R中多个data.frame的变量的平均值？

Question

我有以下 data.frame，我想创建另一个 data.frame（比如 M），它将存储 M1,M2,M3 中的 A1 的 mean , mean of B1, 来自 M1,M2,M3 并且同样适用于 C1.

library(tidyverse)


set.seed(123)

M1 <- data.frame(Date = seq(as.Date("2001-01-01"), to = as.Date("2005-12-31"), by = "month"),
           A1 = runif(60,1,5),
           B1 = runif(60,1,5),
           C1 = runif(60,1,5))

M2 <- data.frame(Date = seq(as.Date("2001-01-01"), to = as.Date("2005-12-31"), by = "month"),
                 A1 = runif(60,1,5),
                 B1 = runif(60,1,5),
                 C1 = runif(60,1,5))

M3 <- data.frame(Date = seq(as.Date("2001-01-01"), to = as.Date("2005-12-31"), by = "month"),
                 A1 = runif(60,1,5),
                 B1 = runif(60,1,5),
                 C1 = runif(60,1,5))

期望输出

输出将是 data.frame (M)，变量为 A (mean of A1 from M1,M2,M3)、B (mean of B1 from M1,M2,M3) 和 C (mean of C1 from M1,M2,M3)。

Answer 1

我们在 list (mget) 中获取数据集，对感兴趣的列进行子集化，获取元素总和 (+) 并除以 3（因为只有3 个数据集）

M <- Reduce(`+`, lapply(mget(ls(pattern = "^M\d+")), `[`, 
     -1))/3
names(M) <- sub("\d+", "", names(M))

-输出

> head(M)
         A        B        C
1 2.694883 3.345868 3.196847
2 2.724759 2.868531 2.524246
3 3.685341 2.535909 2.859400
4 2.941540 2.639169 3.182535
5 3.530815 3.690165 3.576402
6 2.747724 3.399104 3.107880

或者另一种选择是将数据集绑定在一起，然后按 mean

进行分组

library(dplyr)
library(stringr)
bind_rows(M1, M2, M3) %>%
   group_by(Date) %>%
   summarise(across(everything(), mean, na.rm = TRUE, 
      .names = "{str_remove(.col, '[0-9]+')}"))
# A tibble: 60 × 4
   Date           A     B     C
   <date>     <dbl> <dbl> <dbl>
 1 2001-01-01  2.69  3.35  3.20
 2 2001-02-01  2.72  2.87  2.52
 3 2001-03-01  3.69  2.54  2.86
 4 2001-04-01  2.94  2.64  3.18
 5 2001-05-01  3.53  3.69  3.58
 6 2001-06-01  2.75  3.40  3.11
 7 2001-07-01  2.32  3.02  1.58
 8 2001-08-01  2.97  3.89  2.04
 9 2001-09-01  3.49  3.56  2.36
10 2001-10-01  3.46  3.71  3.69
# … with 50 more rows

R中多个data.frame的变量的平均值？

Mean of a variable from multiple data.frame in R?

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tidyverse