How can I subset rows in a data frame in R based on a vector of values?

Question

I have two data sets that are supposed to be the same size but aren\'t. I need to trim the values from A that are not in B and vice versa in order to eliminate noise from a

Answer 1

If you really just want to subset each data frame by an index that exists in both data frames, you can do this with the 'match' function, like so:

data_A[match(data_B$index, data_A$index, nomatch=0),]
data_B[match(data_A$index, data_B$index, nomatch=0),]

This is, though, the same as:

data_A[data_A$index %in% data_B$index,]
data_B[data_B$index %in% data_A$index,]

Here is a demo:

# Set seed for reproducibility.
set.seed(1)

# Create two sample data sets.
data_A <- data.frame(index=sample(1:200, 90, rep=FALSE), value=runif(90))
data_B <- data.frame(index=sample(1:200, 120, rep=FALSE), value=runif(120))

# Subset data of each data frame by the index in the other.
t_A <- data_A[match(data_B$index, data_A$index, nomatch=0),]
t_B <- data_B[match(data_A$index, data_B$index, nomatch=0),]

# Make sure they match.
data.frame(t_A[order(t_A$index),], t_B[order(t_B$index),])[1:20,]

#    index     value index.1    value.1
# 27     3 0.7155661       3 0.65887761
# 10    12 0.6049333      12 0.14362694
# 88    14 0.7410786      14 0.42021589
# 56    15 0.4525708      15 0.78101754
# 38    18 0.2075451      18 0.70277874
# 24    23 0.4314737      23 0.78218212
# 34    32 0.1734423      32 0.85508236
# 22    38 0.7317925      38 0.56426384
# 84    39 0.3913593      39 0.09485786
# 5     40 0.7789147      40 0.31248966
# 74    43 0.7799849      43 0.10910096
# 71    45 0.2847905      45 0.26787813
# 57    46 0.1751268      46 0.17719454
# 25    48 0.1482116      48 0.99607737
# 81    53 0.6304141      53 0.26721208
# 60    58 0.8645449      58 0.96920881
# 30    59 0.6401010      59 0.67371223
# 75    61 0.8806190      61 0.69882454
# 63    64 0.3287773      64 0.36918946
# 19    70 0.9240745      70 0.11350771