結合1行數據幀和正行數據幀，通過複製1行，並追加到n行數據幀

Question

考慮下面dataframes，D1作爲學生信息和d2爲主題級

>>> data = [['Alice',18]] 
>>> d1 = pd.DataFrame(data,columns=['Name','Age']) 
>>> d1 
    Name Age 
0 Alice 18 
>>> data2 = [['Science','A'],['Math','C'],['English','B']] 
>>> d2 = pd.DataFrame(data2, columns=['Subject','Grade']) 
>>> d2 
    Subject Grade 
0 Science  A 
1  Math  C 
2 English  B 

我想D1和D2與merge + assign + drop這樣

Name Age Subject Grade 
0 Alice 18 Science  A 
1 Alice 18  Math  C 
2 Alice 18 English  B 

Answer 1

使用交叉連接結合起來 - 如果想在d1組合多個行，則此解決方案可用於：

df = pd.merge(d1.assign(A=1), d2.assign(A=1), on='A').drop('A', 1) 
print (df) 
    Name Age Subject Grade 
0 Alice 18 Science  A 
1 Alice 18  Math  C 
2 Alice 18 English  B 

與concat和reindex另一種解決方案：

df = pd.concat([d1.reindex(d2.index, method='ffill'), d2], axis=1) 
print (df) 
    Name Age Subject Grade 
0 Alice 18 Science  A 
1 Alice 18  Math  C 
2 Alice 18 English  B 

Answer 2

您可以用assign

In [101]: d2.assign(**d1.iloc[0]) 
Out[101]: 
    Subject Grade Age Name 
0 Science  A 18 Alice 
1  Math  C 18 Alice 
2 English  B 18 Alice 

或者，

In [102]: d2.assign(**d1.iloc[0].to_dict()) 
Out[102]: 
    Subject Grade Age Name 
0 Science  A 18 Alice 
1  Math  C 18 Alice 
2 English  B 18 Alice 

Answer 3

您可以使用ffill即

CONCAT做

ndf = pd.concat([d1,d2],1).ffill() 

 
    Name Age Subject Grade 
0 Alice 18.0 Science  A 
1 Alice 18.0  Math  C 
2 Alice 18.0 English  B 

Answer 4

爲什麼不重建Dataframe

pd.DataFrame([data[0]+x for x in data2],columns=['Name','Age','Subject', 'Grade']) 
Out[279]: 
    Name Age Subject Grade 
0 Alice 18 Science  A 
1 Alice 18  Math  C 
2 Alice 18 English  B