【R语言编程绘图-折线图】

安装与加载GGPLOT2库

确保已安装ggplot2库，若未安装可通过以下命令安装：

install.packages("ggplot2")

加载库：

library(ggplot2)

准备数据

假设有一个包含时间序列数据的数据框df，包含两列：date（日期）和value（数值）。示例数据生成：

df <- data.frame(
  date = seq(as.Date("2023-01-01"), as.Date("2023-12-31"), by = "month"),
  value = c(15, 18, 22, 25, 30, 28, 26, 24, 20, 18, 16, 14)
)

基础折线图绘制

使用geom_line()绘制折线图：

ggplot(df, aes(x = date, y = value)) +
  geom_line()

自定义折线图样式

调整线条颜色、粗细和添加点标记：

ggplot(df, aes(x = date, y = value)) +
  geom_line(color = "blue", linewidth = 1) +
  geom_point(color = "red", size = 3)

添加标题与坐标轴标签

通过labs()函数设置标题和标签：

ggplot(df, aes(x = date, y = value)) +
  geom_line(color = "blue") +
  labs(title = "Monthly Value Trends (2023)",
       x = "Date",
       y = "Value")

调整坐标轴格式

例如将日期格式化为月份缩写：

ggplot(df, aes(x = date, y = value)) +
  geom_line(color = "blue") +
  scale_x_date(date_labels = "%b") +
  labs(title = "Monthly Trends", x = "Month", y = "Value")

多系列折线图

若数据包含分组（如category列），可通过aes(color)区分不同系列：

df_multi <- data.frame(
  date = rep(seq(as.Date("2023-01-01"), as.Date("2023-06-01"), by = "month"), 2),
  value = c(15, 18, 22, 25, 30, 28, 10, 12, 15, 18, 20, 22),
  category = rep(c("A", "B"), each = 6)
)

ggplot(df_multi, aes(x = date, y = value, color = category)) +
  geom_line() +
  labs(title = "Multi-Series Line Chart")

# 加载必要的库
library(ggplot2)

# 生成数据
df <- data.frame(
  date = seq(as.Date("2023-01-01"), by = "day", length.out = 100),
  value = cumsum(rnorm(100))
)

# 绘制折线图
p <- ggplot(df, aes(x = date, y = value)) +
  geom_line(color = "blue", size = 1) +  # 使用蓝色线条，适当调整线条粗细
  labs(title = "Time Series Plot of Random Values",  # 标题
       x = "Date",  # X轴标签
       y = "Cumulative Sum of Random Values") +  # Y轴标签
  theme_classic() +  # 使用经典主题
  theme(plot.title = element_text(size = 16, face = "bold", hjust = 0.5),  # 标题样式
        axis.title = element_text(size = 14, face = "bold"),  # 轴标题样式
        axis.text = element_text(size = 12),  # 轴刻度标签样式
        legend.position = "none")  # 移除图例（如果不需要）

# 保存为高分辨率图像
ggsave("time_series_plot.png", plot = p, width = 8, height = 6, dpi = 300)

# 显示图像
print(p)