Question

我在操作以下数据结构时遇到了困难：

属性数据框：

ID  Begin_A      End_A        Interval                         Value
5   2017-03-01   2017-03-10   2017-03-01 UTC--2017-03-10 UTC   Cat1
10  2017-12-01   2017-12-02   2017-12-01 UTC--2017-12-02 UTC   Cat2
5   2017-03-01   2017-03-03   2017-03-01 UTC--2017-03-03 UTC   Cat3
10  2017-12-05   2017-12-10   2017-12-05 UTC--2017-12-10 UTC   Cat4

预订数据框：

ID  Begin_A      End_A        Interval 
5   2017-03-03   2017-03-05   2017-03-03 UTC--2017-03-05 UTC
6   2017-05-03   2017-05-05   2017-05-03 UTC--2017-05-05 UTC
8   2017-03-03   2017-03-05   2017-03-03 UTC--2017-03-05 UTC
10  2017-12-05   2017-12-06   2017-12-05 UTC--2017-12-06 UTC

期望的结果框架（预订）：

ID  Begin_A      End_A        Interval                        Attribute_value
5   2017-03-03   2017-03-05   2017-03-03 UTC--2017-03-05 UTC  Cat1,Cat3
6   2017-05-03   2017-05-05   2017-05-03 UTC--2017-05-05 UTC  NA
8   2017-03-03   2017-03-05   2017-03-03 UTC--2017-03-05 UTC  NA
10  2017-12-05   2017-12-06   2017-12-05 UTC--2017-12-06 UTC  Cat4

数据框的代码：

library(lubridate)
# Attributes data frame:
date1 <- as.Date(c('2017-3-1','2017-12-1','2017-3-1','2017-12-5'))
date2 <- as.Date(c('2017-3-10','2017-12-2','2017-3-3','2017-12-10'))
attributes <- data.frame(matrix(NA,nrow=4, ncol = 5)) 
names(attributes) <- c("ID","Begin_A", "End_A", "Interval", "Value")
attributes$ID <- as.numeric(c(5,10,5,10))
attributes$Begin_A <-date1
attributes$End_A <-date2
attributes$Interval <-attributes$Begin_A %--% attributes$End_A
attributes$Value<- as.character(c("Cat1","Cat2","Cat3","Cat4"))

### Bookings data frame:

date1 <- as.Date(c('2017-3-3','2017-5-3','2017-3-3','2017-12-5'))
date2 <- as.Date(c('2017-3-5','2017-5-5','2017-3-5','2017-12-6'))
bookings <- data.frame(matrix(NA,nrow=4, ncol = 4)) 
names(bookings) <- c("ID","Begin_A", "End_A", "Interval")
bookings$ID <- as.numeric(c(5,6,8,10))
bookings$Begin_A <-date1
bookings$End_A <-date2
bookings$Interval <-bookings$Begin_A %--% bookings$End_A

达到我的结果框架的程序应如下：从预订中获取ID，过滤属性ID与预订ID匹配的属性数据框的所有行。检查具有匹配属性ID的哪些行也具有重叠的时间间隔（来自lubridate的int_overlaps）。然后从“值”列中获取相应的值，并在Attribute_value列中打印每个值。

Answer 1

来自tidyverse的解决方案。

library(tidyverse)

attributes2 <- attributes %>%
  select(-Interval) %>%
  gather(Type, Date, ends_with("_A")) %>%
  select(-Type) %>%
  group_by(Value) %>%
  complete(Date = full_seq(Date, period = 1), ID) %>%
  ungroup()

bookings2 <- bookings %>%
  select(-Interval) %>%
  gather(Type, Date, ends_with("_A")) %>%
  select(-Type) %>%
  group_by(ID) %>%
  complete(Date = full_seq(Date, period = 1)) %>%
  ungroup()

bookings3 <- bookings2 %>%
  left_join(attributes2, by = c("ID", "Date")) %>%
  group_by(ID) %>%
  summarise(Attribute_value = toString(sort(unique(Value)))) %>%
  mutate(Attribute_value = ifelse(Attribute_value %in% "", NA, Attribute_value))

bookings4 <- bookings %>% left_join(bookings3, by = "ID")
bookings4
  ID    Begin_A      End_A                       Interval Attribute_value
1  5 2017-03-03 2017-03-05 2017-03-03 UTC--2017-03-05 UTC      Cat1, Cat3
2  6 2017-05-03 2017-05-05 2017-05-03 UTC--2017-05-05 UTC            <NA>
3  8 2017-03-03 2017-03-05 2017-03-03 UTC--2017-03-05 UTC            <NA>
4 10 2017-12-05 2017-12-06 2017-12-05 UTC--2017-12-06 UTC            Cat4

匹配值以重叠间隔和ID为条件

1 个答案: