Matching Columns with Overlapping Intervals (lubridate) - r

Question

I have two data frames of different number of rows and number of columns: each of these data frames have a date interval. df has an additional column which indicates some kind of attribute. My goal is to extract information from df ( with the attributes) to df2 under certain conditions. The procedure should be the following:
For each date interval of df2, check if there is any interval in df which overlaps with the interval of df2. If yes, create a column in df2 which indicates the attributes matching with the overlapping interval of df. There can be multiple attributes that are matched to a specific interval of df2.
I created the following example of my data:
library(lubridate)
date1 <- as.Date(c('2017-11-1','2017-11-1','2017-11-4'))
date2 <- as.Date(c('2017-11-5','2017-11-3','2017-11-5'))
df <- data.frame(matrix(NA,nrow=3, ncol = 4))
names(df) <- c("Begin_A", "End_A", "Interval", "Attribute")
df$Begin_A <-date1
df$End_A <-date2
df$Interval <-df$Begin_A %--% df$End_A
df$Attribute<- as.character(c("Attr1","Attr2","Attr3"))
### Second df:
date1 <- as.Date(c('2017-11-2','2017-11-5','2017-11-7','2017-11-1'))
date2 <- as.Date(c('2017-11-3','2017-11-6','2017-11-8','2017-11-1'))
df2 <- data.frame(matrix(NA,nrow=4, ncol = 3))
names(df2) <- c("Begin_A", "End_A", "Interval")
df2$Begin_A <-date1
df2$End_A <-date2
df2$Interval <-df2$Begin_A %--% df2$End_A
This results in these data frames:
df:
Begin_A End_A Interval Attribute
2017-11-01 2017-11-05 2017-11-01 UTC--2017-11-05 UTC Attr1
2017-11-01 2017-11-03 2017-11-01 UTC--2017-11-03 UTC Attr2
2017-11-04 2017-11-05 2017-11-04 UTC--2017-11-05 UTC Attr3
df2:
Begin_A End_A Interval
2017-11-02 2017-11-03 2017-11-02 UTC--2017-11-03 UTC
2017-11-05 2017-11-06 2017-11-05 UTC--2017-11-06 UTC
2017-11-07 2017-11-08 2017-11-07 UTC--2017-11-08 UTC
2017-11-01 2017-11-01 2017-11-01 UTC--2017-11-01 UTC
My desired data frames look like this:
Begin_A End_A Interval Matched_Attr
2017-11-02 2017-11-03 2017-11-02 UTC--2017-11-03 UTC Attr1;Attr2
2017-11-05 2017-11-06 2017-11-05 UTC--2017-11-06 UTC Attr1;Attr3
2017-11-07 2017-11-08 2017-11-07 UTC--2017-11-08 UTC NA
2017-11-01 2017-11-01 2017-11-01 UTC--2017-11-01 UTC Attr1;Attr2
I already looked into the int_overlaps() function but could not make the "scanning through all intervals of another column"-part work.
If yes, is there any solution that makes use of the tidyr environment?

Answer 1

Using tidyverse´s lubridate package and it´s function int_overlaps(), you can create a simple for loop to go through the individual values of df2$Interval like follows:
df2$Matched_Attr <- NA
for(i in 1:nrow(df2)){
df2$Matched_Attr[i] <- paste(df$Attribute[int_overlaps(df2$Interval[i], df$Interval)], collapse=", ")
}
giving the following outcome
# Begin_A End_A Interval Matched_Attr
#1 2017-11-02 2017-11-03 2017-11-02 UTC--2017-11-03 UTC Attr1, Attr2
#2 2017-11-05 2017-11-06 2017-11-05 UTC--2017-11-06 UTC Attr1, Attr3
#3 2017-11-07 2017-11-08 2017-11-07 UTC--2017-11-08 UTC
#4 2017-11-01 2017-11-01 2017-11-01 UTC--2017-11-01 UTC Attr1, Attr2
I left the NA strategy open, but additional line df2$Matched_Attr[df2$Matched_Attr==""]<-NA would return exact desired outcome.
In response to your comment (only perform the above action when a df$ID[i]==df2$ID[i] condition is met), the inplementation follows:
library(lubridate)
#df
df <- data.frame(Attribute=c("Attr1","Attr2","Attr3"),
ID = c(3,2,1),
Begin_A=as.Date(c('2017-11-1','2017-11-1','2017-11-4')),
End_A=as.Date(c('2017-11-5','2017-11-3','2017-11-5')))
df$Interval <- df$Begin_A %--% df$End_A
### Second df:
df2 <- data.frame(ID=c(3,4,5),
Begin_A=as.Date(c('2017-11-2','2017-11-5','2017-11-7')),
End_A=as.Date(c('2017-11-3','2017-11-6','2017-11-8')))
df2$Interval <- df2$Begin_A %--% df2$End_A
df2$Matched_Attr <- NA
for(i in 1:nrow(df2)){
if(df2$ID[i]==df$ID[i]){
df2$Matched_Attr[i] <- paste(df$Attribute[int_overlaps(df2$Interval[i], df$Interval)], collapse=", ")
}
}
print(df2)
# ID Begin_A End_A Interval Matched_Attr
#1 3 2017-11-02 2017-11-03 2017-11-02 UTC--2017-11-03 UTC Attr1, Attr2
#2 4 2017-11-05 2017-11-06 2017-11-05 UTC--2017-11-06 UTC <NA>
#3 5 2017-11-07 2017-11-08 2017-11-07 UTC--2017-11-08 UTC <NA>