如何过滤匹配多个值的组?
how to filter groups matching more than one values?
id drug_name med_start med_end
<dbl> <chr> <date> <date>
1 pembrolizumab 2018-02-07 2018-02-07
1 pembrolizumab 2018-02-28 2018-02-28
2 pembrolizumab 2018-01-05 2018-01-05
2 nivolumab 2018-09-20 2018-09-20
2 nivolumab 2018-10-03 2018-10-03
2 nivolumab 2018-11-01 2018-11-01
我正在尝试获取在 drug_name
中同时具有 pembrolizumab
和 nivolumab
的 ID。我可以在 id
上做 group_by
吗?然后用这两个条件过滤?
对于上面的 table,id 2 有两个 drug_names
。我可能会遇到过滤超过 2 drug_names
.
的情况
我也在尝试查看两个 med_start
之间的间隔是否大于 x 天。比方说30天。基本上过滤在 med_start
.
之间间隔 30 天的 ID
以上数据的代码如下
data <- structure(list(id = structure(c(1, 1, 2, 2, 2, 2), class = "int"),
drug_name = c("pembrolizumab", "pembrolizumab", "pembrolizumab",
"nivolumab", "nivolumab", "nivolumab"), med_start = structure(c(17569,
17590, 17536, 17794, 17807, 17836), class = "Date"), med_end = structure(c(17569,
17590, 17536, 17794, 17807, 17836), class = "Date")), row.names = c(NA,
-6L), groups = structure(list(patient_id = structure(c(1.49283861796358e-314,
1.6423825257779e-313), class = "integer64"), .rows = structure(list(
1:2, 3:6), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
我们按 'id' 和 filter
分组,其中 all
感兴趣的药物是 %in%
'drug_name' 列,并提取 unique
'id'
library(dplyr)
data %>%
group_by(id) %>%
filter(all(c("pembrolizumab", "nivolumab") %in% drug_name)) %>%
ungroup %>%
pull(id)%>%
unique
-输出
[1] 2
这里有一些基本的 R 选项
- 第一个问题
> unique(
+ subset(
+ data,
+ ave(match(drug_name, c("pembrolizumab", "nivolumab")), id, FUN = var) > 0,
+ select = id
+ )
+ )
# A tibble: 1 x 1
id
<int>
1 2
- 第二题
> subset(
+ data,
+ ave(as.integer(med_start), id, FUN = function(x) max(diff(x))) <= 30
+ )
# A tibble: 2 x 4
id drug_name med_start med_end
<int> <chr> <date> <date>
1 1 pembrolizumab 2018-02-07 2018-02-07
2 1 pembrolizumab 2018-02-28 2018-02-28
id drug_name med_start med_end
<dbl> <chr> <date> <date>
1 pembrolizumab 2018-02-07 2018-02-07
1 pembrolizumab 2018-02-28 2018-02-28
2 pembrolizumab 2018-01-05 2018-01-05
2 nivolumab 2018-09-20 2018-09-20
2 nivolumab 2018-10-03 2018-10-03
2 nivolumab 2018-11-01 2018-11-01
我正在尝试获取在
的情况drug_name
中同时具有pembrolizumab
和nivolumab
的 ID。我可以在id
上做group_by
吗?然后用这两个条件过滤? 对于上面的 table,id 2 有两个drug_names
。我可能会遇到过滤超过 2drug_names
.我也在尝试查看两个
之间间隔 30 天的 IDmed_start
之间的间隔是否大于 x 天。比方说30天。基本上过滤在med_start
.
以上数据的代码如下
data <- structure(list(id = structure(c(1, 1, 2, 2, 2, 2), class = "int"),
drug_name = c("pembrolizumab", "pembrolizumab", "pembrolizumab",
"nivolumab", "nivolumab", "nivolumab"), med_start = structure(c(17569,
17590, 17536, 17794, 17807, 17836), class = "Date"), med_end = structure(c(17569,
17590, 17536, 17794, 17807, 17836), class = "Date")), row.names = c(NA,
-6L), groups = structure(list(patient_id = structure(c(1.49283861796358e-314,
1.6423825257779e-313), class = "integer64"), .rows = structure(list(
1:2, 3:6), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
我们按 'id' 和 filter
分组,其中 all
感兴趣的药物是 %in%
'drug_name' 列,并提取 unique
'id'
library(dplyr)
data %>%
group_by(id) %>%
filter(all(c("pembrolizumab", "nivolumab") %in% drug_name)) %>%
ungroup %>%
pull(id)%>%
unique
-输出
[1] 2
这里有一些基本的 R 选项
- 第一个问题
> unique(
+ subset(
+ data,
+ ave(match(drug_name, c("pembrolizumab", "nivolumab")), id, FUN = var) > 0,
+ select = id
+ )
+ )
# A tibble: 1 x 1
id
<int>
1 2
- 第二题
> subset(
+ data,
+ ave(as.integer(med_start), id, FUN = function(x) max(diff(x))) <= 30
+ )
# A tibble: 2 x 4
id drug_name med_start med_end
<int> <chr> <date> <date>
1 1 pembrolizumab 2018-02-07 2018-02-07
2 1 pembrolizumab 2018-02-28 2018-02-28