From the list of dictionaries find the largest value lengths for each key

user_13800566 0
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data = [{"id": "78ab45",
         "name": "Jonh"},
        {"id": "69cd234457",
         "name": "Joe"}]

I want my function to return the largest value lengths for each key from all dictionaries:

expected_output = [
    { "size": 10, "name": "id" }, #because the length of the largest "id" value is 10
    { "size": 4, "name": "name" }, #because the length of the largest "name" value is 4
]

My code so far:

def my_func(data):
  headers_and_sizes = []
  for item in data:
     for key, value in item.items():
        headers_and_sizes.append({"size": f'{len(value)}', "name": key})
        if int(headers_and_sizes[0]["size"]) < len(value):
            headers_and_sizes[0]["size"] = len(value)
            
  return headers_and_sizes

Gives me this:

[{'size': '6', 'name': 'id'}, {'size': '4', 'name': 'name'}, {'size': '10', 'name': 'id'}, {'size': '3', 'name': 'name'}]

How can I fix that so that it will return the values as in expected_output?

python
6 Answers

You'll want to be updating a dictionary that stores each key mapped to the maximum length seen for that key thus far.

data = [
  {
     "id": "78ab45",
     "name": "Jonh",
  },
  {
     "id": "69cd234457",
     "name": "Joe",
  },
]
key_to_max_len = {}
for datum in data:
   for key, val in datum.items():
        if key not in key_to_max_len or len(val) > key_to_max_len[key]:
            key_to_max_len[key] = len(val)
key_size_arr = [{"size": val, "name": key} for key, val in key_to_max_len.items()]
user_50010900

you can get the max value for id and name like below code, and structure the output accordingly

>>> data 
[{'id': '78ab45', 'name': 'Jonh'}, {'id': '69cd234457', 'name': 'Joe'}]
id  = max(map(lambda x:len(x['id']), data))
name  = max(map(lambda x:len(x['name']), data))
>>> id
10
>>> name
4
user_50862550

You can use list comprehension to form a tuple with ids and names:

names_ids = [(eachdict['id'],eachdict['name']) for eachdict in data]

Format the output to have the desired shape (dictionaries), find the max length (using the max() function, passing it the lengths of names and ids, using another list comprehension, inside max()):

expected_output = \
[{"size":max([len(each[0]) for each in names_ids]),"name":"id"},
 {"size":max([len(each[1]) for each in names_ids]),"name":"name"}]

Output will be:

[{'name': 'id', 'size': 10}, {'name': 'name', 'size': 4}]
user_85654380

Using the following:

keys = list(data[0].keys())
output = {key:-1 for key in keys}
for d in data:
    for k in d.keys():
        if len(d[k]) > output[k]:
            output[k] = len(d[k])

Will output:

{'id': 10, 'name': 4}
user_119182690

I think the easiest method here is pandas...

import pandas as pd
df = pd.DataFrame(data)

out = [{'size': df['id'].str.len().max(), 'name':'id'},
       {'size': df['name'].str.len().max(), 'name':'name'}]

output:

[{'size': 10, 'name': 'id'}, {'size': 4, 'name': 'name'}]

or for addt'l names..

[{'size':df[col].str.len().max(), 'name':col} for col in df.columns]
user_108181280

Here is how you can use a nested dictionary comprehension:

data = [{"id": "78ab45",
         "name": "Jonh"},
        {"id": "69cd234457",
         "name": "Joe"}]


expected_output = [{'size': len(max([i[k] for i in data], key=len)),
                    'name': k} for k in data[0]]

print(expected_output)

Output:

[{'size': 10, 'name': 'id'},
 {'size': 4, 'name': 'name'}]
user_135524700
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