The data of a2 and b2 is shared with c. To shuffle both arrays simultaneously, use numpy.random.shuffle(c). In production code, you would of course try to avoid creating the original a and b at all and right away create c, a2 and b2. This solution could be adapted to the case that a and b have different dtypes.
Is there a straightforward way to RETURN a shuffled array in Python rather than shuffling it in place? e.g., instead of . x = [array] random.shuffle(x) I'm looking for something like. y = shuffle(x) which maintains x. Note, I am not looking for a function, not something like: x=[array] y=x random.shuffle(x)
Python Provides the various solutions to shuffle the string: 1. External library: python-string-utils. first install the python-string-utils library. pip install python_string_utils. use string_utils.shuffle () function to shuffle string. please use the below snippet for it.
The other answers are the easiest, however it's a bit annoying that the random.shuffle method doesn't actually return anything - it just sorts the given list. If you want to chain calls or just be able to declare a shuffled array in one line you can do: import random def my_shuffle(array): random.shuffle(array) return array
How can I shuffle a multidimensional array by row only in Python (so do not shuffle the columns). I am looking for the most efficient solution, because my matrix is very h
Do not use the second argument to random.shuffle() to return a fixed value. You are no longer shuffling, you are producing a bad fixed swap sequence ill suited for real work. Use random.seed() instead before calling random.shuffle() with just one argument. See Python shuffle(): Granularity of its seed numbers / shuffle() result diversity.
In case you want the entire population within a given range, As @Ashwini proposed you can use random.shuffle. In Case you are interested in a subset of the population, you can look forward to use random.sample >>> random.sample(range(1,10),5) [3, 5, 2, 6, 7] You may also use this to simulate random.shuffle
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 shuffle your dataframe in-place and ...
I am aware that I can shuffle one list using: import random random.shuffle(a) But this just randomizes a, whereas, I would like to randomize a, and maintain the"randomized order" in list b. Would appreciate any guidance on how this can be achieved.
In some cases when using numpy arrays, using random.shuffle created duplicate data in the array. An alternative is to use numpy.random.shuffle. If you're working with numpy already, this is the preferred method over the generic random.shuffle. numpy.random.shuffle. Example >>> import numpy as np >>> import random Using random.shuffle: