Hi all,
Just a quick question:
I want to generate a column of counts of a particular variable. The easiest way
seems to be using table(). For reasonably small amounts of data, there seems to
be no problem.
C <- data.frame(A1 = sample(1:1000, 100000, replace = TRUE), B1 =
sample(1:1000, 100000, replace = TRUE))
C$countC <- table(C$A1)[C$A1]
summary(C$countC)
Min. 1st Qu. Median Mean 3rd Qu. Max.
65 94 101 101 108 132
However, if I'm building a table from a larger set (note that now I'm sampling
from 1:10k, rather than 1:1k), it generates NAs, despite there being no NAs in
the data I'm building the table from:
C <- data.frame(A1 = sample(1:10000, 100000, replace = TRUE), B1 =
sample(1:10000, 100000, replace = TRUE))
C$countC <- table(C$A1)[C$A1]
summary(C$A1)
Min. 1st Qu. Median Mean 3rd Qu. Max.
1 2512 5005 5008 7502 10000
summary(C$countC)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.00 8.00 10.00 10.18 12.00 25.00 7
Note that if you cannot replicate this on your computer, try increasing the
size of the set to sample from (setting it at 1000000 did the trick for a
colleague of mine).
The problem appears not to occur if the data are not in a data-frame.
A <- sample(1:10000, 1000000, replace = TRUE)
summary(table(as.factor(A))[A])
Min. 1st Qu. Median Mean 3rd Qu. Max.
57 94 101 101 108 144
It seems to only have thrown NAs only for the last few categories (in the case
sampling from 100k, only 99998, 99999 and 100000). That makes it manageable,
but definitely not ideal.
I also posted this question to Stack Overflow, and users there have contributed
a work-around. However, I would like to know why table() is exhibiting this
behaviour.
Cheers, Jim
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