Creating a list of dictionaries from separate lists

data-structures, dictionary, list, python

Solution

You can use a list comprehension with `zip` after transposing your dataset:

>>> [dict(zip(data_types, x)) for x in zip(*data)]
[{'place': 'Toronto', 'name': 'tom', 'year': 1990}, 
 {'place': 'New York', 'name': 'jim', 'year': 2000}, 
 {'place': 'Paris', 'name': 'mark', 'year': 2000}]

Problem

I honestly expected this to have been asked previously, but after 30 minutes of searching I haven't had any luck. Say we have multiple lists, each of the same length, each one containing a different type of data about something. We would like to turn this into a list of dictionaries with the data type as the key. input: ``` data = [['tom', 'jim', 'mark'], ['Toronto', 'New York', 'Paris'], [1990,2000,2000]] data_types = ['name', 'place', 'year'] ``` output: ``` travels = [{'name':'tom', 'place': 'Toronto', 'year':1990}, {'name':'jim', 'place': 'New York', 'year':2000}, {'name':'mark', 'place': 'Paris', 'year':2001}] ``` This is fairly easy to do with index-based iteration: ``` travels = [] for d_index in range(len(data[0])): travel = {} for dt_index in range(len(data_types)): travel[data_types[dt_index]] = data[dt_index][d_index] travels.append(travel) ``` But this is 2017! There has to be a more concise way to do this! We have map, flatmap, reduce, list comprehensions, numpy, lodash, zip. Except I can't seem to compose these cleanly into this particular transformation. Any ideas?

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