用r语言plot函数绘制iris数据集的条形图,饼图,直方图,散点图,线图,箱线图， 每种类型2张图，体现不同参数值带来的变化

以下是对 iris 数据集绘制不同类型图表的代码和图像。

## 导入数据集
data(iris)
iris <- iris

## 条形图
# 按照花的种类（Species）统计花萼长度（Sepal.Length）的平均值
library(ggplot2)
ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
geom_bar(stat = "summary", fun.y = "mean", position = "dodge") +
labs(title = "Bar Plot of Sepal Length by Species", x = "Species", y = "Sepal Length")

# 按照花的种类（Species）统计花萼宽度（Sepal.Width）的平均值
ggplot(iris, aes(x = Species, y = Sepal.Width, fill = Species)) +
geom_bar(stat = "summary", fun.y = "mean", position = "dodge") +
labs(title = "Bar Plot of Sepal Width by Species", x = "Species", y = "Sepal Width")

## 饼图
# 按照花的种类（Species）统计花瓣长度（Petal.Length）的总和
library(plotrix)
pie3D(tapply(iris$Petal.Length, iris$Species, sum), labels = c("setosa", "versicolor", "virginica"),
main = "Pie Chart of Petal Length by Species")

# 按照花的种类（Species）统计花瓣宽度（Petal.Width）的总和
pie3D(tapply(iris$Petal.Width, iris$Species, sum), labels = c("setosa", "versicolor", "virginica"),
main = "Pie Chart of Petal Width by Species")

## 直方图
# 统计花萼长度（Sepal.Length）的分布情况
par(mfrow = c(1, 2))
hist(iris$Sepal.Length[iris$Species == "setosa"], main = "Histogram of Sepal Length for setosa",
xlab = "Sepal Length", ylab = "Count", col = "blue", border = "white")
hist(iris$Sepal.Length[iris$Species == "versicolor"], main = "Histogram of Sepal Length for versicolor",
xlab = "Sepal Length", ylab = "Count", col = "green", border = "white")

# 统计花萼宽度（Sepal.Width）的分布情况
hist(iris$Sepal.Width[iris$Species == "setosa"], main = "Histogram of Sepal Width for setosa",
xlab = "Sepal Width", ylab = "Count", col = "blue", border = "white")
hist(iris$Sepal.Width[iris$Species == "versicolor"], main = "Histogram of Sepal Width for versicolor",
xlab = "Sepal Width", ylab = "Count", col = "green", border = "white")

## 散点图
# 绘制花萼长度（Sepal.Length）和宽度（Sepal.Width）之间的散点图
plot(iris$Sepal.Length, iris$Sepal.Width, col = iris$Species, pch = 19, main = "Scatter Plot of Sepal Length vs. Width",
xlab = "Sepal Length", ylab = "Sepal Width", xlim = c(4, 8), ylim = c(1.5, 5))

# 绘制花瓣长度（Petal.Length）和宽度（Petal.Width）之间的散点图
plot(iris$Petal.Length, iris$Petal.Width, col = iris$Species, pch = 19, main = "Scatter Plot of Petal Length vs. Width",
xlab = "Petal Length", ylab = "Petal Width", xlim = c(0, 8), ylim = c(0, 3))

## 线图
# 统计花萼长度（Sepal.Length）的变化趋势
library(ggplot2)
ggplot(iris, aes(x = seq(1, nrow(iris)), y = Sepal.Length, group = Species, color = Species)) +
geom_line() +
labs(title = "Line Plot of Sepal Length by Species", x = "Index", y = "Sepal Length")

# 统计花瓣长度（Petal.Length）的变化趋势
ggplot(iris, aes(x = seq(1, nrow(iris)), y = Petal.Length, group = Species, color = Species)) +
geom_line() +
labs(title = "Line Plot of Petal Length by Species", x = "Index", y = "Petal Length")

## 箱线图
# 统计花萼长度（Sepal.Length）的分布情况
par(mfrow = c(1, 2))
boxplot(iris$Sepal.Length ~ iris$Species, main = "Boxplot of Sepal Length by Species", col = "blue")
boxplot(iris$Sepal.Length ~ iris$Species, main = "Boxplot of Sepal Length by Species", col = "green", notch = TRUE)

# 统计花萼宽度（Sepal.Width）的分布情况
boxplot(iris$Sepal.Width ~ iris$Species, main = "Boxplot of Sepal Width by Species", col = "blue")
boxplot(iris$Sepal.Width ~ iris$Species, main = "Boxplot of Sepal Width by Species", col = "green", notch = TRUE)