = element_text(size = 9, color = "gray28", face = "bold", hjust = .5),
          axis.title.x = element_text(size = 12, color = "gray32", face = "bold"),
          legend.position = "none",
          text = element_text(family = "Arial"),
          plot.title = element_text(size = 14, color = "gray32", face = "bold", hjust = .5)) +
    ylim(0, 100)
}

test%>%
  map(~my_plots(variable = .x, titles))

Answer 1

最好转换为symbol 并评估 (!!) 而不是{{}} 或使用.data

library(dplyr)
library(purrr)
library(ggplot2)
library(ggpubr)
my_plots = function(variable, title) {
  test %>%
    count(!! rlang::sym(variable)) %>%
    mutate(percent = 100*(n / sum(n, na.rm = TRUE))) %>%
    ggplot(aes(x = !! rlang::sym(variable), y = percent, fill = .data[[variable]])) + 
    geom_bar(stat = "identity") +
    ylab("Percentage") +
    ggtitle(title) +
    coord_flip() +
    theme_minimal() +
    scale_fill_manual(values = c("Strongly disagree" = "#CA001B", "Disagree" = "#1D28B0", "Neutral" = "#D71DA4", "Agree" = "#00A3AD", "Strongly agree" = "#FF8200")) +
    scale_x_discrete(labels = c("Strongly disagree" = "Strongly\nDisagree", "Disagree" = "Disagree", "Neutral" = "Neutral", "Agree" = "Agree", "Strongly agree" = "Strongly\nAgree"), drop = FALSE) + 
    theme(axis.title.y = element_blank(),
          axis.text = element_text(size = 9, color = "gray28", face = "bold", hjust = .5),
          axis.title.x = element_text(size = 12, color = "gray32", face = "bold"),
          legend.position = "none",
          text = element_text(family = "Arial"),
          plot.title = element_text(size = 14, color = "gray32", face = "bold", hjust = .5)) +
    ylim(0, 100)
}

然后遍历map2中的列名和标题并应用函数

out <- map2(names(test), titles, ~ my_plots(variable = .x, title = .y))
ggarrange(plotlist = out, ncol = 2, nrow = 2)

-输出