Question

library(tidyverse)

使用底部的示例数据，我尝试删除ID列中的重复项，但只删除＆＃34; Year＆＃34;中的重复项。专栏等于2017年。

我尝试了下面的代码，但似乎没有效果。

DF <- DF %>% 
  group_by(ID) %>% 
  mutate(REMOVE = if_else(duplicated(ID) & Year == 2017, 1, 0))

DF <- DF %>% 
  group_by(ID) %>% 
  mutate(REMOVE = if_else(!unique(ID) & Year == 2017, 1, 0))

我尝试使用代码按＆＃34; ID＆＃34;进行分组，然后使用＆＃34; if_else＆＃34;在每组重复ID的代码年2017年的陈述中使用1.我将使用下面的过滤器代码删除所有1＆＃39;

DF <- DF %>%
  filter(REMOVE == 1)

我不确定为什么这段代码不起作用。我也尝试过改变ID和Year的列类型，从字符，数字等，但这没有帮助。

帮助将不胜感激！

ID<-c(18998878,8888888,57485746,18998878,45454536,64536475,64536475,87966666,58675844,58695847,68574443,87966666)
Program<-c("A111","B488","T687","A111","G888","T444","T444","P867","R444","B323","F888","P867")
Code<-c(1222,4534,543,1222,4678,6544,6544,9898,8888,5656,6666,9898)
Year<-c(2016,2016,2017,2017,2017,2017,2016,2016,2016,2017,2017,2017)
DF<-data_frame(ID,Program,Code,Year)

Answer 1

按DF和ID对Year进行排序，然后使用distinct仅保留Year = 2016个值

library(dplyr)

ID <- c(18998878,8888888,57485746,18998878,45454536,64536475,64536475,87966666,
        58675844,58695847,68574443,87966666)
Program <- c("A111","B488","T687","A111","G888","T444","T444","P867","R444","B323","F888","P867")
Code <- c(1222,4534,543,1222,4678,6544,6544,9898,8888,5656,6666,9898)
Year <- c(2016,2016,2017,2017,2017,2017,2016,2016,2016,2017,2017,2017)
DF <- data_frame(ID,Program,Code,Year)
DF
#> # A tibble: 12 x 4
#>           ID Program  Code  Year
#>        <dbl> <chr>   <dbl> <dbl>
#>  1 18998878. A111    1222. 2016.
#>  2  8888888. B488    4534. 2016.
#>  3 57485746. T687     543. 2017.
#>  4 18998878. A111    1222. 2017.
#>  5 45454536. G888    4678. 2017.
#>  6 64536475. T444    6544. 2017.
#>  7 64536475. T444    6544. 2016.
#>  8 87966666. P867    9898. 2016.
#>  9 58675844. R444    8888. 2016.
#> 10 58695847. B323    5656. 2017.
#> 11 68574443. F888    6666. 2017.
#> 12 87966666. P867    9898. 2017.


DF %>% 
  arrange(ID, Year) %>% 
  distinct(ID, .keep_all = TRUE)
#> # A tibble: 9 x 4
#>          ID Program  Code  Year
#>       <dbl> <chr>   <dbl> <dbl>
#> 1  8888888. B488    4534. 2016.
#> 2 18998878. A111    1222. 2016.
#> 3 45454536. G888    4678. 2017.
#> 4 57485746. T687     543. 2017.
#> 5 58675844. R444    8888. 2016.
#> 6 58695847. B323    5656. 2017.
#> 7 64536475. T444    6544. 2016.
#> 8 68574443. F888    6666. 2017.
#> 9 87966666. P867    9898. 2016.

由reprex package（v0.2.0）创建于2018-03-07。

Answer 2

ID<-c(18998878,8888888,57485746,18998878,45454536,64536475,64536475,87966666,58675844,58695847,68574443,87966666)
Program<-c("A111","B488","T687","A111","G888","T444","T444","P867","R444","B323","F888","P867")
Code<-c(1222,4534,543,1222,4678,6544,6544,9898,8888,5656,6666,9898)
Year<-c(2016,2016,2017,2017,2017,2017,2016,2016,2016,2017,2017,2017)
DF<-data_frame(ID,Program,Code,Year)

filter(DF, (! duplicated(ID)) & Year == 2017)

如果年份是2017年，这将删除第二次或以后出现的任何ID。值得注意的是，没有任何示例，所以我可能误解了您的问题。

Answer 3

您将其划分为两个数据框，一个年份等于2017年，另一个年份不等于2017年。

 DF1 <- DF %>% filter(Year==2017) 
 DF2 <- DF %>% filter(Year!=2017)

然后使用distinct（）通过ID列对DF1进行重复数据删除。 Keep_all是保留其余值。

 DF3 <- DF1 %>% distinct(ID,.keep_all = T)

现在，您可以通过将DF2和DF3与rbind（）

结合使用来获得最终结果

 df_all <- rbind(DF2,DF3)

如何使用Tidyverse根据另一列的值删除选择重复值

3 个答案: