Can I create a numpy array of dictionary values from an array of dictionary keys?

Question

Say I have a dictionary:

d = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

Given a numpy array** of keys, e.g. ['a' 'c' 'e'], is there an easy way to create a numpy array of the corresponding values, e.g. [1 3 5]?

** for reasons of the context I'm using this in, I'd prefer to input/output numpy arrays. Something similar can obviously be done with lists:

keys = ['a', 'c', 'e']
values = []

for k in keys:
    values.append(d[k])

print(values)
[1, 3, 5]

But I am wondering if there is a built-in way to do something like this in numpy.

No, the compiled numpy code does not have anything special for dictionaries. — hpaulj
– hpaulj, Commented Nov 23, 2019 at 17:20

sacuL · Accepted Answer · 2019-11-23 16:44:01Z

1

You could do this with a structured array and np.in1d.

import numpy as np

d = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

# Create structured array (modify formats, names as necessary):
names = ['key', 'data']  
formats = ['U10', 'i4']                                                                        
dtype = dict(names = names, formats = formats)

arr = np.array(list(d.items()), dtype=dtype)

# >>> arr
# array([('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)],
#       dtype=[('key', '<U10'), ('data', '<i4')])

# use np.in1d to get your keys:

keys = ['a', 'c', 'e']

values = arr[np.in1d(arr['key'], keys)]['data']                                                

# >>> values
# array([1, 3, 5], dtype=int32)

answered Nov 23, 2019 at 16:44

sacuL

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1 Comment

Mad Physicist Over a year ago

This is incredibly convoluted and essentially pointless (turning an O(1) looking into an O(n)). I love it.

LWChris · Accepted Answer · 2019-11-23 16:59:41Z

1

If you just require to have numpy arrays as input and output but don't insist on using a numpy function to handle them, you can use numpy.array() on the result of a list comprehension:

import numpy as np

d = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}
keys = np.array(['a', 'c', 'e'])
values = np.array([d[k] for k in keys])

print(values)

answered Nov 23, 2019 at 16:59

LWChris

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2 Comments

hpaulj Over a year ago

A list comprehension is a streamlined for loop, but otherwise not much a change from the OP's approach.

LWChris Over a year ago

I would still recommend to use list comprehension over append, because it is much faster.

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