r - 基于每组行数的子集数据帧

Question

我有这样的数据，其中一些“名称”出现了三遍以上:

df <- data.frame(name = c("a", "a", "a", "b", "b", "c", "c", "c", "c"), x = 1:9)

  name x
1    a 1
2    a 2
3    a 3
4    b 4
5    b 5
6    c 6
7    c 7
8    c 8
9    c 9

我希望根据 name变量每个级别中的行数(观察值)对数据进行子集(过滤)。如果某个 name级别出现了3次以上，那么我想删除属于该级别的所有行。因此，在此示例中，由于该组中有 name == c行，因此我们将观察值放在 > 3处:

  name x
1    a 1
2    a 2
3    a 3
4    b 4
5    b 5

我写了这段代码，但无法正常工作。

as.data.frame(table(unique(df)$name))
subset(df, name > 3)

Answer 1

首先，两个base替代方案。一个依赖table，另一个依赖ave和length。然后，两种data.table方式。

1. table

tt <- table(df$name)

df2 <- subset(df, name %in% names(tt[tt < 3]))
# or
df2 <- df[df$name %in% names(tt[tt < 3]), ]

如果要逐步进行操作:

# count each 'name', assign result to an object 'tt'
tt <- table(df$name)

# which 'name' in 'tt' occur more than three times?
# Result is a logical vector that can be used to subset the table 'tt'
tt < 3

# from the table, select 'name' that occur < 3 times
tt[tt < 3]

# ...their names
names(tt[tt < 3])

# rows of 'name' in the data frame that matches "the < 3 names"
# the result is a logical vector that can be used to subset the data frame 'df'
df$name %in% names(tt[tt < 3])

# subset data frame by a logical vector
# 'TRUE' rows are kept, 'FALSE' rows are removed.
# assign the result to a data frame with a new name
df2 <- subset(df, name %in% names(tt[tt < 3]))
# or
df2 <- df[df$name %in% names(tt[tt < 3]), ]

2. ave和 length
如@flodel所建议:

df[ave(df$x, df$name, FUN = length) < 3, ]

3. data.table: .N和 .SD:

library(data.table)
setDT(df)[, if (.N < 3) .SD, by = name]

4. data.table: .N和 .I:

setDT(df)
df[df[, .I[.N < 3], name]$V1] 

另请参阅相关的Q＆A Count number of observations/rows per group and add result to data frame。