如何使用重複的值合併兩個數據幀中的大熊貓

Question

我有熊貓2個dataframes：

dilevery_time dispatch_time source_lat source_long Address name 
0 21:39:37.265 21:47:37.265 -73.955741 40.3422  Dmart John 
0 21:39:37.265 21:47:37.265 -73.955741 40.3422  Dmart John 

而另一種是：

chef_name dish_name dish_price dish_quantity ratings 
0 xyz  Chicken  120   1    4 
1 abc  Paneer  100   2    3 

我想在大熊貓加入這兩個dataframes。我已經執行了連接，但不允許我執行，因爲第一個數據幀具有重複的值。

所以，我已經做到了這一點：

pd.concat([df1, df2], join='inner', axis=1) 

但是這給了我下面的輸出：

dilevery_time dispatch_time source_long Address name chef_name 
0 21:39:37.265 21:47:37.265 -73.955741 Dmart John xyz 
0 21:39:37.265 21:47:37.265 -73.955741 Dmart John xyz 

    dish_name dish_price dish_quantity ratings 
0 Chicken  120    1    4 
0 Chicken  120    1    4 

而且我想在此格式：

dilevery_time dispatch_time source_long Address name chef_name 
0 21:39:37.265 21:47:37.265 -73.955741 Dmart John xyz 
0 21:39:37.265 21:47:37.265 -73.955741 Dmart John abc 

    dish_name dish_price dish_quantity ratings 
0 Chicken  120    1    4 
0 Paneer  100    2    3 

怎麼辦它在熊貓？

Answer 1

這是因爲在第一個數據幀中索引0有兩次。您可以使用reset_index方法，然後得到您的結果：

In [9]: df 
Out[9]: 
    chef_name dish_name dish_price dish_quantity ratings 
0  xyz Chicken   120    1  4 
1  abc Paneer   100    2  3 

In [10]: df1 
Out[10]: 
    chef_name dish_name dish_price dish_quantity ratings 
0  xyz Chicken   120    1  4 
1  abc Paneer   100    2  3 

df1.reset_index(drop=True, inplace 

In [11]: pd.concat([df1, df2], join='inner', axis=1) 
Out[11]: 
    chef_name dish_name dish_price dish_quantity ratings dilevery_time \ 
0  xyz Chicken   120    1  4 21:39:37.265 
1  abc Paneer   100    2  3 21:39:37.265 

    dispatch_time source_lat source_long Address name 
0 21:47:37.265 -73.955741  40.3422 Dmart John 
1 21:47:37.265 -73.955741  40.3422 Dmart John