我正试图从数据帧中删除这些因素,但只删除特定日期之后的因素。这里我做了一个玩具示例:
我有一个test
数据帧和一个检查数据帧inspec
。我想删除var1
中出现在inspec
中的字母,但只删除inspec
中日期之后的行。例如,考虑
> test = data.frame(var1 = c("A", "B", "A", "B", "C","B", "A"), measure = c(6,7,8,6,10,1,0), date = as.Date(c("2021-01-02", "2021-01-03", "2021-01-04", "2021-01-05", "2021-01-06", "2021-01-07", "2021-01-12")))
> test
var1 measure date
1 A 6 2021-01-02
2 B 7 2021-01-03
3 A 8 2021-01-04
4 B 6 2021-01-05
5 C 10 2021-01-06
6 B 1 2021-01-07
7 A 0 2021-01-12
>
> inspec = data.frame(var1 = c("A", "C", "D", "A"), date = as.Date(c("2021-01-03", "2021-01-06", "2021-01-10", "2021-01-12")))
> inspec
var1 date
1 A 2021-01-03
2 C 2021-01-06
3 D 2021-01-10
4 A 2021-01-12
然后,作为结果,我想获得:
> test
var1 measure date
1 A 6 2021-01-02
2 B 7 2021-01-03
3 B 6 2021-01-05
4 B 1 2021-01-07
注意,仅排除了在inspec
数据帧中指示的日期之后检查的var1
中的A
。如果我不想在inspec
日期之前维护var1
,我可以使用test= test[!(test$var1 %in% inspec$var1),]
有什么提示我该怎么做吗?
基R
## reduce `inspec` to the earliest date
inspec$date <- as.Date(inspec$date)
tmpinspec <- inspec[ave(as.integer(inspec$date), inspec$var1, FUN = function(z) z == min(z)) > 0,]
tmpinspec
# var1 date
# 1 A 2021-01-03
# 2 C 2021-01-06
# 3 D 2021-01-10
tmp <- merge(test, tmpinspec, by = "var1", all.x = TRUE, suffixes = c("", ".y"))
tmp
# var1 measure date date.y
# 1 A 6 2021-01-02 2021-01-03
# 2 A 8 2021-01-04 2021-01-03
# 3 A 0 2021-01-12 2021-01-03
# 4 B 7 2021-01-03 <NA>
# 5 B 6 2021-01-05 <NA>
# 6 B 1 2021-01-07 <NA>
# 7 C 10 2021-01-06 2021-01-06
tmp <- tmp[with(tmp, is.na(date.y) | date < date.y),]
# tmp$date.y <- NULL
# tmp
var1 measure date
# 1 A 6 2021-01-02
# 4 B 7 2021-01-03
# 5 B 6 2021-01-05
# 6 B 1 2021-01-07
dplyr
library(dplyr)
group_by(inspec, var1) %>%
slice_min(date) %>%
left_join(test, ., by = "var1", suffix = c("", ".y")) %>%
filter(is.na(date.y) | date < date.y) %>%
select(-date.y)
# var1 measure date
# 1 A 6 2021-01-02
# 2 B 7 2021-01-03
# 3 B 6 2021-01-05
# 4 B 1 2021-01-07
我们可以在var1
上加入,并基于dates
进行过滤,而数据按var1
分组,只保持第一个匹配。见下文;
library(dplyr)
test %>%
left_join(inspec, by = "var1", suffix = c("", ".y")) %>%
group_by(var1) %>%
filter(is.na(date.y) | date < first(date.y)) %>%
select(-date.y) %>%
group_by_all() %>%
slice(1)
#> # A tibble: 4 x 3
#> # Groups: var1, measure, date [4]
#> var1 measure date
#> <fct> <dbl> <date>
#> 1 A 6 2021-01-02
#> 2 B 1 2021-01-07
#> 3 B 6 2021-01-05
#> 4 B 7 2021-01-03
这是r2evans答案的变体
使用data.table,我们还可以使用合并,然后过滤:
library(data.table)
test <- setDT(test); inspec <- setDT(inspec)
test <- merge(test, inspec, by = "var1", all.x = TRUE, suffixes = c("", ".y"))
test <- test[date < date.y | !is.na(date.y), .(var1, measure, date)]