lokiysh :
I have a Numpy 2D array, and a list of headers. Each row of the Numpy array is a record to be mapped to the header list. In the end, I want to convert each record to a dictionary (and so have a list of dictionaries). For example:
A = [[1, 2, 3], [4, 5, 6]]
headers = ['a', 'b', 'c']
Output:
[{'a' : 1, 'b' : 2, 'c' : 3}, {'a' : 4, 'b' : 5, 'c' : 6}]
What is the fastest way to achieve this in Python? I have in the order of 10^4 rows and 10 headers, and running it is taking me roughly 0.3 seconds.
At this moment, I have the following code:
current_samples = A # The samples described above as input, a Numpy array
locations = []
for i, sample in enumerate(current_samples):
current_location = dict()
for index, dimension in enumerate(headers):
current_location[dimension] = sample[index]
locations.append(current_location)
Dani Mesejo :
result = [dict(zip(headers, l)) for l in A]
print(result)
Output
[{'a': 1, 'b': 2, 'c': 3}, {'a': 4, 'b': 5, 'c': 6}]
With zip you create pair of items from the list and pass it to the dictionary constructor.
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