计算组均值(或其他汇总统计信息)并分配给原始数据 [英] Calculate group mean (or other summary stats) and assign to original data

问题描述

我想计算每个级别内的数字变量(值")的mean(或长度为1的任何其他摘要统计信息，例如min，max，length，sum).分组变量(组").

I want to calculate mean (or any other summary statistics of length one, e.g. min, max, length, sum) of a numeric variable ("value") within each level of a grouping variable ("group").

应将摘要统计信息分配给一个新的变量，该变量的长度应与原始数据的长度相同.也就是说，原始数据的每一行应具有与当前组值相对应的值-数据集应 not 折叠为每组一行.例如，考虑组mean:

The summary statistic should be assigned to a new variable which has the same length as the original data. That is, each row of the original data should have a value corresponding to the current group value - the data set should not be collapsed to one row per group. For example, consider group mean:

之前

id  group  value
1   a      10
2   a      20
3   b      100
4   b      200

之后

id  group  value  grp.mean.values
1   a      10     15
2   a      20     15
3   b      100    150
4   b      200    150

推荐答案

您可以在dplyr中使用mutate进行此操作:

You may do this in dplyr using mutate:

library(dplyr)
df %>%
  group_by(group) %>%
  mutate(grp.mean.values = mean(value))

...或使用data.table通过引用(:=)分配新列:

...or use data.table to assign the new column by reference (:=):

library(data.table)
setDT(df)[ , grp.mean.values := mean(value), by = group]

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