Question

背景

我有两个样本df

这里是df1

import pandas as pd
l =  [list(['ABC', 'DEF', 'GHI'])]
df1 = pd.DataFrame({'Letters': l})

df1
      Letters
 0  [ABC, DEF, GHI]

还有df2

df2 = pd.DataFrame({'Text' : ['Hi ', 
                                       'hey', 
                                       'hello ',
                                        'bye',
                                        'see ya'
                            ], 

                          'ID': [1,2,3, 4,5]
                         })
df2     
        ID Text
    0   1   Hi
    1   2   hey
    2   3   hello
    3   4   bye
    4   5   see ya

所需的输出

    ID Text  Letters
0   1   Hi     [ABC, DEF, GHI]
1   2   hey    [ABC, DEF, GHI]
2   3   hello  [ABC, DEF, GHI]
3   4   bye    [ABC, DEF, GHI]
4   5   see ya [ABC, DEF, GHI]

问题

如何复制df1和df2并合并以获得所需的输出？

Answer 1

您可以这样做：

df2=df2.assign(**pd.concat([df1]*len(df2),ignore_index=True))

或者：

df2=df2.assign(Letters=np.resize(df1.to_numpy(),len(df2))) #df1.values for lower versions

     Text  P_ID          Letters
0     Hi      1  [ABC, DEF, GHI]
1     hey     2  [ABC, DEF, GHI]
2  hello      3  [ABC, DEF, GHI]
3     bye     4  [ABC, DEF, GHI]
4  see ya     5  [ABC, DEF, GHI]

Answer 2

也可以broadcast_to

df2['letters'] = np.broadcast_to(df1['Letters'], len(df2))

    Text    P_ID    letters
0   Hi      1       [ABC, DEF, GHI]
1   hey     2       [ABC, DEF, GHI]
2   hello   3       [ABC, DEF, GHI]
3   bye     4       [ABC, DEF, GHI]
4   see ya  5       [ABC, DEF, GHI]

复制并合并两个数据框熊猫

2 个答案: