# R 语言可视化

# 常用绘图参数速查

type ： "p" 点， "l" 线， "b" 点线；常用于 plot / lines 。
pch ：点形状，整数或字符；常见 16 (实心圆)、19 (大实心圆)、21 (填充圆)。
col / border / fill ：颜色； col.axis / col.lab / col.main 控制轴 / 标签 / 标题颜色。
cex ：整体缩放； cex.axis / cex.lab / cex.main 控制字号缩放。
lwd ：线宽； lty 线型 (1 实线，2 虚线，3 点线)。
xlab / ylab / main / sub ：轴标签与标题。
xlim / ylim ：坐标轴范围； las 坐标轴刻度文字方向。
mfrow / mfcol ： par 的多面板布局。
legend ： legend(x, legend, col, pch, lwd, lty, bty="n") 添加图例。

# 1. 基础绘图

散点图： plot(x, y, type="p", pch=16, col=...) ，可加 legend() ；叠加回归线 abline(lm(y ~ x)) 。

set.seed(1145)
x <- sample(1:100, 80)
y <- 2 * x + 20 + rnorm(80, 0, 10)
plot(x, y, pch = 16, col = "blue", main = "Scatter Plot")
abline(lm(y ~ x), col = "coral", lwd = 2)

# 2. 条形图与帕累托

横向条形： barplot(vals, horiz=TRUE, names=..., col=...) ； DescTools::BarText 添加数值。
帕累托：排序后 barplot ，叠加累计曲线 lines(cumsum(x)/sum(x)) 。

df <- read.csv("resources/data/example3_1.csv")
b <- barplot(df$Beijing, horiz = TRUE, names = df$Expenditure.items, col = "lightblue")
DescTools::BarText(df$Beijing, b = b, horiz = TRUE)
x <- sort(df$Beijing, decreasing = TRUE)
bar <- barplot(x, col = "skyblue")
lines(cumsum(x)/sum(x), type = "b", pch = 15)

# 3. 直方图与密度

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df <- read.csv("resources/data/example3_3.csv")
hist(df$turnover, breaks = 20, prob = TRUE, col = "lightblue")
lines(density(df$turnover), col = "coral", lwd = 2)

# 4. 箱线图

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df3_4 <- read.csv("resources/data/example3_4.csv")
boxplot(df3_4, xlab = "College", ylab = "English Score", col = RColorBrewer::brewer.pal(5, "Set3"))
points(apply(df3_4, 2, mean), col = "blue3", pch = "+", cex = 1.5)

# 5. 散点、气泡与线图

df3_5 <- read.csv("resources/data/example3_5.csv")
plot(df3_5$per.capita.GDP, df3_5$Total.retail.sales.of.consumer.goods, pch = 19, col = "steelblue")
abline(lm(df3_5$Total.retail.sales.of.consumer.goods ~ df3_5$per.capita.GDP), col = "coral", lwd = 2)

symbols(x=df3_5$per.capita.GDP,
        y=df3_5$Total.retail.sales.of.consumer.goods,
        circles=df3_5$General.budgetary.expenditures.of.local.governments,
        inches=0.2, bg="pink")

# 6. 多系列 / 双轴折线

stock <- readxl::read_excel("resources/data/stock.xlsx")
plot(stock$year, stock$SP, type = "b", pch = 16, col = "steelblue")
par(new = TRUE)
plot(stock$year, stock$SQ, type = "b", pch = 17, col = "coral", axes = FALSE, xlab = "", ylab = "")
axis(side = 4); mtext("价格", side = 4, line = 3)

# 7. 雷达与面积图

df3_6 <- read.csv("resources/data/example3_6.csv")
ggiraphExtra::ggRadar(data = df3_6, rescale = FALSE, aes(group = Regional), alpha = 0, size = 2)

library(reshape2); library(ggplot2)
df <- reshape2::melt(read.csv("resources/data/example3_7.csv"), id.vars = "year")
ggplot(df, aes(x = year, y = value, color = variable, group = variable)) +
  geom_line() + geom_point()

# 8. 多图布局

par(mfrow = c(r, c)) 设置面板。

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par(mfrow = c(1, 2))
plot(1:5, main = "A")
plot(5:1, main = "B")

# R 语言可视化

# 常用绘图参数速查

# 1. 基础绘图

# 2. 条形图与帕累托

# 3. 直方图与密度

# 4. 箱线图

# 5. 散点、气泡与线图

# 6. 多系列 / 双轴折线

# 7. 雷达与面积图

# 8. 多图布局

R 语言数据结构

R 语言统计应用