On 20/04/2016 7:38 AM, Gaston wrote:
I indeed used is.na() to check length, as I was not sure weather
lenght() was a simple query or would go through the whole vector to
count the elements.
length() is a simple query, and is very fast. The other problem in your
approach (which may not be a
I indeed used is.na() to check length, as I was not sure weather
lenght() was a simple query or would go through the whole vector to
count the elements.
So to sum up, function calls are expensive, therefore recursion should
be avoided, and growing the size of a vector (which is probably
On 19/04/2016 3:39 PM, Gaston wrote:
Hello everyone,
I am learning R since recently, and as a small exercise I wanted to
write a recursive mergesort. I was extremely surprised to discover that
my sorting, although operational, is deeply inefficient in time. Here is
my code :
merge <-
Hello everyone,
I am learning R since recently, and as a small exercise I wanted to
write a recursive mergesort. I was extremely surprised to discover that
my sorting, although operational, is deeply inefficient in time. Here is
my code :
> merge <- function(x,y){
> if (is.na(x[1]))
You could add an extra sequence on the dataframe you wish to sort on.
Merge together, sort by the sequence, delete the sequence.
It's a bit more work, but it will give you what you want.
Bart
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Hello,
I have the following data1 (index are chars):
index
1 008823
2 012689
3 004503
4 002991
5 012689
6 002845
7 012689
8 012395
9 012689
10 009302
11 002845
12 006669
13 008823
14 009302
15 025340
16 012689
and data2 in this format (index2 are chars):
index2 tic
1
Why yes. If you keep reading the helpfile for merge, you come to this bit:
Value:
A data frame. The rows are by default lexicographically sorted on
the common columns, but for ‘sort = FALSE’ are in an unspecified
order.
sort=FALSE doesn't preserve your order; instead it gives
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