如何用ggplot2调整双Y轴右侧刻度至0-60范围

我尝试在同一图表中对比两个温度相关变量：

• 最初生成Plot 01，代表第二个变量的绿色曲线无法完全显示在图表内
• 调整代码中的轴变换逻辑生成Plot 02后，右侧Y轴数值不准确，希望将右侧Y轴范围设置为c(0, 60)并从0开始

解决方案 #

双Y轴的核心是建立左右轴的数值映射关系，让感知数据的[0,60]范围对应左侧温度轴的[21,31]显示区间：

1. 转换感知数据到温度轴区间：使用公式(tem.perception / 60) * 10 + 21，将0映射到21，60映射到31，确保曲线能在左侧轴的显示范围内完整呈现
2. 反向生成右侧轴刻度：通过公式(. - 21) * 6将左侧温度值还原为感知数据，保证右侧轴数值准确
3. 替换轴范围控制方式：移除coord_cartesian(ylim = c(21, 31))，改用scale_y_continuous的limits参数控制左侧轴范围，避免数据截断

修改后的完整代码 #

rm(list = ls())   # Resetear o limpiar todos los objetos del area de trabajo
graphics.off()    # Resetear o limpiar area de graficos

# Load necessary libraries
library(ggplot2)
library(tidyr)


# Data
tem.perception <- c(55, 58, 57, 11,  0,  0,  0,  4, 15, 18, 22, 35)

tem.inahmi <- read.table(header = TRUE, sep = ",",
text = "year,ENE,FEB,MAR,ABR,MAY,JUN,JUL,AGO,SEP,OCT,NOV,DIC
1980,25.1,25.1,25.8,24.1,26.3,25.1,26.0,25.1,25.1,23.3,25.1,25.1
1981,27.3,28.3,27.5,27.3,25.3,23.7,22.5,22.7,25.5,25.5,25.5,25.2
1982,25.6,26.9,27.8,28.1,27.6,25.5,25.2,24.5,26.5,26.5,26.5,26.9
1983,26.3,27.3,27.2,26.7,27.0,26.3,25.5,26.3,24.9,25.4,26.3,26.8
1984,27.3,26.8,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1985,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1986,27.3,27.1,27.0,26.7,26.0,23.6,24.6,24.8,24.2,25.4,25.9,26.3
1987,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1988,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1989,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1990,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1991,26.3,27.8,27.6,27.8,27.7,25.6,26.3,23.6,24.8,25.4,25.8,27.3
1992,28.5,27.7,26.0,26.5,25.9,26.0,24.4,24.4,24.4,25.7,25.8,26.7
1993,27.6,27.0,26.8,26.3,24.3,24.2,26.0,26.0,26.0,26.0,26.0,26.0
1994,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
1995,28.3,26.2,28.1,27.7,27.0,26.2,24.1,24.5,25.1,25.6,26.1,25.9
1996,27.4,28.5,27.5,27.6,26.5,24.2,23.1,23.7,24.8,24.8,25.4,26.7
1997,27.4,28.2,28.0,27.3,26.9,26.1,27.0,27.2,28.0,27.1,27.4,27.6
1998,27.8,28.0,27.5,26.7,25.5,24.7,25.2,24.3,26.2,25.3,26.2,26.6
1999,27.5,26.5,26.6,26.2,25.8,25.8,23.6,25.8,24.5,25.8,26.0,25.8
2000,27.6,25.9,26.4,25.9,25.9,25.9,24.1,25.9,25.2,25.9,26.0,25.9
2001,27.1,27.1,27.0,26.7,26.0,25.0,24.6,24.6,25.0,25.4,25.9,27.2
2002,27.3,28.3,27.0,26.7,26.0,25.0,24.6,25.1,25.8,25.4,25.9,26.5
2003,27.7,27.1,28.2,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
2004,28.6,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.5,25.8,27.0
2005,28.3,27.3,26.8,27.4,27.0,26.1,24.7,24.6,24.4,24.7,25.7,26.5
2006,27.6,26.9,26.2,26.3,25.4,24.3,24.2,25.1,25.9,26.1,27.0,27.6
2007,28.1,28.8,28.3,27.0,26.7,24.9,25.0,24.3,25.0,24.7,26.1,26.4
2008,26.2,26.0,25.9,26.0,24.1,22.2,23.3,24.2,25.5,25.3,25.7,26.8
2009,26.7,26.0,26.1,25.9,25.3,24.3,24.7,24.9,25.4,25.9,25.8,26.6
2010,26.8,26.6,26.4,26.0,25.1,24.7,23.6,24.3,24.3,24.8,25.2,26.0
2011,27.6,27.1,27.8,27.2,25.8,25.2,24.1,24.5,25.2,24.7,26.1,26.2
2012,27.3,27.1,27.0,26.7,26.0,25.0,24.6,24.8,25.2,25.4,25.9,26.5
2013,25.2,25.2,25.2,26.4,25.3,24.5,24.3,24.6,24.7,25.2,25.1,26.7
" )

tem.inahmi$year <- as.factor(tem.inahmi$year)  # Convert the 'year' column to a factor

# see max and min
max(tem.perception); min(tem.perception)
max(tem.inahmi[,2:13]); min(tem.inahmi[,2:13])

# Melt the data into long format to have month, year, and value columns
tem.inahmi_melted <- tem.inahmi %>% 
  gather(key = "month", value = "value", -year)

# Creating a month factor variable with custom levels for correct ordering
tem.inahmi_melted$month <- factor(tem.inahmi_melted$month, levels = c("ENE", "FEB", "MAR", "ABR", "MAY", "JUN", "JUL", "AGO", "SEP", "OCT", "NOV", "DIC"))

# Create a dataframe for the geom_line data
tem.geom_line <- data.frame(
  month = factor(c("ENE", "FEB", "MAR", "ABR", "MAY", "JUN", "JUL", "AGO", "SEP", "OCT", "NOV", "DIC"), 
                 levels = c("ENE", "FEB", "MAR", "ABR", "MAY", "JUN", "JUL", "AGO", "SEP", "OCT", "NOV", "DIC")),
  value = (tem.perception / 60) * 10 + 21  # 将感知数据映射到温度轴区间
)

# Construct the basic ggplot2
tem.plot <- ggplot(tem.inahmi_melted, aes(x = month, y = value)) +
  geom_boxplot(aes(colour = "INAMHI"), fill = "NA") +  # Boxplot with blue border
  geom_line(data = tem.geom_line, aes(y = value, colour = "Percepción"), group = 1, size = 0.8) +  # Geom line in red
  scale_color_manual(name = "", values = c("INAMHI" = "#F8766D", "Percepción" = "#00BA38")) +  # Assign colors
  scale_y_continuous(
    limits = c(21, 31),  # 控制左侧轴范围
    sec.axis = sec_axis(~(. - 21) * 6, name = "Percepción [Nro. respuestas]")  # 反向生成右侧轴刻度
  ) +
  
  theme_minimal() +
  xlab("Mes") +
  ylab("Temperatura [°C]")+ 
  labs(title = "TEMPERATURE (Inahmi vs Perception)")  +
  theme(legend.position="bottom",
        axis.title.y = element_text(color = "#F8766D"),  # Y axis label color in blue
        axis.title.y.right = element_text(color = "#00BA38"),  # Second Y axis label color in red
        axis.text.y = element_text(color = "#F8766D"),  # Y axis text color in blue
        axis.text.y.right = element_text(color = "#00BA38"))

print(tem.plot)

内容的提问来源于stack exchange，提问作者Darwin PC