df1 = data.frame(id=1,start=as.Date("2012-07-05"),end=as.Date("2012-07-15"))
df2 = data.frame(id=rep(1,1371),date = as.Date(as.Date("2012-05-06"):as.Date("2016-02-05")))
output = dplyr::inner_join(x=df1,y=df2,by="id") %>% filter(date>=start & date<= end)
I have two dataframes which have each one about one millions rows and I want to join them by id and then filter so that for each row, value of column date is comprised between value of startdate and enddate.
An dplyr::inner_join is not working because it asks too much memory.
For each id the date interval is a lot bigger in df2 than in df1 so thats why an inner_join %>% filter is not efficient, is it possible to do it in the same time?
Non-equi join from data.table or sqldf packages could work a lot faster than dplyr so give them a try
df1 = data.frame(id = 1, start = as.Date("2012-07-05"),
end = as.Date("2012-07-15"))
df1
#> id start end
#> 1 1 2012-07-05 2012-07-15
df2 = data.frame(id = rep(1, 1371),
date = seq(as.Date("2012-05-06"), as.Date("2016-02-05"), by = "1 day"))
head(df2)
#> id date
#> 1 1 2012-05-06
#> 2 1 2012-05-07
#> 3 1 2012-05-08
#> 4 1 2012-05-09
#> 5 1 2012-05-10
#> 6 1 2012-05-11
Using sqldf package:
library(sqldf)
sqldf("SELECT f1.id, start, end, date
FROM df1 f1, df2 f2
WHERE f1.id = f2.id AND
f2.date >= f1.start AND
f2.date <= f1.end")
#> id start end date
#> 1 1 2012-07-05 2012-07-15 2012-07-05
#> 2 1 2012-07-05 2012-07-15 2012-07-06
#> 3 1 2012-07-05 2012-07-15 2012-07-07
#> 4 1 2012-07-05 2012-07-15 2012-07-08
#> 5 1 2012-07-05 2012-07-15 2012-07-09
#> 6 1 2012-07-05 2012-07-15 2012-07-10
#> 7 1 2012-07-05 2012-07-15 2012-07-11
#> 8 1 2012-07-05 2012-07-15 2012-07-12
#> 9 1 2012-07-05 2012-07-15 2012-07-13
#> 10 1 2012-07-05 2012-07-15 2012-07-14
#> 11 1 2012-07-05 2012-07-15 2012-07-15
Using non-equi join from data.table package: Benchmark | Video
library(data.table)
## convert both data.frames to data.tables by reference
setDT(df1)
setDT(df2)
# join by id and date within start & end limits
# "x." is used so we can refer to the column in df1 explicitly
df2[df1, .(id, date = x.date, start, end),
on = .(id, date >= start, date <= end)]
#> id date start end
#> 1: 1 2012-07-05 2012-07-05 2012-07-15
#> 2: 1 2012-07-06 2012-07-05 2012-07-15
#> 3: 1 2012-07-07 2012-07-05 2012-07-15
#> 4: 1 2012-07-08 2012-07-05 2012-07-15
#> 5: 1 2012-07-09 2012-07-05 2012-07-15
#> 6: 1 2012-07-10 2012-07-05 2012-07-15
#> 7: 1 2012-07-11 2012-07-05 2012-07-15
#> 8: 1 2012-07-12 2012-07-05 2012-07-15
#> 9: 1 2012-07-13 2012-07-05 2012-07-15
#> 10: 1 2012-07-14 2012-07-05 2012-07-15
#> 11: 1 2012-07-15 2012-07-05 2012-07-15
Created on 2018-03-28 by the reprex package (v0.2.0).