Python将值分组到两列中

数据帧如下所示。这些名称分为5组，通过A列中的公用项链接

我想把名字分组。我试过：

import pandas as pd

data = {'A': ["James","James","James","Edward","Edward","Thomas","Thomas","Jason","Jason","Jason","Brian","Brian"], 
'B' : ["John","Michael","William","David","Joseph","Christopher","Daniel","George","Kenneth","Steven","Ronald","Anthony"]}
df = pd.DataFrame(data)

df_1 = df.groupby('A')['B'].apply(list)
df_1 = df_1.to_frame().reset_index()

for index, row in df_1.iterrows():
    print (row['A'], row['B'])

这些产出是：

('Brian', ['Ronald', 'Anthony'])
('Edward', ['David', 'Joseph'])
('James', ['John', 'Michael', 'William'])
('Jason', ['George', 'Kenneth', 'Steven'])
('Thomas', ['Christopher', 'Daniel'])

但我希望每个组都有一个列表（如果有一种自动为每个列表分配变量的方法会更好），比如：

我尝试了

row['B'].append（row['A']）

但它返回

None

把他们分组的正确方法是什么？谢谢。你可以试试这个。使用

作为输出，您得到

None

的原因是

list。append

返回

None

它会在适当的位置改变列表。

您可以尝试此操作。使用

---

作为输出，您得到

None

的原因是

list。append

返回

None

它会在适当的位置对列表进行变异。

您可以在

中添加
分组列的值。name
属性：

s = df.groupby('A')['B'].apply(lambda x: [x.name] + list(x))
print (s)
A
Brian             [Brian, Ronald, Anthony]
Edward             [Edward, David, Joseph]
James      [James, John, Michael, William]
Jason     [Jason, George, Kenneth, Steven]
Thomas       [Thomas, Christopher, Daniel]
Name: B, dtype: object

您可以使用
属性在中添加
分组列的值

s = df.groupby('A')['B'].apply(lambda x: [x.name] + list(x))
print (s)
A
Brian             [Brian, Ronald, Anthony]
Edward             [Edward, David, Joseph]
James      [James, John, Michael, William]
Jason     [Jason, George, Kenneth, Steven]
Thomas       [Thomas, Christopher, Daniel]
Name: B, dtype: object

请尝试以下操作：

    import pandas as pd

    data = {'A': ["James","James","James","Edward","Edward","Thomas","Thomas","Jason","Jason","Jason","Brian","Brian"], 
    'B' : ["John","Michael","William","David","Joseph","Christopher","Daniel","George","Kenneth","Steven","Ronald","Anthony"]}
    df = pd.DataFrame(data)
    #display(df)
    df_1 = df.groupby(list('A'))['B'].apply(list)
    df_1 = df_1.to_frame().reset_index()

    for index, row in df_1.iterrows():
        ''' The value of  column A is not a list, 
so need to split the string and store in to a list and then concatenate with column B '''
        print(row['A'].split("delimiter") + row['B'])

输出：

['Brian', 'Ronald', 'Anthony']
['Edward', 'David', 'Joseph']
['James', 'John', 'Michael', 'William']
['Jason', 'George', 'Kenneth', 'Steven']
['Thomas', 'Christopher', 'Daniel']

请尝试以下操作：

    import pandas as pd

    data = {'A': ["James","James","James","Edward","Edward","Thomas","Thomas","Jason","Jason","Jason","Brian","Brian"], 
    'B' : ["John","Michael","William","David","Joseph","Christopher","Daniel","George","Kenneth","Steven","Ronald","Anthony"]}
    df = pd.DataFrame(data)
    #display(df)
    df_1 = df.groupby(list('A'))['B'].apply(list)
    df_1 = df_1.to_frame().reset_index()

    for index, row in df_1.iterrows():
        ''' The value of  column A is not a list, 
so need to split the string and store in to a list and then concatenate with column B '''
        print(row['A'].split("delimiter") + row['B'])

输出：

['Brian', 'Ronald', 'Anthony']
['Edward', 'David', 'Joseph']
['James', 'John', 'Michael', 'William']
['Jason', 'George', 'Kenneth', 'Steven']
['Thomas', 'Christopher', 'Daniel']

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