Convert Dictionary to Numpy array

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I am trying to convert the dictionary 

{0: {0: 173, 1: 342, 2: 666, 3: 506, 4: 94},
 1: {0: 13, 1: 2171, 2: 1915, 3: 3075, 4: 630},
 2: {0: 0, 1: 265, 2: 5036, 3: 508, 4: 11},
 3: {0: 0, 1: 3229, 2: 2388, 3: 3649, 4: 193},
 4: {0: 3, 1: 151, 2: 591, 3: 1629, 4: 410}}

to numpy array 

array([[ 173,  342,  666,  506,   94],
       [  13, 2171, 1915, 3075,  630],
       [   0,  265, 5036,  508,   11],
       [   0, 3229, 2388, 3649,  193],
       [   3,  151,  591, 1629,  410]])

Any ideas how to do it efficiently?

numpy-ndarray python-3.x numpy dictionary python
1 Answers

A Python-level loop is unavoidable here, so you can use a list comprehension:

res = np.array([list(item.values()) for item in d.values()])

# array([[ 173,  342,  666,  506,   94],
#        [  13, 2171, 1915, 3075,  630],
#        [   0,  265, 5036,  508,   11],
#        [   0, 3229, 2388, 3649,  193],
#        [   3,  151,  591, 1629,  410]])

As per @FHTMitchell's comment, this assumes your dictionary items (inner and outer) are ordered appropriately. Dictionaries are insertion ordered in 3.6 as a CPython implementation detail, and officially in 3.7+.

One way to define an order for inner and outer dictionaries is via operator.itemgetter:

getter = itemgetter(*range(5))
res = np.array([getter(item) for item in getter(d)])

Such a solution does not depend on the order of your input dictionary.

user_92095460
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