在 r 中总结两个数据帧

Question

我有两个数据框

df1
#    var1 var2
# 1 X01    Red
# 2 X02    Green
# 3 X03    Red
# 4 X04    Yellow
# 5 X05    Red
# 6 X06    Green

df2
#   X01    X02    X03   ...
# 1 1      0.1    2.1
# 2 2      0.2    2.2
# 3 3      0.3    2.3
# 4 4      0.4    2.4
# 5 5      0.5    2.5
# 6 6      0.6    2.6

我想得到这样的东西

            
mean green  val1
mean red    val2
mean yellow val3

当用相应的变量计算平均值时。

Answer 1

我们可以更改 'df2' 中的列名与 'df1' 中的键值对的匹配，以替换颜色值，rep通过 colum 索引, unlist 'df2' 并使用分组方法得到 mean

tapply(unlist(df2), setNames(df1$var2, df1$var1)[names(df2)][col(df2)], 
    FUN = mean, na.rm = TRUE)

或使用 tidyverse，重塑为 'long' 并在执行 group_by mean

之前进行连接

library(dplyr)
library(tidyr)
df2 %>% 
 pivot_longer(cols = everything(), names_to = 'var1') %>% 
 left_join(df1) %>% 
 group_by(var2) %>% 
 summarise(value = mean(value, na.rm = TRUE), .groups = 'drop')

数据

df1 <- structure(list(var1 = c("X01", "X02", "X03", "X04", "X05", "X06"
), var2 = c("Red", "Green", "Red", "Yellow", "Red", "Green")),
   class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6"))

df2 <- structure(list(X01 = 1:6, X02 = c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6
), X03 = c(2.1, 2.2, 2.3, 2.4, 2.5, 2.6)), 
  class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6"))

在 r 中总结两个数据帧

Summarize two dataframes in r

r

crosstab

dataframe

数据