Create a dictionary by keys and values-CodePudding

I'm trying to create a dictionary dico which contains elements like this:

<key>           <values>
comb_element     pageId1, pageId2, .. pageIdn

comb_element are elements of list of tuple comb :

I try with this code to create dico, but I didn't get the correct format of dico

comb=list(set(product(data['OsId'], data['BrowserId'])))
dico={}
dico[tuple(comb)] = list(data['PageId'])

Here what contains comb :

[(12, 16),
 (33, 11),
 (99, 11),
 (11, 14),
 (33, 14),
 (32, 12),
 (99, 14),
 (11, 11),
 (11, 17),
 (32, 15),
 (99, 17),
 (33, 17),
 (11, 99),
 (33, 99),
 (99, 99),
 (12, 12),
 (12, 15),
 (32, 11),
 (11, 16),
 (33, 16),
 (32, 14),
 (99, 16),
 (32, 17),
 (32, 99),
 (12, 11),
 (12, 14),
 (12, 17),
 (12, 99),
 (11, 12),
 (99, 15),
 (33, 12),
 (99, 12),
 (11, 15),
 (32, 16),
 (33, 15)]

Here the dataframe data: in case of (12, 16) as key I would like to attribute the lis of page : 1005581 and 1016529.

Cluster PageId     OsId BrowserId   
0         1005581   11  16  
0         1016529   11  16  
0         1016529   11  17  
0         1016529   12  14  
0         1016529   12  16

So for example, any idea to fix it? thanks

CodePudding user response：

I think the code below might do what you want.

Assuming you have the dataframe in list-of-dicts format, you can just build up the entries in the dictionary dico by appending the 'PageId' value to a list with the (OsId, BrowserId) tuple as its key.

This way you don't need to bother with using product() to get all possible combinations of (OsId, BrowserId), some of which may have no matching PageIds.

        df_as_list_of_dicts = [
            {'Cluster' : 0, 'PageId' : 1005581, 'OsId' : 11, 'BrowserId' : 16},
            {'Cluster' : 0, 'PageId' : 1016529, 'OsId' : 11, 'BrowserId' : 16},
            {'Cluster' : 0, 'PageId' : 1016529, 'OsId' : 11, 'BrowserId' : 17},
            {'Cluster' : 0, 'PageId' : 1016529, 'OsId' : 12, 'BrowserId' : 14},
            {'Cluster' : 0, 'PageId' : 1016529, 'OsId' : 12, 'BrowserId' : 16},
        ]
        dico = {}
        for row in df_as_list_of_dicts:
            tup = (row['OsId'], row['BrowserId'])
            if tup not in dico:
                dico[tup] = []
            dico[tup].append(row['PageId'])
        [print(f"{key} : {value}") for key, value in dico.items()]

Sample output:

(11, 16) : [1005581, 1016529]
(11, 17) : [1016529]
(12, 14) : [1016529]
(12, 16) : [1016529]