{see}：研究好物分享！能将统计模型画成图，还能拼接多个图片～

install.packages("see")
library(see)

# 先安装，后续会用到
install.packages("parameters")
install.packages("performance")
install.packages("effectsize")
install.packages("correlation")
install.packages("qqplotr") # 作图
install.packages("ggplot2") # 作图

# 数据1
data("ToothGrowth")
summary(ToothGrowth)

# 数据2
data("mtcars")

mtcars$am_factor <- factor(mtcars$am)
mtcars$cyl_factor <- factor(mtcars$cyl)

summary(mtcars)

library(parameters)

# 拟合模型
model <- lm(len ~ supp * dose, data = ToothGrowth)

# 作图
plot(parameters(model))

library(performance)

# 拟合模型
model1 <- lm(len ~ supp, data = ToothGrowth)

# 作图
plot(check_normality(model1), type = "qq")

library(correlation)

model3 <- correlation(mtcars[, c(1, 3:7)])

plot(summary(model3), show_data = "points")

library(ggplot2)

# 兼容ggplot2，修改x轴上标签
plot(parameters(model)) + 
  xlab("Coefficients")

ggplot(mtcars, aes(x = am_factor, y = mpg, fill = am_factor)) +
  geom_violinhalf() +
  theme_lucid() +
  scale_fill_material_d()

ggplot(mtcars, aes(x = am_factor, y = mpg, fill = am_factor)) +
  geom_violindot(size_dots = 6, 
                 fill_dots = "grey") +
  theme_lucid()

p1 <- ggplot(mtcars, aes(x = cyl_factor, y = mpg, fill = cyl_factor)) +
  geom_boxplot() +
  scale_fill_material(palette = "full")

p2 <- ggplot(mtcars, aes(x = cyl_factor, y = mpg, fill = cyl_factor)) +
  geom_col(width = 0.5) +
  scale_fill_material_d(palette = "ice")

p3 <- ggplot(mtcars, aes(x = mpg, y = disp, color = wt)) +
  geom_point() +
  scale_color_material_c(palette = "contrast")

# 拼接并排列多个图
plots(p1, p2, p3, 
      n_columns = 1)

plots(p1, p2, p3,
      n_rows = 2, 
      title = "MTCARS", 
      tags = paste("Fig. ", LETTERS[1:3])
)

p <- ggplot(mtcars, aes(x = mpg, y = wt, color = am_factor)) +
  geom_point() +
  labs(color = "Transmission\n 0 = automatic\n 1 = manual")
p

p + theme_lucid()

p + theme_abyss()

[1]. https://easystats.github.io/see/