CODEWITHSUNDEEP
pythonpython-2.7dictionary
Matrix166
Matrix166

Reputation: 79

Comparing values of two dictionary's items

I need to compare the values of the items in two different dictionaries. Let's say that dictionary RawData has items that represent phone numbers and number names.

Rawdata for example has items like: {'name': 'Customer Service', 'number': '123987546'} {'name': 'Switchboard', 'number': '48621364'}

Now, I got dictionary FilteredData, which already contains some items from RawData: {'name': 'IT-support', 'number': '32136994'} {'name': 'Company Customer Service', 'number': '123987546'}

As you can see, Customer Service and Company Customer Service both have the same values, but different keys. In my project, there might be hundreds of similar duplicates, and we only want unique numbers to end up in FilteredData.

FilteredData is what we will be using later in the code, and RawData will be discarded.

Their names(keys) can be close duplicates, but not their numbers(values)**

There are two ways to do this.

A. Remove the duplicate items in RawData, before appending them into FilteredData.

B. Append them into FilteredData, and go through the numbers(values) there, removing the duplicates. Can I use a set here to do that? It would work on a list, obviously.

I'm not looking for the most time-efficient solution. I'd like the most simple and easy to learn one, if and when someone takes over my job someday. In my project it's mandatory for the next guy working on the code to get a quick grip of it.

I've already looked at sets, and tried to face the problem by nesting two for loops, but something tells me there gotta be an easier way.

Of course I might have missed the obvious solution here.

Thanks in advance!

Upvotes: 0

Views: 63

Answers (4)

Tim
Tim

Reputation: 3407

I take the numbers are unique. Then, another solution would be taking advantage of the uniqueness of dictionary keys. This means converting each list of dictionary to a dictionary of 'number:name' pairs. Then, you simple need to update RawData with FilteredData.

RawData = [
  {'name': 'Customer Service', 'number': '123987546'},
  {'name': 'Switchboard', 'number': '48621364'}
]

FilteredData = [
  {'name': 'IT-support', 'number': '32136994'},
  {'name': 'Company Customer Service', 'number': '123987546'}
]

def convert_list(input_list):
    return {item['number']:item['name'] for item in input_list}

def unconvert_dict(input_dict):
    return [{'name':val, 'number': key} for key, val in input_dict.items()]

NewRawData = convert_list(RawData)
NewFilteredData = conver_list(FilteredData)

DesiredResultConverted = NewRawData.update(NewFilteredData)
DesuredResult = unconvert_dict(DesiredResultConverted)

In this example, the variables will have the following values:

NewRawData = {'123987546':'Customer Service', '48621364': 'Switchboard'}
NewFilteredData = {'32136994': 'IT-support', '123987546': 'Company Customer Service'}

When you update NewRawData with NewFilteredData, Company Customer Service will overwrite Customer Service as the value associated with the key 123987546. So,

DesiredResultConverted = {'123987546':'Company Customer Service', '48621364': 'Switchboard', '32136994': 'IT-support'}

Then, if you still prefer the original format, you can "unconvert" back.

Upvotes: 1

user9772620
user9772620

Reputation:

I hope I understands your problem here:

data = [{'name': 'Customer Service', 'number': '123987546'}, {'name': 'Switchboard', 'number': '48621364'}]
newdata = [{'name': 'IT-support', 'number': '32136994'}, {'name': 'Company Customer Service', 'number': '123987546'}]

def main():
    numbers = set()
    for entry in data:
        numbers.add(entry['number'])
    for entry in newdata:
        if entry['number'] not in numbers:
            data.append(entry)
    print data

main()

Output:

[{'name': 'Customer Service', 'number': '123987546'},
 {'name': 'Switchboard', 'number': '48621364'},
 {'name': 'IT-support', 'number': '32136994'}]

Upvotes: 1

fixatd
fixatd

Reputation: 1404

If you're willing on changing how FilteredData is currently, you can just use a dict and use the number as your key:

RawData = [
  {'name': 'Customer Service', 'number': '123987546'},
  {'name': 'Switchboard', 'number': '48621364'}
]

# Change how FilteredData is structured
FilteredDataMap = {
  '32136994': 
  {'name': 'IT-support', 'number': '32136994'},
  '123987546':
  {'name': 'Company Customer Service', 'number': '123987546'}
}

for item in RawData:
  number = item.get('number')
  if number not in FilteredDataMap:
    FilteredDataMap[number] = item

# If you need the list of items
FilteredData = list(FilteredDataMap.values())

You can just pull the actual list from the Map using .values()

Upvotes: 1

Novak
Novak

Reputation: 2171

What you can do is take a dict.values(), create a set of those to remove duplicates and then go through the old dictionary and find the first key with that value and add it to a new one. Keep the set around because when you get the next dict entry, try adding the element to that set and see if the length of the set is longer that before adding it. If it is, it's a unique element and you can add it to the dict.

Upvotes: 1

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