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Combining three different list collection of dictionary having same value in key name “firstname” and “lastname” in python

I have three different list collection of dictionary as shown all three have same "firstname" and lastname". I need to combine this list in a copy of one without replicating the firstname and lastname, ie for each firstname and lastname a combination of the other three list collection of dictionary:
list one
[{'First Name': 'Justin',
'lastName': 'Walker',
'Age (Years)': '29',
'Sex': 'Male',
'Vehicle Make': 'Toyota',
'Vehicle Model': 'Continental',
'Vehicle Year': '2012',
'Vehicle Type': 'Sedan'},
{'First Name': 'Maria',
'lastName': 'Jones',
'Age (Years)': '66',
'Sex': 'Female',
'Vehicle Make': 'Mitsubishi',
'Vehicle Model': 'Yukon XL 2500',
'Vehicle Year': '2014',
'Vehicle Type': 'Van/Minivan'},
{'First Name': 'Samantha',
'lastName': 'Norman',
'Age (Years)': '19',
'Sex': 'Female',
'Vehicle Make': 'Aston Martin',
'Vehicle Model': 'Silverado 3500 HD Regular Cab',
'Vehicle Year': '1995',
'Vehicle Type': 'SUV'}
list two
[{'firstName': 'Justin',
'lastName': 'Walker',
'age': 71,
'iban': 'GB43YKET96816855547287',
'credit_card_number': '2221597849919620',
'credit_card_security_code': '646',
'credit_card_start_date': '03/18',
'credit_card_end_date': '06/26',
'address_main': '462 Marilyn radial',
'address_city': 'Lynneton',
'address_postcode': 'W4 0GW'},
{'firstName': 'Maria',
'lastName': 'Jones',
'age': 91,
'iban': 'GB53QKRK45175204753504',
'credit_card_number': '4050437758955103343',
'credit_card_security_code': '827',
'credit_card_start_date': '11/21',
'credit_card_end_date': '01/27',
'address_main': '366 Brenda radial',
'address_city': 'Ritafurt',
'address_postcode': 'NE85 1RG'}]
list three
{'firstName': 'Justin',
'lastName': 'Walker',
'age': '64',
'sex': 'Male',
'retired': 'False',
'dependants': '2',
'marital_status': 'single',
'salary': '56185',
'pension': '0',
'company': 'Hudson PLC',
'commute_distance': '14.1',
'address_postcode': 'G2J 0FH'},
{'firstName': 'Maria',
'lastName': 'Jones',
'age': '69',
'sex': 'Female',
'retired': 'False',
'dependants': '1',
'marital_status': 'divorced',
'salary': '36872',
'pension': '0',
'company': 'Wall, Reed and Whitehouse',
'commute_distance': '10.47',
'address_postcode': 'TD95 7FL'}
This is what I trying but
for i in range(0,2):
dict1 = list_one[i]
dict2 = list_two[i]
dict3 = list_three[i]
combine_file = list_three.copy()
for k, v in dict1.items():
if k == "firstname" or "lastname":
for k1, v1 in combine_file.items():
if dict1.get(k) == combine_file.v1:
This is what I'm expecting
print(combine_file)
{'firstName': 'Justin',
'lastName': 'Walker',
'age': '64',
'sex': 'Male',
'retired': 'False',
'dependants': '2',
'marital_status': 'single',
'salary': '56185',
'pension': '0',
'company': 'Hudson PLC',
'commute_distance': '14.1',
'iban': 'GB43YKET96816855547287',
'credit_card_number': '2221597849919620',
'credit_card_security_code': '646',
'credit_card_start_date': '03/18',
'credit_card_end_date': '06/26',
'address_main': '462 Marilyn radial',
'address_city': 'Lynneton',
'address_postcode': 'W4 0GW',
'Vehicle Make': 'Mitsubishi',
'Vehicle Model': 'Yukon XL 2500',
'Vehicle Year': '2014',
'Vehicle Type': 'Van/Minivan'},
{'firstName': 'Maria',
'lastName': 'Jones',
'age': '69',
'sex': 'Female',
'retired': 'False',
'dependants': '1',
'marital_status': 'divorced',
'salary': '36872',
'pension': '0',
'company': 'Wall, Reed and Whitehouse',
'commute_distance': '10.47',
'iban': 'GB53QKRK45175204753504',
'credit_card_number': '4050437758955103343',
'credit_card_security_code': '827',
'credit_card_start_date': '11/21',
'credit_card_end_date': '01/27',
'address_main': '366 Brenda radial',
'address_city': 'Ritafurt',
'address_postcode': 'NE85 1RG',
'Vehicle Make': 'Aston Martin',
'Vehicle Model': 'Silverado 3500 HD Regular Cab',
'Vehicle Year': '1995',
'Vehicle Type': 'SUV'}

Create a new dictionary keyed on a composite of either 'firstname_lastname' or 'First Name_lastname' then you can do this:
master = {}
for _list in list_1, list_2, list_3:
for d in _list:
if not (firstname := d.get('firstName')):
firstname = d['First Name']
name_key = f'{firstname}_{d["lastName"]}'
for k, v in d.items():
master.setdefault(name_key, {})[k] = v
print(list(master.values()))

Python's dict.update() functionality might be what you are looking for.
For example:
dict1 = { 'a' : 0,
'b' : 1,
'c' : 2}
dict2 = { 'c' : 0,
'd' : 1,
'e' : 2}
dict2.update(dict1)
dict2 is now:
{'a' : 0, 'b': 1, 'c': 2, 'd' 1, 'e': 2}
Notice how 'c' was overwritten with the updated value from dict1.
You can't update together dictionaries from different people, but if you run through your lists beforehand you could compile sets of dictionaries where each set belongs to one person.
You can create a new dictionary, called people, and then iterate through your lists of dictionaries and extract the person's name from those dictionaries and turn it into a key in the new "people" dictionary.
If that person's name is not in people yet, you can add that dictionary, so that people[name] points to that dictionary.
If people[name] does exist, then you can use the people[name].update() function on the new dictionary to add the new values.
After this process, you will have a dictionary whose keys are the names of people and the values point to a dictionary containing those people's attributes.

How to get maximum value of one entity in nested dictionary?

people = {1: {'Name': 'John', 'Age': '22', 'Sex': 'Male'}, 2: {'Name': 'Marie', 'Age': '26', 'Sex': 'Female'}, 3: {'Name': 'Marie', 'Age': '25', 'Sex': 'Female'}, 4: {'Name': 'Marie', 'Age': '21', 'Sex': 'Female'}}
I want to get the maximum value of 'Age'. Kindly help me how to do this.

You can use max with a defined key and lambda.
people = {1: {'Name': 'John', 'Age': '22', 'Sex': 'Male'}, 2: {'Name': 'Marie', 'Age': '26', 'Sex': 'Female'}, 3: {'Name': 'Marie', 'Age': '25', 'Sex': 'Female'}, 4: {'Name': 'Marie', 'Age': '21', 'Sex': 'Female'}}
max(people.values(), key=lambda x: int(x['Age']))
# {'Name': 'Marie', 'Age': '26', 'Sex': 'Female'}
max(people.values(), key=lambda x: int(x['Age']))['Age']
# '26'

If you wanted just the max value then max with a generator would suffice
people = {1: {'Name': 'John', 'Age': '22', 'Sex': 'Male'}, 2: {'Name': 'Marie', 'Age': '26', 'Sex': 'Female'}, 3: {'Name': 'Marie', 'Age': '25', 'Sex': 'Female'}, 4: {'Name': 'Marie', 'Age': '21', 'Sex': 'Female'}}
result = max(int(p['Age']) for p in people.values())
Which I prefer over the lambda, however if you want the dictionary that has the max Age then #I'mahdi answer is what you want.

Get specific the nested key/values based on a condition from python nested dictionary

I'm stuck parsing the below python nested dictionary based on the nested key. I want to filter a key's value and return all the nested key/values related to that.
{ 'US': { 'Washington': {'Seattle': {1: {'name': 'John', 'age': '27', 'gender': 'Male'}}},
{ 'Florida': {'some city': {2: {'name': 'Marie', 'age': '22', 'gender': 'Female'}}},
{ 'Ohio': {'some city': {3: {'name': 'Luna', 'age': '24', 'gender': 'Female', 'married': 'No'}}},
{ 'Nevada': {'some city': {4: {'name': 'Peter', 'age': '29', 'gender': 'Male', 'married': 'Yes'}}}}}
For instance, filtering on gender "Male" should return the below:
US
Washington
Seattle
1
name:John
age: 27
US
Nevada
somecity
4
name:Peter
age: 29
married: Yes
Can you please suggest the best way to parse it. I tried to use contains within a loop that doesn't seem to work.

We can recursively explore the dict structure, keeping track of the path of keys at each point. When we reach a dict containing the target value, we yield the path and the content of the dict.
We can use this generator:
def recursive_search(dct, target, path=None):
if path is None:
path = []
if target in dct.values():
out = ' '.join(path) + ' ' + ' '.join(f'{key}:{value}' for key, value in dct.items())
yield out
else:
for key, value in dct.items():
if isinstance(value, dict):
yield from recursive_search(value, target, path+[str(key)])
this way:
data = { 'US': { 'Washington': {'Seattle': {1: {'name': 'John', 'age': '27', 'gender': 'Male'}}},
'Florida': {'some city': {2: {'name': 'Marie', 'age': '22', 'gender': 'Female'}}},
'Ohio': {'some city': {3: {'name': 'Luna', 'age': '24', 'gender': 'Female', 'married': 'No'}}},
'Nevada': {'some city': {4: {'name': 'Peter', 'age': '29', 'gender': 'Male', 'married': 'Yes'}}}}}
for match in recursive_search(data, 'Male'):
print(match)
# US Washington Seattle 1 name:John age:27 gender:Male
# US Nevada some city 4 name:Peter age:29 gender:Male married:Yes

This Code Will work...
a_dict={ 'US': { 'Washington': {'Seattle': {1: {'name': 'John', 'age': '27', 'gender': 'Male'}}}, 'Florida': {'some city': {2: {'name': 'Marie', 'age': '22', 'gender': 'Female'}}}, 'Ohio': {'some city': {3: {'name': 'Luna', 'age': '24', 'gender': 'Female', 'married': 'No'}}}, 'Nevada': {'some city': {4: {'name': 'Peter', 'age': '29', 'gender': 'Male', 'married': 'Yes'}}}}}
for k,v in a_dict.items():
for k1,v1 in v.items():
for k2,v2 in v1.items():
for k3,v3 in v2.items():
if v3["gender"]=="Male":
string=""
for k4,v4 in v3.items():
string=string+ k4+":"+v4+" "
print(k,k1,k2,k3, string.strip())

Extracting key value pair and transpose nested dict

From this below data
people = {1: {'name': 'John', 'age': '27', 'sex': 'Male'},
2: {'name': 'Marie', 'age': '22', 'sex': 'Female'},
3: {'name': 'Luna', 'age': '24', 'sex': 'Female'},
4: {'name': 'Peter', 'age': '29', 'sex': 'Male'}}
How do I extract all the names: ex: ['John','Marie','Luna','Peter']
How do I transpose this dict and get something like below
new_dict = {name: {'John','Marie','Luna','Peter'},
age:{'27','22','24','29'},
sex:{'Male','Female','Female','Male'}}

Create a dataframe from your dict like:
import pandas as pd
df = pd.DataFrame.from_dict(people)
Transpose the dataframe
df2 = df.T
Convert the dataframe to dict
df2.to_dict

how do i remove a duplicate lines in a list using a function?

def remove_repeated_lines(data):
lines_seen = set() # holds lines already seen
d=[]
for t in data:
if t not in lines_seen: # check if line is not duplicate
d.append(t)
lines_seen.add(t)
return d
a=[{'name': 'paul', 'age': '26.', 'hometown': 'AU', 'gender': 'male'},
{'name': 'mei', 'age': '26.', 'hometown': 'NY', 'gender': 'female'},
{'name': 'smith', 'age': '16.', 'hometown': 'NY', 'gender': 'male'},
{'name': 'raj', 'age': '13.', 'hometown': 'IND', 'gender': 'male'}]
age=[]
for line in a:
for key,value in line.items():
if key == 'age':
age.append(remove_repeated_lines(value.replace('.','___')))
print(age)
the output is
[['2', '6', '___'], ['2', '6', '___'], ['1', '6', '___'], ['1', '3', '___']]
my desired output is ['26___','16___','13___']
Here is my code to remove repeated lines from the value of a dictionary. After I run the code, the repeated lines are not remove.

In [37]: a=[{'name': 'paul', 'age': '26.', 'hometown': 'AU', 'gender': 'male'},
...: {'name': 'mei', 'age': '26.', 'hometown': 'NY', 'gender': 'female'},
...: {'name': 'smith', 'age': '16.', 'hometown': 'NY', 'gender': 'male'},
...: {'name': 'raj', 'age': '13.', 'hometown': 'IND', 'gender': 'male'}]
In [40]: set(i["age"].replace(".","")+"_" for i in a)
Out[40]: {'13_', '16_', '26_'}

You can use set comprehension to do it with ease, in a more readable fashion:
age = list({
line['age'].replace('.', '___')
for line in a
if 'age' in line
})
Output:
['26___', '16___', '13___']