I need to convert a nested for loop with a function call and appending data to a list comprehension.
This is what I would like to convert to a list comprehension
predictions = []
for train_row in test_data:
distances = np.argmin([dist(train_row, test_row) for test_row in train_data])
predictions.append(train_tgt[distances])
On the surface, it's a trivial transformation after inlining the definition of distances:
predictions = []
for train_row in test_data:
distances = ...
predictions.append(train_tgt[distances])
becomes
predictions = []
for train_row in test_data:
predictions.append(train_tgt[...])
which becomes
predictions = [train_tgt[...] for train_row in test_data]
predictions = [train_tgt[np.argmin([euclideanDistance(train_row, test_row) for test_row in train_data])] for train_row in test_data]