durden2.0 - 1 year ago 62

Python Question

Is there a way to vectorize an operation that takes several numpy arrays and puts them into a list of dictionaries?

Here's a simplified example. The real scenario might involve more arrays and more dictionary keys.

`import numpy as np`

x = np.arange(10)

y = np.arange(10, 20)

z = np.arange(100, 110)

print [dict(x=x[ii], y=y[ii], z=z[ii]) for ii in xrange(10)]

I might have thousands or hundreds of thousands of iterations in the

`xrange`

`x`

`y`

`z`

I've tried using

`map`

`for`

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Answer Source

Here is one (Num)?Pythonic way:

```
In [18]: names = np.array(['x', 'y', 'z'])
In [38]: map(dict, np.dstack((np.repeat(names[None, :], 10, axis=0), np.column_stack((x, y, z)))))
Out[38]:
[{'x': '0', 'y': '10', 'z': '100'},
{'x': '1', 'y': '11', 'z': '101'},
{'x': '2', 'y': '12', 'z': '102'},
{'x': '3', 'y': '13', 'z': '103'},
{'x': '4', 'y': '14', 'z': '104'},
{'x': '5', 'y': '15', 'z': '105'},
{'x': '6', 'y': '16', 'z': '106'},
{'x': '7', 'y': '17', 'z': '107'},
{'x': '8', 'y': '18', 'z': '108'},
{'x': '9', 'y': '19', 'z': '109'}]
```

Also, note that if you don't need all of the dictionaries at once, you can simply create a generator and access to each item on demand.

```
(dict(x=x[ii], y=y[ii], z=z[ii]) for ii in xrange(10))
```

If you want a nested dictionary, I suggest a list comprehension:

```
In [88]: inner = np.dstack((np.repeat(names[None, :], 10, axis=0), np.column_stack((x, y))))
In [89]: [{'connection': d} for d in map(dict, inner)]
Out[89]:
[{'connection': {'x': '0', 'y': '10'}},
{'connection': {'x': '1', 'y': '11'}},
{'connection': {'x': '2', 'y': '12'}},
{'connection': {'x': '3', 'y': '13'}},
{'connection': {'x': '4', 'y': '14'}},
{'connection': {'x': '5', 'y': '15'}},
{'connection': {'x': '6', 'y': '16'}},
{'connection': {'x': '7', 'y': '17'}},
{'connection': {'x': '8', 'y': '18'}},
{'connection': {'x': '9', 'y': '19'}}]
```

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