Extract numpy array columns into dictionary

Question

I'm creating manually a dictionary of features and numpy array.

columns = ['a', 'b', 'c', 'd']
features = {'a': df_train.values[:, 0],
            'b': df_train.values[:, 1],
            'c': df_train.values[:, 2],
            'd': df_train.values[:, 3]}

df_train is a Pandas dataframe originated from pandas.read_csv()

I'm using this code to simplify it:

features = {c: df_train.values[:, i] for i, c in enumerate(columns)}

Is there a more Pythonic way? (dict with zip for example?)

You got it in a single line. That's as Pythonic as it gets I am afraid. You can probably use different methods as you suggest, but the outcome will be the same. Are you implying a more computationally efficient way? — b-fg
– b-fg, Commented Oct 24, 2018 at 3:52
No, I don't think there's a more pythonic way. Following up on the comment by @b-fg you don't necessarily get "pythonic" from having a 1-liner but, in this case, it's perfectly readable and efficient. — roganjosh
– roganjosh, Commented Oct 24, 2018 at 3:58
@b-fg spend a bit more time on SO and you'll see some catastrophic 1-liners :P. The dict comprehension here is fine, but there's also a broader misunderstanding with some people that cramming everything into one line with horrible time complexity wins. — roganjosh
– roganjosh, Commented Oct 24, 2018 at 4:06
@roganjosh, Yes understand where you come from hehe. And we are on the same page ;) — b-fg
– b-fg, Commented Oct 24, 2018 at 4:08
"dict with zip"? Yes, there is: dict(zip(columns, df_train.values.T)) — Paul Panzer
– Paul Panzer, Commented Oct 24, 2018 at 4:38

Paul Panzer · Accepted Answer · 2018-10-24 05:02:26Z

3

You can use the transpose:

dict(zip(columns, df_train.values.T))

or

{k: v for k, v in zip(columns, df_train.values.T)}

answered Oct 24, 2018 at 5:02

Paul Panzer

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