根据不同的DataFrame在Pandas DataFrame中添加一列

Question

I have these two DataFrames:

df1

       A   B
    0  8   x
    1  3   y
    2  1   x
    3  2   z
    4  7   y

    and

df2    
       A   B
    0  x   hey
    1  y   there
    2  z   sir

I am trying to append df1['B'] based on df2['B'] so that my desired output would be:

df3

       A   B
    0  8   hey
    1  3   there
    2  1   hey
    3  2   sir
    4  7   there

Is there a built in method for doing this kind of transformation? I was experimenting with something similar to this, but I could not get it to function properly:

for x in df1['B']:
    if df2['A'] == x:
        df1['B'].append.df2['B']

Answer 1

I believe you'll want a simple merge:

In [10]: df1.merge(df2, left_on='B', right_on='A')
Out[10]:
   A_x B_x A_y    B_y
0    8   x   x    hey
1    1   x   x    hey
2    3   y   y  there
3    7   y   y  there
4    2   z   z    sir

And if you'd like to keep the order of the index:

In [11]: df1.reset_index().merge(df2, left_on='B', right_on='A').set_index('index').sort_index()
Out[11]:
       A_x B_x A_y    B_y
index
0        8   x   x    hey
1        3   y   y  there
2        1   x   x    hey
3        2   z   z    sir
4        7   y   y  there

Answer 2

you can set column A as an index to look-up values in column B :

>>> df1.B = df2.set_index('A').loc[df1.B,'B'].values
>>> df1
   A      B
0  8    hey
1  3  there
2  1    hey
3  2    sir
4  7  there

[5 rows x 2 columns]