Question

我正在寻找一种简单的方法来轮播dplyr tibble摘要。

说我正在做这样的事情，

# install.packages(c("dplyr"), dependencies = TRUE)
library(dplyr) 

mtcars %>% 
    group_by(am)  %>%
    summarise(
        n = n(),
        Mean_disp = mean(disp),
        Mean_hp = mean(hp),
        Mean_qsec = mean(qsec),
        Mean_drat = mean(drat)
             )
#>     # A tibble: 2 x 6
#>      am     n Mean_disp  Mean_hp Mean_qsec Mean_drat
#>   <dbl> <int>     <dbl>    <dbl>     <dbl>     <dbl>
#> 1     0    19  290.3789 160.2632  18.18316  3.286316
#> 2     1    13  143.5308 126.8462  17.36000  4.050000

但是，我想要的是获得或多或少的输出，

#> # A tibble: 5 x 2
#>    am <dbl>             0           1
#>   n <int>              19          13
#>   Mean_disp <dbl>     290.3789    143.5308
#>   Mean_hp <dbl>       160.2631    126.8462
#>   Mean_qsec <dbl>      18.183158   17.36000
#>   Mean_drat <dbl>       3.286316    4.050000

我意识到我可以使用t()，但是将tibble转换为列表并弄乱格式化。

Answer 1

也许收集然后传播：

library(dplyr) 
library(tidyr)

mtcars %>% 
  group_by(am)  %>%
  summarise(
    n = n(),
    Mean_disp = mean(disp),
    Mean_hp = mean(hp),
    Mean_qsec = mean(qsec),
    Mean_drat = mean(drat)) %>%
  gather(key = key, value = value, -am) %>% 
  spread(key = am, value = value)


# # A tibble: 5 x 3
#         key        `0`      `1`
# *     <chr>      <dbl>    <dbl>
# 1 Mean_disp 290.378947 143.5308
# 2 Mean_drat   3.286316   4.0500
# 3   Mean_hp 160.263158 126.8462
# 4 Mean_qsec  18.183158  17.3600
# 5         n  19.000000  13.0000

另一个选项在 group_by 之前收集，然后获取所有选定列的均值，然后再次传播（但不知道如何添加{ {1}}）：

n()

Answer 2

  new_tibble <- as.data.frame(t(mt_cars_df)) %>% 
  as_tibble()

  new_tibble$name <- names(mt_cars_df) %>%
    select(name, V1, V2)

根据this，row.names在tibbles中被弃用，因此将它们添加为键列将是处理该情况的逻辑方式。这留下了需要重新排序列的元素。

旋转dplyr的tibble摘要

2 个答案: