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rdataframesubsetr-faq

Subset data frame based on number of rows per group

I have data like this, where some "name" occurs more than three times:

df <- data.frame(name = c("a", "a", "a", "b", "b", "c", "c", "c", "c"), x = 1:9)

  name x
1    a 1
2    a 2
3    a 3
4    b 4
5    b 5
6    c 6
7    c 7
8    c 8
9    c 9

I wish to subset (filter) the data based on number of rows (observations) within each level of the name variable. If a certain level of name occurs more than say 3 times, I want to remove all rows belonging to that level. So in this example, we would drop observations where name == c, since there are > 3 rows in that group:

  name x
1    a 1
2    a 2
3    a 3
4    b 4
5    b 5

I wrote this code, but can't get it to work. 

as.data.frame(table(unique(df)$name))
subset(df, name > 3)
Solution

  • First, two base alternatives. One relies on table, and the other on ave and length. Then, two data.table ways.

    1. table

    tt <- table(df$name)

df2 <- subset(df, name %in% names(tt[tt < 3]))
# or
df2 <- df[df$name %in% names(tt[tt < 3]), ]

    If you want to walk it through step by step:

    # count each 'name', assign result to an object 'tt'
tt <- table(df$name)

# which 'name' in 'tt' occur more than three times?
# Result is a logical vector that can be used to subset the table 'tt'
tt < 3

# from the table, select 'name' that occur < 3 times
tt[tt < 3]

# ...their names
names(tt[tt < 3])

# rows of 'name' in the data frame that matches "the < 3 names"
# the result is a logical vector that can be used to subset the data frame 'df'
df$name %in% names(tt[tt < 3])

# subset data frame by a logical vector
# 'TRUE' rows are kept, 'FALSE' rows are removed.
# assign the result to a data frame with a new name
df2 <- subset(df, name %in% names(tt[tt < 3]))
# or
df2 <- df[df$name %in% names(tt[tt < 3]), ]

    2. ave and length

    As suggested by @flodel:

    df[ave(df$x, df$name, FUN = length) < 3, ]

    3. data.table: .N and .SD:

    library(data.table)
setDT(df)[, if (.N < 3) .SD, by = name]

    4. data.table: .N and .I:

    setDT(df)
df[df[, .I[.N < 3], name]$V1]

    See also the related Q&A Count number of observations/rows per group and add result to data frame.