python - 组合/合并具有重复名称的两个数据集

Question

我尝试合并两个数据集(DataFrame)，如下所示:

D1 = pd.DataFrame({'Village':['Ampil','Ampil','Ampil','Bachey','Bachey','Center','Center','Center','Center'], 'Code':[123,324,190,453,321,786,456,234,987]})

D2 = pd.DataFrame({'Village':['Ampil','Ampil','Bachey','Bachey','Center','Center'],'Lat':[11.563,13.278,12.637,11.356,12.736,13.456], 'Long':[102.234,103.432,105.673,103.539,103.873,102.983]})

我想根据 Village 列合并两者。我希望输出如下所示:

D3 = pd.DataFrame({'Village': ['Ampil','Ampil','Bachey','Bachey','Center','Center'],'Code':[123,324,453,321,786,456],'Lat':[11.563,13.278,12.637,11.356,12.736,13.456], 'Long':[102.234,103.432,105.673,103.539,103.873,102.983]})

我尝试过连接、合并和连接，但都不符合目的。我需要一个适用于更大数据的代码。如果有人能提供帮助，我真的很感激。

Answer 1

一种方法是首先按 Village 为初始 dfs 创建一个正在运行的 cumcount，然后按 Village 和 count 合并:

df1['count'] = df1.groupby('Village').cumcount()
df2["count"] = df2.groupby('Village').cumcount()

print (df2.merge(df1,on=["Village","count"],how="left").drop("count",axis=1))

#
      Village     Lat     Long  Code
0   Ampil  11.563  102.234   123
1   Ampil  13.278  103.432   324
2  Bachey  12.637  105.673   453
3  Bachey  11.356  103.539   321
4  Center  12.736  103.873   786
5  Center  13.456  102.983   456