Indexing condition with a vector [closed]

Question

Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.

---

This question appears to be off-topic because it lacks sufficient information to diagnose the problem. Describe your problem in more detail or include a minimal example in the question itself.

Closed 9 years ago.

Improve this question

I have two data frames that contain time series, unfortunately one has fewer element. I would like to extract the rows of the longer data frame for which there exists an entry with the corresponding date in the shorter data frame.

My idea was to simply get the Date values of the shorter data frame in a vector and somehow use that vector inside an indexing condition, so that only the entries of the longer data frame for which the Date entry is included in the Date vector in the indexing condition are selected. Unfortunately I was unable to find a way to use the vector in a boolean condition and the only solution that I have found involved writing a slow for-loop. Can anybody tell me how to do this without a for-loop?

Answer 1

Consider the following example. you have two data.frames df1 and df2, where df1 has more rows than df2.

date <- seq(as.Date("2014-01-01"),as.Date("2014-01-10"), 1)
value <- 20:29
df1 <- data.frame(date,value)

df1
#         date value
#1  2014-01-01    20
#2  2014-01-02    21
#3  2014-01-03    22
#4  2014-01-04    23
#5  2014-01-05    24
#6  2014-01-06    25
#7  2014-01-07    26
#8  2014-01-08    27
#9  2014-01-09    28
#10 2014-01-10    29

date <- seq(as.Date("2014-01-01"),as.Date("2014-01-10"), 2)
value2 <- 5:1
df2 <- data.frame(date, value2)

df2
#        date value2 
#1 2014-01-01      5
#2 2014-01-03      4
#3 2014-01-05      3
#4 2014-01-07      2
#5 2014-01-09      1

To extract all the rows of df1 which have corresponding date entries in df2 you can use the %in% operator:

df1[df1$date %in% df2$date, ]

#        date value
#1 2014-01-01    20
#3 2014-01-03    22
#5 2014-01-05    24
#7 2014-01-07    26
#9 2014-01-09    28

Most likely, this will work the same for your data.