如何批量合并变量名形如output1至output100的多个data frame？

Hey there! Merging 100 data frames by typing each name manually is such a tedious task—let’s cut that work down to a few lines of code with these practical R solutions:

This is my go-to method for this kind of job. mget() grabs all the objects whose names match your pattern and stores them in a list, then do.call() applies rbind() to every element of that list in one go:

# 生成数据框名称的字符向量
df_names <- paste0("output", 1:100)

# 获取所有数据框并合并
combined_df <- do.call(rbind, mget(df_names))

If you prefer a more explicit approach, a simple loop works too. Start with your first data frame, then iterate through the rest and bind them one by one:

# 用第一个数据框初始化合并结果
combined_df <- output1

# 从output2循环到output100
for (i in 2:100) {
  # 通过名称获取当前数据框
  current_df <- get(paste0("output", i))
  # 合并到总数据框中
  combined_df <- rbind(combined_df, current_df)
}

If you’re using the tidyverse, bind_rows() is even cleaner. It handles cases where data frames have slightly different columns (filling missing ones with NA) more gracefully than base R’s rbind:

library(dplyr)

# 生成名称并一步完成合并
df_names <- paste0("output", 1:100)
combined_df <- bind_rows(mget(df_names))

小提示： #

• 确保所有数据框的列名和数据类型匹配。如果不匹配，rbind()会报错（或强制转换类型），而bind_rows()会自动为缺失列填充NA。
• 如果你的环境中还有其他名为outputXX的非数据框对象，可以调整paste0的生成规则，或者对mget()返回的列表进行过滤，只保留数据框类型。

All these methods will save you the headache of typing 100 variable names. Pick the one that fits your workflow best!

内容的提问来源于stack exchange，提问作者Sonal Bajoriya