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    2. 将数据框转换为元组列表字典

      时间:2023-08-31
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                本文介绍了将数据框转换为元组列表字典的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                问题描述

                我有一个如下所示的数据框

                I have a dataframe that looks like the following

                    user                             item  
                0  b80344d063b5ccb3212f76538f3d9e43d87dca9e          The Cove - Jack Johnson   
                1  b80344d063b5ccb3212f76538f3d9e43d87dca9e  Entre Dos Aguas - Paco De Lucia   
                2  b80344d063b5ccb3212f76538f3d9e43d87dca9e            Stronger - Kanye West   
                3  b80344d063b5ccb3212f76538f3d9e43d87dca9e    Constellations - Jack Johnson   
                4  b80344d063b5ccb3212f76538f3d9e43d87dca9e      Learn To Fly - Foo Fighters   
                
                rating  
                0       1  
                1       2  
                2       1  
                3       1  
                4       1  
                

                并想实现如下结构:

                dict-> list of tuples
                user-> (item, rating)
                
                b80344d063b5ccb3212f76538f3d9e43d87dca9e -> list((The Cove - Jack 
                Johnson, 1), ... , )
                

                我能做到:

                item_set = dict((user, set(items)) for user, items in 
                data.groupby('user')['item'])
                

                但这只会让我半途而废.如何从 groupby 中获取相应的评分"值?

                But that only gets me halfways. How do I get the corresponding "rating" value from the groupby?

                推荐答案

                设置user为索引,使用df.apply转换成元组,使用分组索引df.groupby(level=0) 并使用 dfGroupBy.agg 获取列表并使用 df.to_dict 转换为字典:

                Set user as index, convert to tuple using df.apply, groupby index using df.groupby(level=0) and get a list using dfGroupBy.agg and convert to dictionary using df.to_dict:

                In [1417]: df
                Out[1417]: 
                                                       user                             item  
                0  b80344d063b5ccb3212f76538f3d9e43d87dca9e          The Cove - Jack Johnson   
                1  b80344d063b5ccb3212f76538f3d9e43d87dca9e  Entre Dos Aguas - Paco De Lucia   
                2  b80344d063b5ccb3212f76538f3d9e43d87dca9e            Stronger - Kanye West   
                3  b80344d063b5ccb3212f76538f3d9e43d87dca9e    Constellations - Jack Johnson   
                4  b80344d063b5ccb3212f76538f3d9e43d87dca9e      Learn To Fly - Foo Fighters   
                
                   rating  
                0       1  
                1       2  
                2       2  
                3       2  
                4       2  
                
                In [1418]: df.set_index('user').apply(tuple, 1)
                             .groupby(level=0).agg(lambda x: list(x.values))
                             .to_dict()
                Out[1418]: 
                {'b80344d063b5ccb3212f76538f3d9e43d87dca9e': [('The Cove - Jack Johnson', 1),
                  ('Entre Dos Aguas - Paco De Lucia', 2),
                  ('Stronger - Kanye West', 2),
                  ('Constellations - Jack Johnson', 2),
                  ('Learn To Fly - Foo Fighters', 2)]}
                

                这篇关于将数据框转换为元组列表字典的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

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