RPlot/01.geom_line.R
生信分析 70e1577b61 更新 01.geom_line.R
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2024-12-14 01:22:21 +08:00

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### 模板说明:
### ggplot2画多变量折线图共用x轴
###快速使用(最终推荐)
library(ggplot2)
dat <- reshape::melt(data.frame(
water_press = c(2, 4, 6),
抽气容积 = c(1.5, 4, 6),
充气容积 = c(1, 3, 5)
), "water_press")
pdf("Dr.Liang.pdf", width = 7, height = 5, family = "GB1")
ggplot(dat, aes(x = water_press, y = value, col = variable)) +
theme_classic() +
geom_point() +
geom_line() +
labs(
x = "水检压计",
y = "容积变化",
title = "Dr.Liang 的病生实验",
color = "变量"
) +
scale_color_manual(
#自定义每个变量的颜色
values = c("#000080", "#df6100")
)
dev.off()
###快速使用
# 一、最原始办法——手动画每条变量折线
library(ggplot2)
dat <- data.frame(
water_press = c(2, 4, 6),
out_volumn = c(1.5, 4, 6),
in_volumn = c(1, 3, 5)
)
pdf("Dr.Liang.pdf", width = 7, height = 5, family = "GB1")
ggplot(dat) +
theme_classic() +
geom_point(aes(x = water_press, y = out_volumn, col = "c")) +
geom_line(aes(x = water_press, y = out_volumn, col = "c")) +
geom_point(aes(x = water_press, y = in_volumn, col = "d")) +
geom_line(aes(x = water_press, y = in_volumn, col = "d")) +
ggtitle("Dr.Liang 的病生实验") +
xlab("水检压计") +
ylab("容积变化") +
#手动设置图例
scale_color_manual(
values = c("c" = "#000080", "d" = "#df6100"),
name = "变量",
labels = c("充气容积", "抽气容积")
)
dev.off()
# 二、将dataFrame变为长数据形式后再绘制
library(ggplot2)
dat <- reshape::melt(data.frame(
water_press = c(2, 4, 6),
out_volumn = c(1.5, 4, 6),
in_volumn = c(1, 3, 5)
), "water_press")
pdf("Dr.Liang.pdf", width = 7, height = 5, family = "GB1")
ggplot(dat, aes(x = water_press, y = value, col = variable)) +
theme_classic() +
geom_point() +
geom_line() +
labs(
x = "水检压计",
y = "容积变化",
title = "Dr.Liang 的病生实验",
color = "变量"
) +
scale_color_manual(
#自定义每个变量的颜色
values = c("out_volumn" = "#000080", "in_volumn" = "#df6100"),
# 自定义图例标签, 或者在dataframe里就提前定义好
labels = c("out_volumn" = "抽气容积", "in_volumn" = "充气容积")
)
dev.off()