Convert 2D numpy.ndarray to nested dictionary

Assumed a as your array,

Try this,

{index:{i:j for i,j in enumerate(k) if j} for index,k in enumerate(a)}

Result

{0: {0: 50}, 1: {1: 3, 2: 47}, 2: {1: 36, 2: 14}}

Dictionary created with the concept:

In [18]: dict([[1,'a'],[2,'b']])
Out[18]: {1: 'a', 2: 'b'}

You can do that with a pair of nested for loops.

The built-in enumerate function steps through a list or other iterable, giving us both the item and its index.

import numpy as np

a = np.array(
    [[50,  0,  0],
    [ 0,  3, 47],
    [ 0, 36, 14]]
)

d = {}
for i, row in enumerate(a):
    temp = {}
    for j, v in enumerate(row):
        if v:
            temp[j] = v
    d[i] = temp

print(d)

output

{0: {0: 50}, 1: {1: 3, 2: 47}, 2: {1: 36, 2: 14}}

That can be condensed considerably by using a nested pair of dictionary comprehensions:

d = {i: {j: v for j, v in enumerate(row) if v}
    for i, row in enumerate(a)}

Just loop through and build your nested dicts:

import numpy as np

arr = np.array([[50,  0,  0],
               [ 0,  3, 47],
               [ 0, 36, 14]])

d = {}
for i, row in enumerate(arr):  
    d[i] = {}
    for j, cell in enumerate(row):
        if cell != 0:
            d[i][j] = cell

This function should work for a 2-D array and 1-D array as well. Additionally you can make it work for list with int/float just by commenting the first line of the function.

def arrtodict(your_array):
    your_array = your_array.tolist()
    dict_data = {key: value for key, value in enumerate(your_array)}

    if type(dict_data[0]) is list: 
        for key, value in dict_data.items():
            dict_data[key] = {k: v for k, v in enumerate(value)}
    elif type(dict_data[0]) is (float or int):
        pass
    else:
        print ('Check Your data')
    return dict_data