R function rep() in Python (replicates elements of a list/vector)

Question

The R function rep() replicates each element of a vector:

> rep(c("A","B"), times=2) [1] "A" "B" "A" "B" 

This is like the list multiplication in Python:

>>> ["A","B"]*2 ['A', 'B', 'A', 'B'] 

But with the rep() R function it is also possible to specifiy the number of repeats for each element of the vector:

> rep(c("A","B"), times=c(2,3)) [1] "A" "A" "B" "B" "B" 

Is there such a function availbale in Python ? Otherwise how could one define it ? By the way I'm also interested in such a function for duplicating rows of an array.

Answer 1

Not sure if there's a built-in available for this, but you can try something like this:

>>> lis = ["A", "B"] >>> times = (2, 3) >>> sum(([x]*y for x,y in zip(lis, times)),[]) ['A', 'A', 'B', 'B', 'B'] 

Note that sum() runs in quadratic time. So, it's not the recommended way.

>>> from itertools import chain, izip, starmap >>> from operator import mul >>> list(chain.from_iterable(starmap(mul, izip(lis, times)))) ['A', 'A', 'B', 'B', 'B'] 

Timing comparions:

>>> lis = ["A", "B"] * 1000 >>> times = (2, 3) * 1000 >>> %timeit list(chain.from_iterable(starmap(mul, izip(lis, times)))) 1000 loops, best of 3: 713 µs per loop >>> %timeit sum(([x]*y for x,y in zip(lis, times)),[]) 100 loops, best of 3: 15.4 ms per loop 

Answer 2

Use numpy arrays and the numpy.repeat function:

import numpy as np  x = np.array(["A", "B"]) print np.repeat(x, [2, 3], axis=0)  ['A' 'A' 'B' 'B' 'B']