合并pandas数据帧中的2列，用前面的值填充nan

Question

我有一个数据帧：

         State                           RegionName
0      Alabama                              Alabama
1          NaN                               Auburn
2          NaN                             Florence
3          NaN                         Jacksonville
4          NaN                           Livingston
5          NaN                           Montevallo
6          NaN                                 Troy
7          NaN                           Tuscaloosa
8          NaN                             Tuskegee
9       Alaska                               Alaska
10         NaN                            Fairbanks
11     Arizona                              Arizona
12         NaN                            Flagstaff
13         NaN                                Tempe
14         NaN                               Tucson

我怎么回去

DataFrame([["Alabama", "Auburn"], 
           ["Alabama", "Florence"], .
            .., 
           ["Alaska", "Fairbanks"],  
           ["Arizona", "Flagstaff"],  
           ...], columns=["State", "RegionName"])

所以所有的值都很好地合并了？你知道吗

我试过：df['State'] = df['State'].apply(lambda x: df['RegionName'])但它缺乏在新的RegionName启动时为RegionName分配新状态的逻辑。你知道吗

Answer 1

需要^{}：

df['State'] = df['State'].ffill()
print (df)
      State    RegionName
0   Alabama       Alabama
1   Alabama        Auburn
2   Alabama      Florence
3   Alabama  Jacksonville
4   Alabama    Livingston
5   Alabama    Montevallo
6   Alabama          Troy
7   Alabama    Tuscaloosa
8   Alabama      Tuskegee
9    Alaska        Alaska
10   Alaska     Fairbanks
11  Arizona       Arizona
12  Arizona     Flagstaff
13  Arizona         Tempe
14  Arizona        Tucson

Answer 2

你可以试试菲娜。你知道吗

df=pd.DataFrame([["Alabama", "Auburn"],
               [np.nan, "Florence"],
               [np.nan, "Fairbanks"],
               ["Arizona", "Flagstaff"]], columns=["State", "RegionName"])
df
Out[94]: 
     State RegionName
0  Alabama     Auburn
1      NaN   Florence
2      NaN  Fairbanks
3  Arizona  Flagstaff


df.fillna(method='ffill')
Out[95]: 
     State RegionName
0  Alabama     Auburn
1  Alabama   Florence
2  Alabama  Fairbanks