R语言合并列名不同的两个数据框并执行melt长表转换的方法

方案1：tidyverse实现（推荐，代码易维护） #

首先安装并加载依赖包：

install.packages("tidyverse")
library(tidyverse)

处理并合并数据框代码：

# 处理df1为目标长表结构
df1_long <- df1 %>%
  rename(sum = weight) %>%
  mutate(var = "weight") %>%
  select(treatment, var, sum, sd)

# 处理df2为目标长表结构，先统一列名
df2_long <- df2 %>%
  rename(
    treatment = treatment2,
    sum = area,
    sd = sd2
  ) %>%
  mutate(var = "area") %>%
  select(treatment, var, sum, sd)

# 合并两个长表得到最终结果
final_df <- bind_rows(df1_long, df2_long)

如果单个数据框内有多个测量变量，可使用pivot_longer通用写法适配更多场景：

df1_long <- df1 %>%
  pivot_longer(cols = weight, names_to = "var", values_to = "sum") %>%
  select(treatment, var, sum, sd)

df2_long <- df2 %>%
  rename(treatment = treatment2, sd = sd2) %>%
  pivot_longer(cols = area, names_to = "var", values_to = "sum") %>%
  select(treatment, var, sum, sd)

final_df <- bind_rows(df1_long, df2_long)

方案2：base R实现（无需额外依赖） #

无需安装任何第三方包，直接用R原生函数实现：

# 处理df1为目标结构
df1_long <- data.frame(
  treatment = df1$treatment,
  var = "weight",
  sum = df1$weight,
  sd = df1$sd
)

# 处理df2为目标结构
df2_long <- data.frame(
  treatment = df2$treatment2,
  var = "area",
  sum = df2$area,
  sd = df2$sd2
)

# 合并两个数据框
final_df <- rbind(df1_long, df2_long)

最终结果示例 #

两种方案输出的结果完全一致，符合要求的结构：

内容的提问来源于stack exchange，提问作者GIS_newbie