计算每组的行数并将结果添加到原始数据框中 [英] Count number of rows per group and add result to original data frame

问题描述

假设我有一个 data.frame 对象:

Say I have a data.frame object:

df <- data.frame(name=c('black','black','black','red','red'),
                 type=c('chair','chair','sofa','sofa','plate'),
                 num=c(4,5,12,4,3))

现在我想计算 name 和 type 的每个组合的行数(观察值).可以这样做:

Now I want to count the number of rows (observations) of for each combination of name and type. This can be done like so:

table(df[ , c("name","type")])

或者也可能使用 plyr，(虽然我不确定如何).

or possibly also with plyr, (though I am not sure how).

但是，如何将结果合并到原始数据框中?使结果看起来像这样:

However, how do I get the results incorporated into the original data frame? So that the results will look like this:

df
#    name  type num count
# 1 black chair   4     2
# 2 black chair   5     2
# 3 black  sofa  12     1
# 4   red  sofa   4     1
# 5   red plate   3     1

count 现在存储聚合结果的位置.

where count now stores the results from the aggregation.

使用 plyr 的解决方案也可能很有趣，但我想看看这是如何使用基础 R 完成的.

A solution with plyr could be interesting to learn as well, though I would like to see how this is done with base R.

推荐答案

使用data.table:

library(data.table)
dt = as.data.table(df)

# or coerce to data.table by reference:
# setDT(df)

dt[ , count := .N, by = .(name, type)]

对于 data.table 1.8.2 之前的替代方案，请参阅编辑历史记录.

For pre-data.table 1.8.2 alternative, see edit history.

使用dplyr:

library(dplyr)
df %>%
  group_by(name, type) %>%
  mutate(count = n())

或者简单地说:

add_count(df, name, type)

<小时>

使用plyr:

plyr::ddply(df, .(name, type), transform, count = length(num))

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