计算组平均值、总和或其他汇总统计数据.并将列分配给原始数据 [英] Calculate group mean, sum, or other summary stats. and assign column to original data

问题描述

我想计算 mean(或任何其他长度为 1 的汇总统计数据，例如 min、max、length, sum) 在分组变量(group")的每个级别内的数值变量(value").

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").

汇总统计量应分配给与原始数据具有相同长度的新变量.也就是说，原始数据的每一行都应该有一个对应于当前组值的值——数据集不应该被折叠成每组一行.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 执行此操作:

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]

这篇关于计算组平均值、总和或其他汇总统计数据.并将列分配给原始数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！