如何合并特定的数据框？

Question

我正在与一个大型数据框合并进行摔跤，但这是一个非常小的问题...循环工作，但它太慢......

import pandas as pd  
import numpy as np


df = pd.DataFrame({"A": [1,1,2,2,2,3,3,3,3,4,4], 
               "B": [ np.nan , 10, np.nan, 20, np.nan, np.nan,np.nan,np.nan,np.nan,40, np.nan]})

In[1]: df
Out[1]: 
    A     B
0   1   NaN
1   1  10.0
2   2   NaN
3   2  20.0
4   2   NaN
5   3   NaN
6   3   NaN
7   3   NaN
8   3   NaN
9   4  40.0
10  4   NaN

如何获得df2，没有循环 - ？

df2 = pd.DataFrame({"A": [1,1,2,2,2,3,3,3,3,4,4], 
               "B": [ 10 , 10, 20, 20, 20, np.nan,np.nan,np.nan,np.nan,40, 40]})

In[1]: df2
Out[18]: 
A     B
0   1  10.0
1   1  10.0
2   2  20.0
3   2  20.0
4   2  20.0
5   3   NaN
6   3   NaN
7   3   NaN
8   3   NaN
9   4  40.0
10  4  40.0

Answer 1

IIUC你可以这样做：

In [91]: df.groupby('A').apply(lambda x: x.ffill().bfill())
Out[91]:
    A     B
0   1  10.0
1   1  10.0
2   2  20.0
3   2  20.0
4   2  20.0
5   3   NaN
6   3   NaN
7   3   NaN
8   3   NaN
9   4  40.0
10  4  40.0

Answer 2

如果每个子组只有一个值

df.B=df.A.map(df.set_index('A').dropna().B.to_dict())
df
Out[717]: 
    A     B
0   1  10.0
1   1  10.0
2   2  20.0
3   2  20.0
4   2  20.0
5   3   NaN
6   3   NaN
7   3   NaN
8   3   NaN
9   4  40.0
10  4  40.0