pandas concat/merge/join多个数据框，仅此一列 [英] pandas concat/merge/join multiple dataframes with only one column by this column

问题描述

我有(超过)两个数据框:

I have (more than) two dataframes:

In [22]: df = pd.DataFrame({'database' : ['db1', 'db2', 'db3']})                                                                                                                                                             

In [23]: df1 = pd.DataFrame({'database' : ['db1', 'db2', 'db3']})                                                                                                                                                            

In [24]: df2 = pd.DataFrame({'database' : ['db2', 'db3', 'db4']})                                                                                                                                                            

In [25]: df1                                                                                                                                                                                                                 
Out[25]: 
  database
0      db1
1      db2
2      db3

In [26]: df2                                                                                                                                                                                                                 
Out[26]: 
  database
0      db2
1      db3
2      db4

我想要的输出是这种格式的数据帧:

What I want as output is dataframe in this format:

Out[45]: 
  database database
0      db1         
1      db2      db2
2      db3      db3
3               db4

我设法以这种格式获取它:

I manage to get it in this format like this:

df1.index = df1.database.values.ravel()
df2.index = df2.database.values.ravel()
pd.concat([df1, df2], axis=1).fillna('').reset_index(drop=True)                                                                                                                                                              

但是我认为必须有比ravel()函数更好的解决方案.

But I think there must be better solution than this trick with ravel() function.

推荐答案

使用使用list comprehension的更多动态解决方案:

More dynamic solution with list comprehension:

dfs = [df, df1, df2]
dfs1 = [x.set_index('database', drop=False) for x in dfs]
df = (pd.concat(dfs1, axis=1)
        .fillna('')
        .reset_index(drop=True))
print (df)
  database database database
0      db1      db1         
1      db2      db2      db2
2      db3      db3      db3
3                        db4

这篇关于pandas concat/merge/join多个数据框，仅此一列的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！