For example:
persons = [{'id': 1, 'name': 'john'}, {'id': 2, 'name': 'mary'}, {'id': 3, 'name': 'tom'}]
I want to get two lists from it:
ids = [1, 2, 3]
names = ['john', 'mary', 'tom']
What I did:
names = [d['name'] for d in persons]
ids = [d['id'] for d in persons]
Is there a better way to do it?
What you did works fine. Another way to handle this (not necessarily better, depending on your needs) is to store your data in a more efficient dictionary and pull the names/ids out of it when you need them:
>>> persons = [{'id': 1, 'name': 'john'}, {'id': 2, 'name': 'mary'}, {'id': 3, 'name': 'tom'}]
>>> p2 = {x['id']: x['name'] for x in persons}
>>> p2
{1: 'john', 2: 'mary', 3: 'tom'}
>>> list(p2.keys())
[1, 2, 3]
>>> list(p2.values())
['john', 'mary', 'tom']
I'd stick with using list comprehension or use @Woodford technique
ids,name = [dcts['id'] for dcts in persons],[dcts['name'] for dcts in persons]
output
[1, 2, 3]
['john', 'mary', 'tom']
An alternative, inspired by this question, is
ids, names = zip(*map(lambda x: x.values(), persons))
that return tuples. If you need lists
ids, names = map(list, zip(*map(lambda x: x.values(), persons)))
It is a little bit slower on my laptop using python3.9 than the accepted answer but it might be useful.
You can do it with pandas in a vectorized fashion:
import pandas as pd
persons = [{'id': 1, 'name': 'john'}, {'id': 2, 'name': 'mary'}, {'id': 3, 'name': 'tom'}]
df = pd.DataFrame(persons)
id_list = df.id.tolist() #[1, 2, 3]
name_list = df.name.tolist() #['john', 'mary', 'tom']
It sounds like you're trying to iterate through the values of your list while unpacking your dictionaries:
persons = [{'id': 1, 'name': 'john'}, {'id': 2, 'name': 'mary'}, {'id': 3, 'name': 'tom'}]
for x in persons:
id, name = x.values()
ids.append(id)
names.append(name)
