Replace column values based on another dataframe python pandas - better way?

Question

Note:for simplicity\'s sake, i\'m using a toy example, because copy/pasting dataframes is difficult in stack overflow (please let me know if there\'s an easy way to do this)

Answer 1

In [27]: This is the correct one.

df.loc[df.Name.isin(df1.Name), ['Nonprofit', 'Education']] = df1[['Nonprofit', 'Education']].values

df
Out[27]:

Name  Nonprofit  Business  Education

0    X          1         1          0
1    Y          1         1          1
2    Z          1         0          1
3    Y          1         1          1

[4 rows x 4 columns]

The above will work only when all rows in df1 exists in df . In other words df should be super set of df1

Incase if you have some non matching rows to df in df1,you should follow below

In other words df is not superset of df1 :

df.loc[df.Name.isin(df1.Name), ['Nonprofit', 'Education']] = 
df1.loc[df1.Name.isin(df.Name),['Nonprofit', 'Education']].values