使用dplyr按组将NA替换为上一个或下一个值 [英] Replace NA with previous or next value, by group, using dplyr

问题描述

我有一个按日期降序排列的数据框.

I have a data frame which is arranged by descending order of date.

ps1 = data.frame(userID = c(21,21,21,22,22,22,23,23,23), 
             color = c(NA,'blue','red','blue',NA,NA,'red',NA,'gold'), 
             age = c('3yrs','2yrs',NA,NA,'3yrs',NA,NA,'4yrs',NA), 
             gender = c('F',NA,'M',NA,NA,'F','F',NA,'F') 
)

我希望将NA值估算(替换为以前的值) 并按用户ID分组 如果userID的第一行具有NA，则替换为该userid组的下一组值.

I wish to impute(replace) NA values with previous values and grouped by userID In case the first row of a userID has NA then replace with the next set of values for that userid group.

我正在尝试使用dplyr和zoo包之类的东西...但是它不起作用

I am trying to use dplyr and zoo packages something like this...but its not working

cleanedFUG <- filteredUserGroup %>%
 group_by(UserID) %>%
 mutate(Age1 = na.locf(Age), 
     Color1 = na.locf(Color), 
     Gender1 = na.locf(Gender) ) 

我需要这样的结果df:

I need result df like this:

                      userID color  age gender
                1     21  blue 3yrs      F
                2     21  blue 2yrs      F
                3     21   red 2yrs      M
                4     22  blue 3yrs      F
                5     22  blue 3yrs      F
                6     22  blue 3yrs      F
                7     23   red 4yrs      F
                8     23   red 4yrs      F
                9     23  gold 4yrs      F

推荐答案

require(tidyverse) #fill is part of tidyr

ps1 %>% 
  group_by(userID) %>% 
  fill(color, age, gender) %>% #default direction down
  fill(color, age, gender, .direction = "up")

哪个给您:

Source: local data frame [9 x 4]
Groups: userID [3]

  userID  color    age gender
   <dbl> <fctr> <fctr> <fctr>
1     21   blue   3yrs      F
2     21   blue   2yrs      F
3     21    red   2yrs      M
4     22   blue   3yrs      F
5     22   blue   3yrs      F
6     22   blue   3yrs      F
7     23    red   4yrs      F
8     23    red   4yrs      F
9     23   gold   4yrs      F

这篇关于使用dplyr按组将NA替换为上一个或下一个值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！