I have a numpy array
[['5.1', '3.5', '1.4', '0.2', 'Setosa'],
['4.9', '3.0', '1.4', '0.2', 'Versicolor']]
How to convert it to a dictionary such that
{['5.1', '3.5', '1.4', '0.2']:'Setosa', ['4.9', '3.0', '1.4', '0.2']:'Versicolor'}
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I'm assuming you ment 'Setosa' and 'Versicolor' instead of 'Iris-setosa' in that example output, right?Joost– Joost2014-04-06 11:22:02 +00:00Commented Apr 6, 2014 at 11:22
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2this isn't really specific to numpy is it?TooTone– TooTone2014-04-06 11:55:57 +00:00Commented Apr 6, 2014 at 11:55
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1@TooTone Indeed. The solution I proposed works fine on regular nested lists as well.Joost– Joost2014-04-06 12:43:39 +00:00Commented Apr 6, 2014 at 12:43
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@Joost I know: I tried it :)TooTone– TooTone2014-04-06 12:47:05 +00:00Commented Apr 6, 2014 at 12:47
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1 Answer
The dictionary you're currently specifying is invalid, since the keys of your dictionaries cannot be list objects. However, you could change them to tuples. As tuples are immutable, they can be used as keys.
A dictionary comprehension that converts the sample case you have provided might look like this:
a = numpy.array([['5.1', '3.5', '1.4', '0.2', 'Setosa'],
['4.9', '3.0', '1.4', '0.2', 'Versicolor']])
b = {tuple(x[:-1]) : x[-1] for x in a}
It creates a tuple from the first n-1 elements of each list, and then assigns the last element as the value. The resulting dictionary looks like this:
{('5.1', '3.5', '1.4', '0.2'): 'Setosa', ('4.9', '3.0', '1.4', '0.2'): 'Versicolor'}
