合并数据框中的文本元素并删除文本来自的行

Question

这个玩具数据框代表人的时间条目。我可用的格式以完全随机的模式为同一个人和同一天提供多个文本条目。同一个人和同一天最多可以有 15 个文本条目。多文本条目的行中没有任何人物条目。

structure(list(Date = structure(c(1514764800, 1514764800, NA, 
1517443200, 1519862400, NA, NA, NA, 1519862400, NA, NA), class = c("POSIXct", 
"POSIXt"), tzone = "UTC"), Person = c("FMC", "ABC", NA, "FMC", 
"ABC", NA, NA, NA, "RWM", NA, NA), Text = c("work on request", 
"More text", "third line", "email to re: summary", "work on loan documents", 
"sixth line of text", "text seven", "eighth in a series", "conferences with working group", 
"line ten", "review and provide comments")), row.names = c(NA, 
-11L), class = c("tbl_df", "tbl", "data.frame"))

我如何组合文本元素，以便每个人的条目只有一行每天，删除不需要的行（一旦文本粘贴在一起）和到达以下对象？

EDITED QUESTION 省略了 for 循环，我尝试失败了。

必须有一种方法可以将给定人员在给定日期的所有文本合并为一行（例如，ABC 在 2018 年 1 月 1 日有两个条目）并删除其中的行合并后的文字来了。

Answer 1

library(dplyr)

merge_lines <- function(x) paste(x, collapse = ' ')

df %>% 
  zoo::na.locf(.) %>%
  group_by(Person) %>%
  summarise_at(vars(Text), (funs(merge_lines)))

结果：

# A tibble: 4 x 2
  Person Text                                                                   
  <chr>  <chr>                                                                  
1 ABC    More text third line                                                   
2 FMC    work on request email to re: summary                                   
3 HIL    work on loan documents sixth line of text text seven eighth in a series
4 RWM    conferences with working group line ten review and provide comments

Answer 2

我们可以使用na.locf用最后一个非缺失值填充缺失值（NA），然后group_by连续出现Person和summarise Text 通过 paste 将它们组合在一起。

library(dplyr)
library(zoo)
library(data.table)

df %>%
  na.locf(.) %>%
  group_by(group = rleid(Person)) %>%
  summarise(Text = paste0(Text, collapse = " "))


#  group Text                                                                   
#  <int> <chr>                                                                  
#1     1 work on request                                                        
#2     2 More text third line                                                   
#3     3 email to re: summary                                                   
#4     4 work on loan documents sixth line of text text seven eighth in a series
#5     5 conferences with working group line ten review and provide comments

对于更新后的问题，我们可以做

library(dplyr)
library(zoo)

df %>%
  na.locf(.) %>%
  group_by(Date, Person) %>%
  summarise(Text = paste0(Text, collapse = " "))

Answer 3

不用复杂，直接用tidyverse.

根据问题的变化进行调整：

library(tidyverse)

> df%>%
   fill(Date:Person, Date:Person) %>% # Fills missing values in using the previous entry.
   group_by(Date, Person) %>%
   summarise(Text = paste(Text, collapse = ' '))

# A tibble: 5 x 3
  Date                Person Text                                                                   
  <dttm>              <chr>  <chr>                                                                  
1 2018-01-01 00:00:00 ABC    More text third line                                                   
2 2018-01-01 00:00:00 FMC    work on request                                                        
3 2018-02-01 00:00:00 FMC    email to re: summary                                                   
4 2018-03-01 00:00:00 ABC    work on loan documents sixth line of text text seven eighth in a series
5 2018-03-01 00:00:00 RWM    conferences with working group line ten review and provide comments

数据：

# A tibble: 11 x 3
   Date                Person Text                          
   <dttm>              <chr>  <chr>                         
 1 2018-01-01 00:00:00 FMC    work on request               
 2 2018-01-01 00:00:00 ABC    More text                     
 3 NA                  NA     third line                    
 4 2018-02-01 00:00:00 FMC    email to re: summary          
 5 2018-03-01 00:00:00 ABC    work on loan documents        
 6 NA                  NA     sixth line of text            
 7 NA                  NA     text seven                    
 8 NA                  NA     eighth in a series            
 9 2018-03-01 00:00:00 RWM    conferences with working group
10 NA                  NA     line ten                      
11 NA                  NA     review and provide comments

合并数据框中的文本元素并删除文本来自的行

Combine text elements in a data frame and remove rows the text came from

r

copy-paste