使用字典向pandas数据框添加列

Question

我想根据字典向现有的数据框架中添加列。如果我的数据帧看起来像这样：

import pandas as pd
column_names=['name','surname','age']
lfa=[("tom","jones",44),("elvis","prestley",50),("jim","reeves",30)]
lfa=pd.DataFrame(lfa,columns=column_names)
lfa

我的字典是这样的：

new_cols= {"adj1":"adjustment1","adj2":"adjustment2"}

然后，我尝试获取一个数据帧，如下所示：

column_names=['name','surname','age','adj1','adj2']
lfa=[("tom","jones",44,"adjustment1","adjustment2"), 
("elvis","prestley",50,"adjustment1","adjustment2"), 
("jim","reeves",30,"adjustment1","adjustment2")]
lfa=pd.DataFrame(lfa,columns=column_names)
lfa

Answer 1

通过**将DataFrame.assign与解压缩字典一起使用

df = lfa.assign(**new_cols)
print (df)
    name   surname  age         adj1         adj2
0    tom     jones   44  adjustment1  adjustment2
1  elvis  prestley   50  adjustment1  adjustment2
2    jim    reeves   30  adjustment1  adjustment2

或DataFrame.join

df = lfa.join(pd.DataFrame(new_cols, index=lfa.index))
print (df)
    name   surname  age         adj1         adj2
0    tom     jones   44  adjustment1  adjustment2
1  elvis  prestley   50  adjustment1  adjustment2
2    jim    reeves   30  adjustment1  adjustment2

Answer 2

您也可以通过以下方式完成此操作：-

lfa[list(new_cols.keys())]=new_cols.values()

print(lfa)
    name    surname     age     adj1        adj2
0   tom     jones       44  adjustment1     adjustment2
1   elvis   prestley    50  adjustment1     adjustment2
2   jim     reeves      30  adjustment1     adjustment2

Answer 3

一种方法是使用pd.concat

In [533]: df = pd.concat([lfa, pd.DataFrame(new_cols, index=lfa.index)], 1)

In [534]: df
Out[534]: 
    name   surname  age         adj1         adj2
0    tom     jones   44  adjustment1  adjustment2
1  elvis  prestley   50  adjustment1  adjustment2
2    jim    reeves   30  adjustment1  adjustment2