R 散点图

17 Mar 2025 | 5 分钟阅读

散点图用于比较变量。当我们需要定义一个变量受另一个变量影响多少时，需要进行变量之间的比较。在散点图中，数据以点的集合表示。散点图上的每个点都定义了两个变量的值。选择一个变量作为纵轴，另一个变量作为横轴。在 R 中，创建散点图有两种方法，即使用 plot() 函数和使用 ggplot2 包的函数。

以下是在 R 中创建散点图的语法

此处，

序号	参数	描述
1.	x	它是其值是水平坐标的数据集。
2.	y	它是其值是垂直坐标的数据集。
3.	main	它是图表的标题。
4.	xlab	它是水平轴上的标签。
5.	ylab	它是垂直轴上的标签。
6.	xlim	它是用于绘制的 x 值的限制。
7.	ylim	它是 y 值（用于绘制）的限制。
8.	axes	它指示是否应在图上绘制两个轴。

让我们看一个例子来了解如何使用 plot 函数构造散点图。在我们的例子中，我们将使用数据集 "mtcars"，这是 R 环境中可用的预定义数据集。

示例

#Fetching two columns from mtcars
data <-mtcars[,c('wt','mpg')]
# Giving a name to the chart file.
png(file = "scatterplot.png")
# Plotting the chart for cars with weight between 2.5 to 5 and mileage between 15 and 30.
plot(x = data$wt,y = data$mpg, xlab = "Weight", ylab = "Milage", xlim = c(2.5,5), ylim = c(15,30), main = "Weight v/sMilage")
# Saving the file.
dev.off()

输出

使用 ggplot2 的散点图

在 R 中，创建散点图的另一种方法是借助 ggplot2 包。

ggplot2 包提供了 ggplot() 和 geom_point() 函数来创建散点图。 ggplot() 函数接受一系列输入项。第一个参数是一个输入向量，第二个参数是 aes() 函数，我们在其中添加 x 轴和 y 轴。

让我们开始通过一个例子来理解如何使用 ggplot2 包，我们使用了熟悉的数据集 "mtcars"。

示例

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot_ggplot.png")
# Plotting the chart using ggplot() and geom_point() functions.
ggplot(mtcars, aes(x = drat, y = mpg)) +geom_point()
# Saving the file.
dev.off()

输出

我们还可以添加更多特征并制作更具吸引力的散点图。以下是一些添加了不同参数的示例。

示例 1：带分组的散点图

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot1.png")
# Plotting the chart using ggplot() and geom_point() functions.
#The aes() function inside the geom_point() function controls the color of the group.
ggplot(mtcars, aes(x = drat, y = mpg)) +
geom_point(aes(color=factor(gear)))
# Saving the file.
dev.off()

输出

示例 2：轴的变化

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot2.png")
# Plotting the chart using ggplot() and geom_point() functions.
#The aes() function inside the geom_point() function controls the color of the group.
ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color=factor(gear)))
# Saving the file.
dev.off()

输出

示例 3：带有拟合值的散点图

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot3.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) + stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
# Saving the file.
dev.off()

输出

向图表中添加信息

示例 4：添加标题

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot4.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
new_graph<-ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) +
stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
new_graph+
labs(
        title = "Scatterplot with more information"
)
# Saving the file.
dev.off()

输出

示例 5：添加带动态名称的标题

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot5.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
new_graph<-ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) +
stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
#Finding mean of mpg
mean_mpg<- mean(mtcars$mpg)
#Adding title with dynamic name
new_graph + labs(
        title = paste("Adding additiona information. Average mpg is", mean_mpg)
)
# Saving the file.
dev.off()

输出

示例 6：添加副标题

#Loading ggplot2 package
library(ggplot2)
# Giving a name to the chart file.
png(file = "scatterplot6.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
new_graph<-ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) +
stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
#Adding title with dynamic name
new_graph + labs(
        title =
                "Relation between Mile per hours and drat",
        subtitle =
                "Relationship break down by gear class",
        caption = "Authors own computation"
)
# Saving the file.
dev.off()

输出

示例 7：更改 x 轴和 y 轴的名称

#Loading ggplot2 package
library(ggplot2
# Giving a name to the chart file.
png(file = "scatterplot7.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
new_graph<-ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) +
stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
#Adding title with dynamic name
new_graph + labs(
        x = "Drat definition",
        y = "Mile per hours",
        color = "Gear",
        title = "Relation between Mile per hours and drat",
        subtitle = "Relationship break down by gear class",
        caption = "Authors own computation"
)
# Saving the file.
dev.off()

输出

示例 8：添加主题

#Loading ggplot2 package
library(ggplot2
# Giving a name to the chart file.
png(file = "scatterplot8.png")
#Creating scatterplot with fitted values.
# An additional function stst_smooth is used for linear regression.
new_graph<-ggplot(mtcars, aes(x = log(mpg), y = log(drat))) +geom_point(aes(color = factor(gear))) +
stat_smooth(method = "lm",col = "#C42126",se = FALSE,size = 1)
#in above example lm is used for linear regression and se stands for standard error.
#Adding title with dynamic name
new_graph+
theme_dark() +
                labs(
                        x = "Drat definition, in log",
                        y = "Mile per hours, in log",
                        color = "Gear",
                        title = "Relation between Mile per hours and drat",
                        subtitle = "Relationship break down by gear class",
                        caption = "Authors own computation"
                )
# Saving the file.
dev.off()

输出

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R 散点图

示例

使用 ggplot2 的散点图

示例

示例 1：带分组的散点图

示例 2：轴的变化

示例 3：带有拟合值的散点图

向图表中添加信息

示例 4：添加标题

示例 5：添加带动态名称的标题

示例 6：添加副标题

示例 7：更改 x 轴和 y 轴的名称

示例 8：添加主题

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