R: Subsetting a data frame using a list of dates as the filter

Question

I have a data frame with a date column and some other value columns. I would like to extract from the data frame those rows in which the date column matches any of the eleme

Answer 1

Or you can go the other way round to what @RYogi suggested and convert the Date into a string:

testdf[as.character(testdf$mydate) %in% c('2012-01-05', '2012-01-09'),]
      mydate col1 col2 col3
5 2012-01-05    5   15   25
9 2012-01-09    9   19   29

Edit: timing

Converting Date to a string is slightly faster, but it doesn't really make a difference:

library(rbenchmark)
benchmark(asDate=testdf[testdf$mydate %in% as.Date(c('2012-01-05', '2012-01-09')),],
  asString=testdf[as.character(testdf$mydate) %in% c('2012-01-05', '2012-01-09'),], 
  replications=1000)

#     test replications elapsed relative user.self sys.self user.child
# 1   asDate         1000   0.211 1.076531     0.212        0          0
# 2 asString         1000   0.196 1.000000     0.192        0          0
#  sys.child
# 1         0
# 2         0

Answer 2

You have to convert the date string into a Date variable using as.Date (try ?as.Date at the console). Bonus: you can drop which:

> testdf[testdf$mydate %in% as.Date(c('2012-01-05', '2012-01-09')),]
      mydate col1 col2 col3
5 2012-01-05    5   15   25
9 2012-01-09    9   19   29

Answer 3

Both suggestions so far are definitely good, but if you are going to be doing a lot of work with dates, you may want to invest some time with the xts package:

# Some sample data for 90 consecutive days 
set.seed(1)
testdf <- data.frame(mydate = seq(as.Date('2012-01-01'), 
                                  length.out=90, by = 'day'),
                     col1 = rnorm(90), col2 = rnorm(90),
                     col3 = rnorm(90))

# Convert the data to an xts object
require(xts)
testdfx = xts(testdf, order.by=testdf$mydate)

# Take a random sample of dates
testdfx[sample(index(testdfx), 5)]
#                   col1        col2        col3
# 2012-01-17 -0.01619026  0.71670748  1.44115771
# 2012-01-29 -0.47815006  0.49418833 -0.01339952
# 2012-02-05 -0.41499456  0.71266631  1.51974503
# 2012-02-27 -1.04413463  0.01739562 -1.18645864
# 2012-03-26  0.33295037 -0.03472603  0.27005490

# Get specific dates
testdfx[c('2012-01-05', '2012-01-09')]
#                 col1      col2       col3
# 2012-01-05 0.3295078  1.586833  0.5210227
# 2012-01-09 0.5757814 -1.224613 -0.4302118

You can also get dates from another vector.

# Get dates from another vector
lookup = c("2012-01-12", "2012-01-31", "2012-03-05", "2012-03-19")
testdfx[lookup]
testdfx[lookup]
#                   col1        col2       col3
# 2012-01-12  0.38984324  0.04211587  0.4020118
# 2012-01-31  1.35867955 -0.50595746 -0.1643758
# 2012-03-05 -0.74327321 -1.48746031  1.1629646
# 2012-03-19  0.07434132 -0.14439960  0.3747244

The xts package will give you intelligent subsetting options. For instance, testdfx["2012-03"] will return all the data from March; testdfx["2012"] will return for the year; testdfx["/2012-02-15"] will return the data from the start of the dataset to February 15; and testdfx["2012-02-15/"] will go from February 15 to the end of the dataset.