r - 使用变量标签作为标题和轴标题时自动化 ggplots
问题描述
我有点混淆了 NSE 和绘图功能。我试图在使用变量标签(而不是名称)标记轴等的同时自动绘制几个图。假设我们有一个大型数据集,其中所有变量都已标记。这里的小例子:
library(tidyverse)
library(sjlabelled)
library(ggplot2)
library(cowplot)
data("diamonds")
diamonds <- diamonds %>%
var_labels(
cut ="nice cut",
color = "all colours",
clarity = "very claity all",
depth = "test depth")
我想要的基本情节是这样的:
p1 <- ggplot(diamonds, aes(x = cut, y = depth)) + geom_boxplot(aes(fill = cut)) +
theme_cowplot() +
lab(title = "Plot of test depth ~ nice cut", #based on label variable
x = "nice cut", #based on label variable
y = "test depth", #based on label variable
fill = "nice cut") #based on label variable
p1
我想通过循环其他变量来自动化这个情节。vars
所以我想要单独的列箱线图depth
以下是我想要做的。
#firstly i think i should have labels separately (wondering is there a way I can use them directly from variable label?)
my_labels <- c(
cut = "nice cut",
color = "all colours",
clarity = "very claity all",
depth = "test depth"
)
#plot function
plot_f <- function(df, x_var, y_var, x_var_label, y_var_label) {
ggplot(df, aes(x = {{x_var}}, y = {{y_var}})) + geom_boxplot(aes(fill = {{x_var}})) +
theme_cowplot() + labs(title = paste("Plot of", {{x_var_label}}, "~", {{y_var_label}}),
x = {{x_var_label}},
y = {{y_var_label}},
fill = {{x_var_label}})
}
#variables to cycle through
vars <- c("cut", "color", "clarity")
plot_list <- vars %>%
pmap(~plot_f(diamonds, .x, depth, my_labels)) #need to specify y_var_label & x_var_label, is there a
#way I can just specify my_labels here?
#Finally plot lists
grid.arrange(grobs = plot_list, ncol = 1)
其他代码尝试
这就是我在想的方法,我想知道我是否最好稍后尝试单独添加标签,就像这里使用的那样plot_list$labels
?
#Also tried a for loop which worked but the fill didnt (and also missing the variable labels)
p <- list()
for(i in vars){
p[[i]] <- ggplot(diamonds, aes_string(x = i, y = "depth", fill = i)) + geom_boxplot() +
#note aes_string instead of aes
theme_cowplot()
}
grid.arrange(grobs = p, ncol = 1)
编辑
这个更简单的版本绘图,但绘图没有正确捕获填充,并且显然缺少我想要的变量标签(粘贴等):
#plot function
plot_f <- function(df, x_var, y_var) {
ggplot(df, aes(x = {{x_var}}, y = {{y_var}})) + geom_boxplot(aes(fill = {{x_var}})) +
theme_cowplot()
}
plot_f(diamonds, cut, depth ) #plots fine
#variables to cycle through
vars1 <- c("cut", "color", "clarity")
vars1
#[1] "cut" "color" "clarity"
#unquoted version
vars <- noquote(vars1)
vars
#[1] cut color clarity
#runs
plot_list <- vars %>%
map(., ~plot_f(diamonds, .x, depth))
#plots but fill isn't correct
grid.arrange(grobs = plot_list, ncol = 1)
任何帮助表示赞赏。
解决方案
感谢@aosmith @Tung 的评论,我想出了以下解决方案:
library(cowplot)
library(gridExtra)
library(ggplot2)
library(tidyverse)
my_labels <- c(
cut = "nice cut",
color = "all colours",
clarity = "very claity all",
depth = "test depth"
)
vars <- c("cut", "color", "clarity")
plot_f <- function(df, x_var, y_var, x_var_label, y_var_label) {
ggplot(df, aes(x = .data[[x_var]], y = .data[[y_var]])) +
geom_boxplot(aes(fill = .data[[x_var]])) +
theme_cowplot() +
labs(title = paste("Plot of ", y_var_label, "~", x_var_label), #not .data[[]]
x = x_var_label,
y = y_var_label,
fill = x_var_label)
}
#trick here is that elements of length 1 can be recycled if you wrap it in list
#https://stackoverflow.com/questions/46902461/how-to-pass-a-dataframe-and-uneven-vectors-as-parameters-in-purrr-map
plot_list <- pmap(list(df = list(diamonds), x_var = vars, y_var = list("depth"), x_var_label = my_labels[vars],
y_var_label = list(my_labels[!names(my_labels) %in% vars])), plot_f)
grid.arrange(grobs = plot_list, ncol = 1)
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