如何用ggplot2绘制多数据集折线图并保存为PDF（带图例）

Got it, let's convert your base R plot to a clean ggplot2 version with proper legends and save it as a PDF. The key here is reshaping your wide-format matrices into tidy long-format data, which plays nicely with ggplot's grammar.

First, here's the complete code with explanations:

# Load required library
library(tidyverse)

# Generate your original data (added set.seed for reproducibility)
set.seed(123)
mean <- replicate(10, rnorm(10))
colnames(mean) <- paste0(rep(c("x0","x1","x2","x3","x4"),2),"_c", rep(c(1:2), each=5))
meanpos <- replicate(10, rnorm(10)) + 1.5
meanneg <- replicate(10, rnorm(10)) - 1.5
hcol <- c(0,0.5,0,0.75,1.0, 1.1,1.20,0,0.8,-0.025)

# Reshape data to long format (required for ggplot)
# Convert each matrix to a tidy data frame with group labels
mean_df <- as.data.frame(mean) %>%
  mutate(sl_no = 1:n()) %>%
  pivot_longer(-sl_no, names_to = "Variable", values_to = "Value") %>%
  mutate(Group = "Mean")

meanpos_df <- as.data.frame(meanpos) %>%
  mutate(sl_no = 1:n()) %>%
  pivot_longer(-sl_no, names_to = "Variable", values_to = "Value") %>%
  mutate(Group = "Mean + 1.5")

meanneg_df <- as.data.frame(meanneg) %>%
  mutate(sl_no = 1:n()) %>%
  pivot_longer(-sl_no, names_to = "Variable", values_to = "Value") %>%
  mutate(Group = "Mean - 1.5")

# Combine all data frames into one
combined_data <- bind_rows(mean_df, meanpos_df, meanneg_df)

# Create a separate data frame for the horizontal reference lines
hline_data <- tibble(Variable = colnames(mean), hcol = hcol)

# Build the ggplot
plot <- ggplot(combined_data, aes(x = sl_no, y = Value, color = Group)) +
  # Add the three line series
  geom_line(linewidth = 1) +
  # Add purple horizontal reference lines per facet
  geom_hline(data = hline_data, aes(yintercept = hcol), color = "purple", linetype = "dashed") +
  # Arrange facets in 2 rows and 5 columns (fits all 10 variables perfectly)
  facet_wrap(~ Variable, nrow = 2, ncol = 5) +
  # Customize labels and title
  labs(x = "sl no", y = "Value", title = "Line Plots with Mean, Mean ±1.5 and Reference Lines") +
  # Set custom colors matching your original plot
  scale_color_manual(values = c("Mean" = "black", "Mean + 1.5" = "blue", "Mean - 1.5" = "green")) +
  # Use a clean theme
  theme_bw() +
  # Adjust theme elements for readability
  theme(
    plot.title = element_text(hjust = 0.5), # Center the plot title
    legend.position = "bottom", # Move legend to bottom for better space
    axis.text = element_text(size = 8), # Shrink axis text to fit facets
    strip.text = element_text(size = 8) # Shrink facet labels
  )

# Save the plot as a PDF
ggsave("line_plots.pdf", plot, width = 12, height = 6, dpi = 300)

Key Notes: #

• Tidy Data: We converted each wide matrix into a long-format data frame with pivot_longer, which lets ggplot easily map groups to colors.
• Faceting: facet_wrap with nrow=2 and ncol=5 arranges all 10 variable plots into a neat grid (your original mention of 2x2 might have been a typo, but if you really want 2x2, you can adjust the nrow/ncol values—though it will only show 4 plots at a time).
• Legends: The color=Group aesthetic automatically creates a legend, which we customized with scale_color_manual to match your original line colors.
• Saving: ggsave lets you specify the output file, dimensions, and resolution. Adjust width and height as needed for your preferred layout.

This code will produce a PDF with all 10 subplots, each showing the three line series and the purple reference line, plus a clear legend at the bottom.

内容的提问来源于stack exchange，提问作者MNU