使用在 dplyr 中返回多个输出的函数将多列添加到 data.frame

Question

我正在计算连续变量的不同分位数的中位数和值。我想一步添加所有列。这有可能做到这一点。以下是一个可重现的示例。

df <- data.frame(group = rep(c('group1','group2'),50),
             x = rnorm(100), 
             y = rnorm(100))
df %>% 
gather('variable','value', -group) %>% 
group_by(group, variable) %>% 
summarise(median = round(quantile(value,0.5, na.rm = T),2),
          iqr25 = round(quantile(value,0.25, na.rm = T),2),
          iqr75 = round(quantile(value,0.75, na.rm = T),2))

输出

# A tibble: 4 x 5
# Groups:   group [2]
  group  variable median iqr25 iqr75
  <fct>  <chr>     <dbl> <dbl> <dbl>
1 group1 x          0.06 -0.74  1.04
2 group1 y         -0.36 -1.03  0.45
3 group2 x         -0.04 -0.85  0.62
4 group2 y          0.06 -0.56  0.89

这个总结步骤可以不写分位数函数3次就完成吗？

我做了一个解决方法。但是有没有一个很好的方法来做到这一点。

df %>% 
gather('variable','value', -group) %>% 
group_by(group, variable) %>% 
summarise(s = toString(round(quantile(value, c(0.25,0.5,0.75),na.rm = T),2))) %>% 
separate(s, into = c('q25','median','q75'), sep = ',')

Answer 1

你可以nestgroup_by之后的数据，然后map到quantile

df %>% 
  gather('variable','value', -group) %>% 
  group_by(group, variable) %>% 
  nest() %>% 
  mutate(quant = map(data, ~quantile(.$value, probs = c(0.25, 0.5, 0.75))),
         quant = map(quant, t),
         quant = map(quant, as.data.frame),
         quant = map(quant, setNames, c("iqr25", "median", "iqr75")),

         ) %>% 
  unnest(quant) %>% 
  select(-data)

# A tibble: 4 x 5
  group  variable  iqr25  median iqr75
  <fct>  <chr>     <dbl>   <dbl> <dbl>
1 group1 x        -0.876 -0.173  0.471
2 group2 x        -0.372  0.0507 0.519
3 group1 y        -0.785 -0.109  0.618
4 group2 y        -0.944 -0.117  0.647

Answer 2

使用nest的另一种方法：

df %>%
  gather('variable', 'value', -group) %>%
  group_by(group, variable) %>%
  nest() %>%
  mutate(quants = map(data, function(x) 
    quantile(x$value, c(0.25,0.5,0.75)))) %>%
  unnest(quants) %>%
  group_by(group, variable) %>%
  mutate(case = c("iqr25", "median" , "iqr75")) %>%
  spread(case, quants) %>% 
  mutate_if(is.numeric, round, 2)

# A tibble: 4 x 5
# Groups:   group, variable [4]
  group  variable iqr25 iqr75 median
  <fct>  <chr>    <dbl> <dbl>  <dbl>
1 group1 x        -0.5   0.7    0.09
2 group1 y        -0.54  0.7    0.1 
3 group2 x        -0.59  0.61  -0.06
4 group2 y        -0.89  0.35  -0.11