First of all shuffling is the process of transfering data from the mappers to the reducers, so I think it is obvious that it is necessary for the reducers, since otherwise, they wouldn’t be able to have any input (or input from every mapper). Shuffling can start even before the map phase has finished, to … Read more
random.shuffle() changes the x list in place. Python API methods that alter a structure in-place generally return None, not the modified data structure. >>> x = [‘foo’, ‘bar’, ‘black’, ‘sheep’] >>> random.shuffle(x) >>> x [‘black’, ‘bar’, ‘sheep’, ‘foo’] If you wanted to create a new randomly-shuffled list based on an existing one, where the existing … Read more
It’s not a way of shuffling that I like, mostly on the grounds that it’s O(n log n) for no good reason when it’s easy to implement an O(n) shuffle. The code in the question “works” by basically giving a random (hopefully unique!) number to each element, then ordering the elements according to that number. … Read more
I solved this by adding a category to NSMutableArray. Edit: Removed unnecessary method thanks to answer by Ladd. Edit: Changed (arc4random() % nElements) to arc4random_uniform(nElements) thanks to answer by Gregory Goltsov and comments by miho and blahdiblah Edit: Loop improvement, thanks to comment by Ron Edit: Added check that array is not empty, thanks to … Read more
Using Collections to shuffle an array of primitive types is a bit of an overkill… It is simple enough to implement the function yourself, using for example the Fisher–Yates shuffle: import java.util.*; import java.util.concurrent.ThreadLocalRandom; class Test { public static void main(String args[]) { int[] solutionArray = { 1, 2, 3, 4, 5, 6, 16, 15, … Read more
Your can use NumPy’s array indexing: def unison_shuffled_copies(a, b): assert len(a) == len(b) p = numpy.random.permutation(len(a)) return a[p], b[p] This will result in creation of separate unison-shuffled arrays.
This answer details how to shuffle with a fast and uniform algorithm (Fisher-Yates) in Swift 4.2+ and how to add the same feature in the various previous versions of Swift. The naming and behavior for each Swift version matches the mutating and nonmutating sorting methods for that version. Swift 4.2+ shuffle and shuffled are native … Read more
You can use shuf. On some systems at least (doesn’t appear to be in POSIX). As jleedev pointed out: sort -R might also be an option. On some systems at least; well, you get the picture. It has been pointed out that sort -R doesn’t really shuffle but instead sort items according to their hash … Read more
import random random.shuffle(array)
The idiomatic way to do this with Pandas is to use the .sample method of your data frame to sample all rows without replacement: df.sample(frac=1) The frac keyword argument specifies the fraction of rows to return in the random sample, so frac=1 means to return all rows (in random order). Note: If you wish to … Read more