Is there a quick way to “sub-flatten” or flatten only some of the first dimensions in a numpy array?
For example, given a numpy array of dimensions (50,100,25), the resultant dimensions would be (5000,25)
….
I have a dataframe with 2 index levels:
value
Trial measurement
1 0 13
1 3
2 4
2 0 NaN
1 12
3 0 34
Which I want to turn into this:
Trial measurement value
….
import numpy as np
y = np.array(((1,2,3),(4,5,6),(7,8,9)))
OUTPUT:
print(y.flatten())
[1 2 3 4 5 6 7 8 9]
print(y.ravel())
[1 2 3 4 5 6 7 8 9]
Both function return the same list.
Then what is the need of two different functions performing same job.
….
Yes, I know this subject has been covered before (here, here, here, here), but as far as I know, all solutions, except for one, fail on a list like this:
L = [[[1, 2, 3], [4, 5]], 6]
Where the desired output is
[1, 2, 3, 4, 5, 6]
Or perhaps even better, an iterator. The only solution I saw that works for an arbitrary nesting is found in this que….
I want to flatten this list of lists:
[[1, 2, 3], [4, 5, 6], [7], [8, 9]]
into:
[1, 2, 3, 4, 5, 6, 7, 8, 9]