如何使用向量将数据帧缩减为单行

Question

我有这个DF

  email       date      user_ipaddress       other data    
1 x@bla.com 2020-03-24  177.95.75.230         xxxx
2 x@bla.com 2020-04-02  177.139.49.93         yyyy
3 x@bla.com 2020-04-02  177.139.49.93         zzzz

并且我想将此数据转换为要存储的形状

整个问题将是一个包含不同电子邮件的大数据框，我想像这样在一行中减少每封电子邮件的所有数据

  email       date      user_ipaddress                       other data    
1 x@bla.com 2020-04-02  c('177.95.75.230','177.139.49.93')   c('xxxx','yyyy','zzzz')

实际上，如果有人可以帮助我解决只有一个电子邮件地址的情况，那将挽救我的生命，但请随时帮助解决整个问题

使用

ipadreessVec<-Reduce(append,x =df$network_userid)

我可以获得我的矢量 c('177.95.75.230','177.139.49.93') 但如果我尝试制作

newdf$network_userid<-a

我明白了

Error in `$<-.data.frame`(`*tmp*`, network_userid, value = c("20562206-f557-48a3-861b-5d1e18524bbb",  : 
  replacement has 3 rows, data has 1

任何让我更进一步的答案都会得到批准，即使它不能解决所有问题。

Answer 1

我们可以创建一个按 'email'、'date'

分组的 list 列

library(dplyr)
DF %>% 
    group_by(email, date) %>%
    summarise_all(list)
# A tibble: 2 x 4
# Groups:   email [1]
#  email     date       user_ipaddress otherdata
#  <chr>     <chr>      <list>         <list>   
#1 x@bla.com 2020-03-24 <chr [1]>      <chr [1]>
#2 x@bla.com 2020-04-02 <chr [2]>      <chr [2]>

或者在 devel 版本中使用 across 和 summarise

DF %>%
   group_by(email, date) %>% 
   summarise(across(everything(), list))
# A tibble: 2 x 4
# Groups:   email [1]
#  email     date       user_ipaddress otherdata
#  <chr>     <chr>      <list>         <list>   
#1 x@bla.com 2020-03-24 <chr [1]>      <chr [1]>
#2 x@bla.com 2020-04-02 <chr [2]>      <chr [2]>

数据

DF <- structure(list(email = c("x@bla.com", "x@bla.com", "x@bla.com"
), date = c("2020-03-24", "2020-04-02", "2020-04-02"),
 user_ipaddress = c("177.95.75.230", 
"177.139.49.93", "177.139.49.93"),
otherdata = c("xxxx", "yyyy", 
"zzzz")), class = "data.frame", row.names = c("1", "2", "3"))

Answer 2

我可能误会了你，你似乎更可能想要@akrun 节目之类的东西，但从字面上解释你，你可能想要使用 dput:

的东西

as.data.frame(lapply(df, function(x) capture.output(dput(unique(x)))))
#>         email                          date                      user_ipaddress
#> 1 "x@bla.com" c("2020-03-24", "2020-04-02") c("177.95.75.230", "177.139.49.93")
#>                       other
#> 1 c("xxxx", "yyyy", "zzzz")

Answer 3

library('data.table')

通过电子邮件和日期：

setDT(df)[, .(user_ipaddress = paste0(user_ipaddress, collapse = ","),
              other = paste0(other_data, collapse = ",")), by = .(email, date)]

#       email       date              user_ipaddress     other
# 1: x@bla.com 2020-03-24               177.95.75.230      xxxx
# 2: x@bla.com 2020-04-02 177.139.49.93,177.139.49.93 yyyy,zzzz

仅通过电子邮件：

setDT(df)[, .(date = paste0(date, collapse = ","),
              user_ipaddress = paste0(user_ipaddress, collapse = ","),
              other = paste0(other_data, collapse = ",")), by = .(email)]

#        email                             date                            user_ipaddress          other
# 1: x@bla.com 2020-03-24,2020-04-02,2020-04-02 177.95.75.230,177.139.49.93,177.139.49.93 xxxx,yyyy,zzzz

数据：

df <- read.table(text='email       date      user_ipaddress       other_data    
1 x@bla.com 2020-03-24  177.95.75.230         xxxx
                 2 x@bla.com 2020-04-02  177.139.49.93         yyyy
                 3 x@bla.com 2020-04-02  177.139.49.93         zzzz', header = TRUE, stringsAsFactors = FALSE)

Answer 4

也许你可以试试 aggregate in base R:

dfout <- aggregate(.~email,df,FUN = function(x) list(unique(levels(x))))

这样

> dfout
      email                   date               user_ipaddress       other data
1 x@bla.com 2020-03-24, 2020-04-02 177.139.49.93, 177.95.75.230 xxxx, yyyy, zzzz

数据

df <-  structure(list(email = c("x@bla.com", "x@bla.com", "x@bla.com"
), date = c("2020-03-24", "2020-04-02", "2020-04-02"), user_ipaddress = c("177.95.75.230", 
"177.139.49.93", "177.139.49.93"), `other data` = c("xxxx", "yyyy", 
"zzzz")), class = "data.frame", row.names = c(NA, -3L))

如何使用向量将数据帧缩减为单行

How to reduce a data frame into single row with vectors

reduce

r

vector

dataframe

数据