R语言如何绘制季节图：按年份区分不同线条

Hey there! I see you're looking to create a seasonal plot to compare monthly DENI011 values across years—let's get this done step by step. I'll walk you through loading your data, cleaning it up, and building that year-over-year comparison plot with ggplot2.

1. 加载所需工具包 #

First up, we'll need the tidyverse bundle (it includes ggplot2 for plotting and dplyr for data wrangling) plus lubridate to handle date formatting easily:

# Install packages if you haven't already
install.packages(c("tidyverse", "lubridate"))
library(tidyverse)
library(lubridate)

2. 读取并预处理数据 #

Let's pull in your dataset and tweak it to get the year/month breakdown we need for plotting:

# Load the dataset
df <- read_csv("https://megastore.uni-augsburg.de/get/JVu_V51GvQ/")

# Clean and reshape the data
clean_df <- df %>%
  # Convert your date column to a proper date format (adjust ymd() to dmy()/mdy() if your date format differs!)
  mutate(date = ymd(date)) %>% 
  # Extract year, month labels (Jan/Feb/etc.), and month numbers (for proper x-axis ordering)
  mutate(
    year = year(date),
    month_label = month(date, label = TRUE, abbr = TRUE),
    month_num = month(date)
  ) %>%
  # Keep only the columns we need and drop rows with missing DENI011 values
  select(year, month_label, month_num, DENI011) %>%
  drop_na(DENI011)

Pro tip: If your date column has a non-standard format (like DD/MM/YYYY), swap ymd() for dmy() to avoid errors.

3. 绘制季节图 #

Now let's build the core plot—we'll use lines to represent each year, with color to distinguish them:

ggplot(clean_df, aes(x = month_num, y = DENI011, color = factor(year), group = year)) +
  # Add lines with slight transparency to prevent clutter
  geom_line(alpha = 0.8, linewidth = 1) +
  # Add points to mark individual monthly values (optional but helpful)
  geom_point(size = 2) +
  # Convert x-axis from month numbers to readable abbreviations
  scale_x_continuous(breaks = 1:12, labels = month.abb) +
  # Use a color palette that's easy to distinguish (swap for your favorite if you want!)
  scale_color_viridis_d(option = "plasma", name = "Year") +
  # Add clear titles and labels
  labs(
    title = "Year-over-Year Monthly Comparison of DENI011",
    x = "Month",
    y = "DENI011 Value"
  ) +
  # Use a clean, minimal theme
  theme_minimal() +
  # Tweak layout for better readability
  theme(
    plot.title = element_text(hjust = 0.5, size = 14, face = "bold"),
    axis.title = element_text(size = 12),
    legend.position = "bottom" # Move legend to bottom to avoid blocking the plot
  )

Optional Tweaks for Extra Polish #

• Highlight a specific year: Add a bold line for a key year (e.g., 2023) by adding this layer:

  geom_line(data = filter(clean_df, year == 2023), linewidth = 1.5, color = "darkred")
  

• Smooth out large value ranges: Switch to a logarithmic y-axis with scale_y_log10() if your DENI011 values have huge swings.
• Add annual averages: Include a dashed line showing the overall monthly average across all years:

  stat_summary(fun = mean, geom = "line", linetype = "dashed", color = "black", linewidth = 1)
  

That should give you a clear, informative seasonal plot that lets you easily compare DENI011 trends across years!

内容的提问来源于stack exchange，提问作者Essi