从熊猫列表的字典中删除重复项

Question

我正试图从没有重复的数据框中提取字典。

以下是数据框：

{'Country': {0: 'Japan', 1: 'China', 2: 'USA', 3: 'Russia', 4: 'Japan', 
5: 'Japan', 6: 'China'}, 'Port': {0: 'Yokohama', 1: 'Ningbo', 2: 
'Baltimore', 3: 'Moscow', 4: 'Tokyo', 5: 'Tokyo', 6: 'Shanghai'}}

我将国家/地区设置为键并删除了重复项。现在，我需要从列表中删除重复项

import pandas as pd
a ={'Country': {0: 'Japan', 1: 'China', 2: 'USA', 3: 'Russia', 4: 'Japan', 
5: 'Japan', 6: 'China'}, 'Port': {0: 'Yokohama', 1: 'Ningbo', 2: 
'Baltimore', 3: 'Moscow', 4: 'Tokyo', 5: 'Tokyo', 6: 'Shanghai'}}

a_dict=a.groupby(['Country'])['Port'].apply(list).to_dict()
print(a_dict)

输出：

{'China': ['Ningbo', 'Shanghai'], 'Japan': ['Yokohama', 'Tokyo', 
'Tokyo'], 'Russia': ['Moscow'], 'USA': ['Baltimore']}

预期输出：

{'China': ['Ningbo', 'Shanghai'], 'Japan': ['Yokohama', 'Tokyo'], 
'Russia': ['Moscow'], 'USA': ['Baltimore']}

Answer 1

使用drop_duplicates和您的代码：

d = df.drop_duplicates().groupby(['Country'])['Port'].apply(list).to_dict()

print(d)
{'China': ['Ningbo', 'Shanghai'], 'Japan': ['Yokohama', 'Tokyo'], 
 'Russia': ['Moscow'], 'USA': ['Baltimore']}

Answer 2

GroupBy.apply与set

df.groupby('Country')['Port'].apply(set).map(list).to_dict()

如果您不在乎输出是列表或集合的字典，则可以简化为

df.groupby('Country')['Port'].apply(set).to_dict()

---

defaultdict

from collections import defaultdict

d = defaultdict(set)
for c, p in zip(df['Country'], df['Port']):
    d[c].add(p)

{k: list(v) for k, v in d.items()}