Q:

Creating a list of dictionaries from separate lists

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?

A:

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}]

