## Permute list of lists with mixed elements (np.random.permutation() fails with ValueError)

Question

I'm trying to permute a list composed of sublists with mixed-type elements:

```
import numpy as np
a0 = ['122', 877.503017, 955.471176, [21.701201, 1.315585]]
a1 = ['176', 1134.076908, 1125.504758, [19.436181, 0.9987899]]
a2 = ['177', 1038.686843, 1018.987868, [19.539959, 1.183997]]
a3 = ['178', 878.999081, 1022.050447, [19.6448771, 1.1867719]]
a = [a0, a1, a2, a3]
b = np.random.permutation(a)
```

This will fail with:

```
ValueError: cannot set an array element with a sequence
```

Is there a built in function that will allow me to generate such permutation?

I need to generate a single random permutation, I'm not trying to obtain all the possible permutations.

I checked the three answers given with:

```
import time
import random
# np.random.permutation()
start = time.time()
for _ in np.arange(100000):
b = np.random.permutation([np.array(i, dtype='object') for i in a])
print(time.time() - start)
# np.random.shuffle()
start = time.time()
for _ in np.arange(100000):
b = a[:]
np.random.shuffle(b)
print(time.time() - start)
# random.shuffle()
start = time.time()
for _ in np.arange(100000):
random.shuffle(a)
print(time.time() - start)
```

The results are:

```
1.47580695152
0.11471414566
0.26300907135
```

so the `np.random.shuffle()`

solution is about 10x faster than `np.random.permutation()`

and 2x faster than `random.shuffle()`

.

Show source

## Answers to Permute list of lists with mixed elements (np.random.permutation() fails with ValueError) ( 4 )

You need to convert your list to numpy arrays with with type

`object()`

, so that`random.permutation()`

can interpret the lists as numpy types rather than sequence:You can also use create a uniqe array from your lists using

`numpy.array()`

instead of using a list comprehension:What about using np.random.shuffle?

See this answer for the difference between

`shuffle`

and`permutation`

random.shuffle() changes the list in place.

Python API methods that alter a structure in-place generally return None.

Please try

`random.sample(a,len(a))`

The code would look like:

If you just want to create a random permutation of

`a = [a0, a1, a2, a3]`

, might I suggest permuting the indices instead?If you're using numpy

justfor this, skip numpy altogether instead and just use`random.shuffle`

to effect the same: