You aren't performing any DML here - and you can't, because your aggregate query doesn't return any Ids as you've aggregated them:
SELECT Name, Prospect_Code__c , COUNT(Id) ids ...
You'll have to perform a second query based on the
Prospect_Code__c of each
AggregateResult to find the Accounts you're considering duplicated and update them. Your
Map<String, Boolean> is not really going to help here.
You can iterate over the
AggregateResult list to perform one query each, which puts you in limits trouble. There's a better but much more complex approach I'll sketch here, but you'll have to write a fair amount of code to implement it.
First, accumulate a set of composite keys: the combinations of Name and Prospect Code that are duplicated. I'd do this with a
Set<String> compositeKeySet, where the values are something like
Prospect_Code__c + '\n' + Name. Then, accumulate sets of
Prospect_Code__c values and perform a single, bulkified, but overly broad query:
SELECT Name, Prospect_Code__c FROM Account WHERE Name IN :nameSet AND Prospect_Code__c IN :prospectCodeSet
Then, iterate over the results of that query. For each Account in the results, check if its composite key (
Prospect_Code__c + '\n' + Name) is in
compositeKeySet. If it is, you know its specific combination of Name and Prospect Code was one of those identified as a duplicate. You can then update that Account.
It's important to bear in mind that this is a very expensive operation in terms of the queries you're going to run and how much system resources they require. It is likely you will have to implement this as an Apex batch class, or even two Apex batch classes - one to run the first query, chaining into the second to actually process the results. How critical the architecture ends up being is heavily dependent on the data volume in the target org and the extent of the duplication.
If you don't have experience tuning query performance and implementing this kind of architecture, I'd encourage taking advantage of this opportunity to work with a senior developer on your team or in your local user group to work out the complex details.