R 如何分别使用每列的总和、平均值和计数来聚合数据？

我有一个名为“order_product”的数据集，如下所示：

order_id   product  order_sequence  reorder
    1        egg          1            1
    1        meat         2            0
    1        fruit        3            1
    1        meat         4            1
    2        egg          1            1
    2        egg          2            1
    2        fruit        3            0
    3        egg          1            0
    3        fruit        2            1
    3        fruit        3            1

product  frequency reorder_rate  mean_sequence
  egg        4          3/4           5/4
  meat       2          1/2            3
 fruit       4          3/4           11/4

我将把数据聚合到一个新的数据框中，称为“产品”，它是按产品分组的。新聚合数据集的变量显示每个产品的总频率、再订购率和平均序列。每个变量的计算如下所示：

frequency: product count
reorder_rate: sum of reorder/frequency 
mean_sequence: sum or order_sequence/frequency

所以结果应该是这样的：

order_id   product  order_sequence  reorder
    1        egg          1            1
    1        meat         2            0
    1        fruit        3            1
    1        meat         4            1
    2        egg          1            1
    2        egg          2            1
    2        fruit        3            0
    3        egg          1            0
    3        fruit        2            1
    3        fruit        3            1

product  frequency reorder_rate  mean_sequence
  egg        4          3/4           5/4
  meat       2          1/2            3
 fruit       4          3/4           11/4

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有人能帮我做这个吗？我在package data.table中尝试了melt（）函数，但不知道如何编写它

这种计算很容易使用

dplyr

library(dplyr)

df %>%
  group_by(product) %>%
  summarise(frequency = n(), 
            reorder_rate = sum(reorder)/frequency, 
            mean_sequence = sum(order_sequence)/frequency)

# A tibble: 3 x 4
#  product frequency reorder_rate mean_sequence
#  <fct>       <int>        <dbl>         <dbl>
#1 egg             4         0.75          1.25
#2 fruit           4         0.75          2.75
#3 meat            2         0.5           3