清除具有重复但因子级别不同的Origina目标数据

Question

我有一些GIS数据，其中包含始发地和目的地（OD）以及有关OD一天中的时间的信息。我打算对此进行映射，并根据每天的时间对OD进行着色。

一件事是，某些OD在白天和黑夜中都有可能以不同的顺序出现。我想以不同的方式标记这些标记，例如“日/夜”

是否有简单的方法可以做到这一点？我的MWE只是一个OD，但我需要在其他几个中进行识别。无论顺序如何，我都可以找到重复项，但是我不知道如何找出是否存在两个时间案例，以及如何用“日/夜”替换它们。

library(data.table)
Origin<-c("London", "Paris")
Destination<-rev(Origin)
dt<-data.table(Origin=Origin, Destination=Destination, Time=c("Day", "Night"))
#duplicates regardless of order
dat.sort = t(apply(dt[,.(Origin,Destination)], 1, sort))
dt[duplicated(dat.sort) | duplicated(dat.sort, fromLast=TRUE),]
´´´

Answer 1

您可以使用dplyr软件包，如下所述：

根据您的需要随意更改条件。

library(data.table)
library(dplyr)

# Creating data
dt <- 
  data.table(
    Origin = c("London", "Paris", "Italy", "Spain", "Portugal", "Poland"),
    Destination = c("Paris", "London", "Norway", "Portugal", "Spain", "Spain"),
    Time = c("Day", "Night", "Day", NA_character_, NA_character_, NA_character_)
  )

dt

# Origin Destination  Time
# London   Paris      Day
# Paris    London     Night
# Italy    Norway     Day
# Spain    Portugal   <NA>
# Portugal Spain      <NA>
# Poland   Spain      <NA>

dt %>%
  # pmin and pmax are used to sort the 2 columns
  # in order to group by them regardless to their order
  group_by(Origin2 = pmin(Origin, Destination), 
           Destination2 = pmax(Origin, Destination)) %>%
  mutate(count = n(), # To check if Origin/destination are repeated or not
         row = row_number(), # Place holder to know if it was first to repeat or second
         # If not repeated then make Time = Day
         # If repeated and first occurance then Time = Day
         # If repeated and second occurance then Time = Night
         Time = case_when(count == 1 ~ "Day",
                          count == 2 & row == 1 ~ "Day",
                          count == 2 & row == 2 ~ "Night")) %>%
  ungroup() %>%
  select(Origin, Destination, Time)

# Origin   Destination Time 
# <chr>    <chr>       <chr>
#   1 London   Paris       Day  
# 2 Paris    London      Night
# 3 Italy    Norway      Day  
# 4 Spain    Portugal    Day  
# 5 Portugal Spain       Night
# 6 Poland   Spain       Day