我有兩個資料框
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
我想得到這樣的東西
mean green val1
mean red val2
mean yellow val3
當使用相應的變數計算平均值時。
uj5u.com熱心網友回復：
我們可以將'df2'中的列名與'df1'中的keyval對更改為顏色值，rep通過colum索引，unlist'df2'來替換，并使用分組方法來獲取mean
tapply(unlist(df2), setNames(df1$var2, df1$var1)[names(df2)][col(df2)],
FUN = mean, na.rm = TRUE)
或者使用tidyverse, reshape to 'long' 并在做之前加入group_by mean
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')
資料
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"))
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