将两个列名不同的 dfs 组合起来，然后融化 [英] Combine two dfs with different column names and then melt

问题描述

我想合并两个数据框，但根据以下内容将它们融合到不同的列中:

I want to combine two data frames but melt them into different columns based on below:

treatment<-c('control','noise')
weight<-c(0.01872556,0.01575400)
sd<-c(0.008540041,0.007460524)

df1<-data.frame(treatment,weight,sd)

treatment2<-c('control','noise')
area<-c(0.79809444,0.68014667)
sd2<-c(0.337949414,0.294295847)

df2<-data.frame(treatment2,area,sd2)

我想组合它们并创建一个看起来像这样的数据框:

And I wanted to combine them and create a data frame which should look like this:

<头>

治疗	变量	总和	sd
控制	区域	0.79809444	0.337949414
噪音	区域	0.68014667	0.294295847
控制	重量	0.01872556	0.008540041
噪音	重量	0.01575400	0.01575400

我尝试了各种方法，搜索了各种方法，最终将每个数据框导出到 csv 中，然后将它们组合到 excel 中，重新导入到 R 中进行分析.

I tried this various ways, googled various ways and ended up exporting each data frame into a csv then combining them in excel, re-importing into R for analysis.

有更简单的解决方案吗?

Is there a simpler solution?

推荐答案

你可以使用

library(tidyr)
library(dplyr)

df2 %>% 
  rename(sd = sd2, treatment = treatment2) %>% 
  pivot_longer(area, names_to = "var", values_to = "sum") %>% 
  bind_rows(pivot_longer(df1, weight, names_to = "var", values_to = "sum")) %>% 
  select(treatment, var, sum, sd)

得到

# A tibble: 4 x 4
  treatment var       sum      sd
  <chr>     <chr>   <dbl>   <dbl>
1 control   area   0.798  0.338  
2 noise     area   0.680  0.294  
3 control   weight 0.0187 0.00854
4 noise     weight 0.0158 0.00746

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