I would like to add an id key to a list of dictionaries, where each id represents the enumerated nested dictionary.
Current list of dictionaries:
current_list_d = [{'id': 0, 'name': 'Paco', 'age': 18} #all id's are 0
{'id': 0, 'name': 'John', 'age': 20}
{'id': 0, 'name': 'Claire', 'age': 22}]
Desired output:
output_list_d = [{'id': 1, 'name': 'Paco', 'age': 18} #id's are counted/enumerated
{'id': 2, 'name': 'John', 'age': 20}
{'id': 3, 'name': 'Claire', 'age': 22}]
My code:
for d in current_list_d:
d["id"]+=1
You could use a simple for loop with enumerate and update in-place the id keys in the dictionaries:
for new_id, d in enumerate(current_list_d, start=1):
d['id'] = new_id
current_list_d
[{'id': 1, 'name': 'Paco', 'age': 18},
{'id': 2, 'name': 'John', 'age': 20},
{'id': 3, 'name': 'Claire', 'age': 22}]
You can use a variable.
id_val = 1
for dict in current_list_d :
dict["id"] = id_val
id_val+=1
Related
I am new to python and learning how to use a dictionary comprehension. I have a movie cast dictionary that I would like to filter on a specific value using the dictionary comprehension technique. I was able to get it work but for some reason I get empty dictionaries added as well if the condition is not met. Why does it do it? And how can I ensure these are not included?
movie_cast = [{'id': 90633,'name': 'Gal Gadot','cast_id': 0, 'order': 0},
{'id': 62064, 'name': 'Chris Pine','cast_id': 15, 'order': 1},
{'id': 41091, 'name': 'Kristen Wiig', 'cast_id': 12,'order': 2},
{'id': 41092, 'name': 'Pedro Pascal', 'cast_id': 13, 'order': 3},
{'id': 32, 'name': 'Robin Wright', 'cast_id': 78, 'order': 4}]
limit = 1
cast_limit = []
for dict in movie_cast:
d = {key:value for (key,value) in dict.items() if dict['order'] < limit}
cast_limit.append(d)
print(cast_limit)
current_result = [{'id': 90633,'name': 'Gal Gadot','cast_id': 0, 'order': 0},
{'id': 62064, 'name': 'Chris Pine','cast_id': 15, 'order': 1},{},{},{}]
desired_result = [{'id': 90633,'name': 'Gal Gadot','cast_id': 0, 'order': 0},
{'id': 62064, 'name': 'Chris Pine','cast_id': 15, 'order': 1}]
Try with this (you need a list comprehension, not a dict comprehension):
cast_limit = [dct for dct in movie_cast if dct['order'] < limit]
I.e., you need to filter out elements of the list, not elements of a dict.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 1 year ago.
Improve this question
I have a list of dicts (same format) like this :
L = [
{'id': 1, 'name': 'john', 'age': 34},
{'id': 1, 'name': 'john', 'age': 34},
{'id': 2, 'name': 'hanna', 'age': 30},
{'id': 2, 'name': 'hanna', 'age': 30},
{'id': 3, 'name': 'stack', 'age': 40}
]
I want to remove duplication and get the number of this duplication like this
[
{'id': 1, 'name': 'john', 'age': 34, 'duplication': 2},
{'id': 2, 'name': 'hanna', 'age': 30, 'duplication': 2},
{'id': 3, 'name': 'stack', 'age': 40, 'duplication': 1}
]
I already managed to remove the duplication by using a set.... but I can't get the number of duplications
my code :
no_duplication = [dict(s) for s in set(frozenset(d.items()) for d in L)]
no_duplication = [
{'id': 1, 'name': 'john', 'age': 34},
{'id': 2, 'name': 'hanna', 'age': 30},
{'id': 3, 'name': 'stack', 'age': 40}
]
Here is a solution you can give a try using collections.Counter,
from collections import Counter
print([
{**dict(k), "duplicated": v}
for k, v in Counter(frozenset(i.items()) for i in L).items()
])
[{'age': 34, 'duplicated': 2, 'id': 1, 'name': 'john'},
{'age': 30, 'duplicated': 2, 'id': 2, 'name': 'hanna'},
{'age': 40, 'duplicated': 1, 'id': 3, 'name': 'stack'}]
ar = [
{'id': 1, 'name': 'john', 'age': 34},
{'id': 1, 'name': 'john', 'age': 34},
{'id': 2, 'name': 'hanna', 'age': 30},
{'id': 2, 'name': 'hanna', 'age': 30},
{'id': 3, 'name': 'stack', 'age': 40}
]
br = []
cnt = []
for i in ar:
if i not in br:
br.append(i)
cnt.append(1)
else:
cnt[br.index(i)] += 1
for i in range(len(br)):
br[i]['duplication'] = cnt[i]
The desired output is contained in br as:
[
{'id': 1, 'name': 'john', 'age': 34, 'duplication': 2},
{'id': 2, 'name': 'hanna', 'age': 30, 'duplication': 2},
{'id': 3, 'name': 'stack', 'age': 40, 'duplication': 1}
]
This is my data set, this is the column I separated from the csv file.
0 [{'id': 16, 'name': 'Animation'}, {'id': 35, '...
1 [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...
2 [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...
3 [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...
4 [{'id': 35, 'name': 'Comedy'}]
How to get just a list with the content ['Animation', 'Adventure', 'Romance', 'Comedy', 'Comedy'] as output?
I guess you want to see something like that.
list_of_items = [[{'id': 16, 'name': 'Animation'}, {'id': 16, 'name': 'Animation2'}],[{'id': 16, 'name': 'Animation3'}, {'id': 16, 'name': 'Animation4'}]]
output_list = []
for item in list_of_items:
for dict in item:
output_list.append(dict['name'])
Output:
>>> print(output_list)
['Animation', 'Animation2', 'Animation3', 'Animation4']
I don't know if you made a typo but you have some errors with the ' in what you wrote.
But nevertheless from what I can see you have a list with dictionaries. So we loop through that list to access each dictionary and select what in the dictionary we want and append it to the list you created:
d = [{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]
list_1 = []
for el in d:
list_1.append(el['name'])
print(list_1)
The output will be: ['Romance', 'Comedy']
It's unclear if you have a list of lists or just one list.
For a single list you can use a list comprehension:
dict_list = [{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]
[dict_item['name'] for dict_item in dict_list]
Otherwise, you can unnest the first list and then do a list comprehension
dict_list = [[{'id': 1, 'name': 'Animation'}, {'id': 2, 'name': 'Comedy'}],[{'id': 3, 'name': 'Romance'}, {'id': 4, 'name': 'Comedy'}]]
[dict_item['name'] for dict_item in [dict_item for sublist in dict_list for dict_item in sublist]]
Suppose I have a named list as follows:
myListOfPeople = [{'ID': 0, 'Name': 'Mary', 'Age': 25}, {'ID': 1, 'Name': 'John', 'Age': 28}]
I want to select the element (not only the field) where an specific field meets certain criteria, e.g., the element with the minimum 'Age'. Something like:
youngerPerson = [person for person in myListOfPeople if person = ***person with minimum age***]
And will get as answer:
>>youngerPerson: {'ID': 0, 'Name': Mary, 'Age': 25}
How can I do that?
You can use the key parameter of min:
>>> myListOfPeople = [{'ID': 0, 'Name': 'Mary', 'Age': 25}, {'ID': 1, 'Name': 'John', 'Age': 28}]
>>>
>>> min(myListOfPeople, key=lambda x: x["Age"])
{'ID': 0, 'Name': 'Mary', 'Age': 25}
>>>
You can use itemgetter :
from operator import itemgetter
myListOfPeople = [{'ID': 0, 'Name': 'Mary', 'Age': 25}, {'ID': 1, 'Name': 'John', 'Age': 28}]
sorted(myListOfPeople, key=itemgetter('Age'))[0]
# {'ID': 0, 'Name': 'Mary', 'Age': 25}
I'm looking for pythonic way to convert list of tuples which looks like this:
res = [{type: 1, name: 'Nick'}, {type: 2, name: 'Helma'}, ...]
To dict like this:
{1: [{type: 1, name: 'Nick'}, ...], 2: [{type: 2, name: 'Helma'}, ...]}
Now i do this with code like this (based on this question):
d = defaultdict(list)
for v in res:
d[v["type"]].append(v)
Is this a Pythonic way to build dict of lists of objects by attribute?
I agree with the commentators that here, list comprehension will lack, well, comprehension.
Having said that, here's how it can go:
import itertools
a = [{'type': 1, 'name': 'Nick'}, {'type': 2, 'name': 'Helma'}, {'type': 1, 'name': 'Moshe'}]
by_type = lambda a: a['type']
>>> dict([(k, list(g)) for (k, g) in itertools.groupby(sorted(a, key=by_type), key=by_type)])
{1: [{'name': 'Nick', 'type': 1}, {'name': 'Moshe', 'type': 1}], ...}
The code first sorts by 'type', then uses itertools.groupby to group by the exact same critera.
I stopped understanding this code 15 seconds after I finished writing it :-)
You could do it with a dictionary comprehension, which wouldn't be as illegible or incomprehensible as the comments suggest (IMHO):
# A collection of name and type dictionaries
res = [{'type': 1, 'name': 'Nick'},
{'type': 2, 'name': 'Helma'},
{'type': 3, 'name': 'Steve'},
{'type': 1, 'name': 'Billy'},
{'type': 3, 'name': 'George'},
{'type': 4, 'name': 'Sylvie'},
{'type': 2, 'name': 'Wilfred'},
{'type': 1, 'name': 'Jim'}]
# Creating a dictionary by type
res_new = {
item['type']: [each for each in res
if each['type'] == item['type']]
for item in res
}
>>>res_new
{1: [{'name': 'Nick', 'type': 1},
{'name': 'Billy', 'type': 1},
{'name': 'Jim', 'type': 1}],
2: [{'name': 'Helma', 'type': 2},
{'name': 'Wilfred', 'type': 2}],
3: [{'name': 'Steve', 'type': 3},
{'name': 'George', 'type': 3}],
4: [{'name': 'Sylvie', 'type': 4}]}
Unless I missed something, this should give you the result you're looking for.