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Converting NumPy array into Python List structure?

Questions:

How do I convert a NumPy array to a Python List (for example [[1,2,3],[4,5,6]] ), and do it reasonably fast?

Use tolist():

import numpy as np
>>> np.array([[1,2,3],[4,5,6]]).tolist()
[[1, 2, 3], [4, 5, 6]]

Note that this converts the values from whatever numpy type they may have (e.g. np.int32 or np.float32) to the “nearest compatible Python type” (in a list). If you want to preserve the numpy data types, you could call list() on your array instead, and you’ll end up with a list of numpy scalars. (Thanks to Mr_and_Mrs_D for pointing that out in a comment.)

Questions:

NumPy arrays have a tolist method:

In : arr=np.array([[1,2,3],[4,5,6]])

In : arr.tolist()
Out: [[1, 2, 3], [4, 5, 6]]

Questions:

The numpy .tolist method produces nested arrays if the numpy array shape is 2D.

if flat lists are desired, the method below works.

import numpy as np
from itertools import chain

a = [1,2,3,4,5,6,7,8,9]
print type(a), len(a), a
npa = np.asarray(a)
print type(npa), npa.shape, "\n", npa
npa = npa.reshape((3, 3))
print type(npa), npa.shape, "\n", npa
a = list(chain.from_iterable(npa))
print type(a), len(a), a`

Questions:

If you have a ndarray in numpy called narray

Example

narray = [[[ 87 137]] [[ 87 138]] [[ 86 139]][[ 85 140]][[ 85 141]]]
narray = [[[ 84 142]] [[ 84 143]] [[ 83 144]]]
narray = [[[ 82 145]] [[ 81 146]] [[ 80 147]] [[ 79 148]] [[ 78 149]] [[ 77 150]][[ 77 151]]]

You could just loop inside a loop like to extra each element separately

for i in range(len(narray)):
i_narray = narray[i]
for j in range(len(i_narray)):
print(i_narray[j],"\n")

This is the output

[[ 87 137]]

[[ 87 138]]

[[ 86 139]]

[[ 85 140]]

[[ 85 141]]

[[ 84 142]]

[[ 84 143]]

[[ 83 144]]

[[ 82 145]]

[[ 81 146]]

[[ 80 147]]

[[ 79 148]]

[[ 78 149]]

[[ 77 150]]

[[ 77 151]]

Hope it helps someone 🙂