迭代 dplyR 中的字符向量 summarize 并使用它来分配新的列名

Question

我有一个带有变量名称的字符向量：

variables -> c("w", "x", "y", "z")

我需要创建一个函数来计算指定参数（如下所示的 alpha）的每个变量的平均值。但是，它不会使用迭代变量名称重命名列，也不会将 alpha 列减少到左侧的一列。

calc <- function(df,
                 parameter,
                 iteration,
                 variables){
      variable <- sym(variables[iteration])
      mean <- df %>% group_by(.dots = parameter) %>% 
              summarise(variable = mean(!!variable),sd_variable = sd(!!variable))
      return(mean)
    }
    
means <- map_dfc(1:length(variables), ~calc(df = input,
                                           parameter = "alpha",
                                           iteration = .,
                                           variables = variables))

理想情况下，输出 df (means) 应如下所示：

alpha | w | sd_w | x | sd_x | y | sd_y | z | sd_z |

这是输入 df 的样子：

    structure(list(time = c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 999.5, 999.6, 
999.7, 999.8, 999.9, 1000), w = c(10, 10.0057192322758, 10.0198266325956, 
10.040096099625, 10.0637654242843, 10.087779652849, 0.889708853982268, 
0.890916575744663, 0.892121389863897, 0.89332329218135, 0.894522278550115, 
0.895718344834999), x = c(10, 11.0467963604334, 12.1782709261765, 
13.3728962503142, 14.6035317074526, 15.8398164069251, 62.6631746231113, 
62.6583134156356, 62.6534565303638, 62.648604016965, 62.6437559251575, 
62.6389123047088), y = c(10, 9.89605687874935, 9.59253574727296, 
9.11222320249057, 8.48917353431654, 7.76447036695841, 0.00833796964522317, 
0.00835876233547079, 0.00837957883570158, 0.00840041916631544, 
0.00842128334742553, 0.00844217139885453), z = c(10, 9.05439359565339, 
8.21533762023494, 7.48379901688836, 6.85562632179817, 6.3231517466183, 
-7.50539460838544, -7.48234149534558, -7.45927733670319, -7.43620225192078, 
-7.41311636057114, -7.39001978233681), alpha = c(0.1, 0.1, 0.1, 
0.1, 0.1, 0.1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5), beta = c(0.1, 0.1, 
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1), eta = c(0.1, 
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1), zeta = c(0.1, 
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1), lambda = c(0.95, 
0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95
), phi = c(5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5), kappa = c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ode_outputs..iteration.. = c(NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c("1", 
"1.1", "1.2", "1.3", "1.4", "1.5", "3.9995", "3.9996", "3.9997", 
"3.9998", "3.9999", "3.10000"), class = "data.frame")

理想情况下，该函数将使用 dplyr and/or baseR。

Answer 1

如果我的理解正确，则无需遍历列。都可以直接在dplyr...

中完成

library(tidyverse)

df %>% 
  group_by(alpha) %>% 
  summarise(
    across(
      c(w, x, y, z), 
      list(mean=mean, sd=sd)
    ), 
    .groups="drop"
  ) %>% 
  rename_with(function(x) str_sub(x,1,1), ends_with("mean"))
# A tibble: 2 x 9
  alpha      w    w_sd     x    x_sd       y      y_sd     z   z_sd
  <dbl>  <dbl>   <dbl> <dbl>   <dbl>   <dbl>     <dbl> <dbl>  <dbl>
1   0.1 10.0   0.0345   12.8 2.20    9.14    0.875      7.99 1.38  
2   0.5  0.893 0.00225  62.7 0.00908 0.00839 0.0000390 -7.45 0.0432

迭代 dplyR 中的字符向量 summarize 并使用它来分配新的列名

Iterate over character vector in dplyR summarise and use it to assign new column names

r

dplyr

purrr