英文:
How to subset duplicates on the earliest date among a group?
问题
我有一个包含多个个体（`id`）的`data.frame`。之前已经删除了重复的行。
```R
df <- data.frame(id=as.integer(c(123,123,123,124,124,124,125,125,125,126,126,126)),
date=as.Date(c("2014-03-12", "2014-03-12", "2015-09-16",
"2015-10-24", "2016-12-11", "2016-12-11",
"2017-08-06", "2017-11-26", "2018-01-29",
"2015-09-16", "2015-09-16", "2015-09-16")),
fruit=as.character(c("Apple", "Orange", "Passion fruit", "Banana",
"Lemon", "Strawberry", "Banana", "Apple",
"Passion fruit", "Orange", "Bluberry", "Pineapple")),
row=rep(c(1, 2, 3)))
我需要选择每个个体中包含重复的最早日期，也就是说，如果最早日期发生多次，我需要保留所有出现的情况。
期望的输出：
df
id date fruit row
1 123 2014-03-12 Apple 1
2 123 2014-03-12 Orange 2
10 126 2015-09-16 Orange 1
11 126 2015-09-16 Blueberry 2
12 126 2015-09-16 Pineapple 3
英文:
I have a data.frame with multiple events by individual (id). Duplicated rows have been previously removed.
df <- data.frame(id=as.integer(c(123,123,123,124,124,124,125,125,125,126,126,126)),
date=as.Date(c("2014-03-12", "2014-03-12", "2015-09-16",
"2015-10-24", "2016-12-11", "2016-12-11",
"2017-08-06", "2017-11-26", "2018-01-29",
"2015-09-16", "2015-09-16", "2015-09-16")),
fruit=as.character(c("Apple", "Orange", "Passion fruit", "Banana",
"Lemon", "Strawberry", "Banana", "Apple",
"Passion fruit", "Orange", "Bluberry", "Pineapple")),
row=rep(c(1, 2, 3)))
id date fruit row
1 123 2014-03-12 Apple 1
2 123 2014-03-12 Orange 2
3 123 2015-09-16 Passion fruit 3
4 124 2015-10-24 Banana 1
5 124 2016-12-11 Lemon 2
6 124 2016-12-11 Strawberry 3
7 125 2017-08-06 Banana 1
8 125 2017-11-26 Apple 2
9 125 2018-01-29 Passion fruit 3
10 126 2015-09-16 Orange 1
11 126 2015-09-16 Blueberry 2
12 126 2015-09-16 Pineapple 3
I need to select only the earliest date per individual that contains a duplicate, that is, if the earliest date happens more than once, I need to keep all occurrences.
Desired Output:
df
id date fruit row
1 123 2014-03-12 Apple 1
2 123 2014-03-12 Orange 2
3 126 2015-09-16 Orange 1
4 126 2015-09-16 Blueberry 2
5 126 2015-09-16 Pineapple 3
答案1
得分: 2
我们可以按'id'分组，使用min创建条件，然后使用duplicated来检查重复项。
library(dplyr)
df %>%
filter(date == min(date) & (duplicated(date) |
duplicated(date, fromLast = TRUE)), .by = id)
输出：
id date fruit row
1 123 2014-03-12 Apple 1
2 123 2014-03-12 Orange 2
3 126 2015-09-16 Orange 1
4 126 2015-09-16 Blueberry 2
5 126 2015-09-16 Pineapple 3
英文:
We could group by 'id', create a condition with min and use duplicated to check for duplicates
library(dplyr)
df %>%
filter(date == min(date) & (duplicated(date)|
duplicated(date, fromLast = TRUE)), .by = id)
-output
id date fruit row
1 123 2014-03-12 Apple 1
2 123 2014-03-12 Orange 2
3 126 2015-09-16 Orange 1
4 126 2015-09-16 Bluberry 2
5 126 2015-09-16 Pineapple 3
答案2
得分: 2
这里是使用dplyr的另一种尝试：
library(dplyr) # 版本 >= 1.1.0
df %>%
slice_min(date, by = id) %>%
filter(n() >= 2, .by = c(id, date))
#> id date fruit row
#> 1 123 2014-03-12 Apple 1
#> 2 123 2014-03-12 Orange 2
#> 3 126 2015-09-16 Orange 1
#> 4 126 2015-09-16 Bluberry 2
#> 5 126 2015-09-16 Pineapple 3
创建于2023-05-25，使用 reprex v2.0.2
英文:
Here's another attempt using dplyr:
library(dplyr) # version >= 1.1.0
df %>%
slice_min(date, by = id) %>%
filter(n() >= 2, .by = c(id, date))
#> id date fruit row
#> 1 123 2014-03-12 Apple 1
#> 2 123 2014-03-12 Orange 2
#> 3 126 2015-09-16 Orange 1
#> 4 126 2015-09-16 Bluberry 2
#> 5 126 2015-09-16 Pineapple 3
<sup>Created on 2023-05-25 with reprex v2.0.2</sup>
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